{
  "counts": {
    "adjacent": 14,
    "core": 6,
    "errors": 0,
    "negative": 69,
    "total": 89
  },
  "date": "2026-09-01",
  "errors": [],
  "fresh_content_days": 21,
  "generated_at": "2026-09-01T18:45:00Z",
  "items": [
    {
      "age_days": 6,
      "arxiv_id": "2608.25449",
      "authors": [
        "Jiaxin Yuan",
        "Connor Martinez Lockhart",
        "Xiaoyu Liu",
        "Jiaqi Wang",
        "Chenghao Deng",
        "Xiayimei Han",
        "Vlassis Mastrantonis",
        "Dmitrii Gudin",
        "Shaopeng Zhu",
        "Abdirisak Mohamed",
        "Bilal Aytekin",
        "Jiewen Lang",
        "Zezheng Song",
        "Furong Huang"
      ],
      "content_date": "2026-08-26",
      "freshness": "fresh",
      "id": "arxiv:2608.25449",
      "kind": "paper",
      "label": "core",
      "matched_signals": [
        "general_ai_math_reasoning",
        "lean_formal_proving_agents"
      ],
      "published": "2026-08-26",
      "score": 7.9,
      "source": "arxiv-ai4math-core",
      "summary": "Formal theorem proving enables machine-verifiable evaluation of mathematical reasoning, yet existing benchmarks often emphasize aggregate proof accuracy, concentrate on a narrow range of mathematics, and provide limited evidence of robustness to equivalent reformulations. We introduce MathAdv, a diagnostic benchmark spanning 13 domains across undergraduate- and graduate-level mathematics. Alongside Lean 4 theorem proving, MathAdv provides up to three auxiliary tasks: multiple-choice questions that probe mathematical knowledge, fill-in-the-blank problems that isolate informal reasoning, and expert-crafted transformations that test robustness to problem presentation. Our evaluation of contemporary theorem provers yields four findings: formalization remains a major bottleneck; performance varies substantially across mathematical domains; natural-language guidance helps general-purpose LLMs but can hinder proof-specialized models; and mathematically equivalent reformulations expose substantial robustness limitations. Together, these results show how component-wise evaluation can reveal model capabilities and failure modes that aggregate theorem-proving accuracy obscures. The dataset and evaluation scripts are available at https://github.com/margotyjx/MathAdv.git.",
      "title": "MathAdv: What Theorem Provers Know, Reason, Formalize, and Generalize",
      "updated": "2026-08-28",
      "url": "https://arxiv.org/abs/2608.25449"
    },
    {
      "age_days": 1,
      "arxiv_id": "2608.30238",
      "authors": [
        "Gregory Morse"
      ],
      "content_date": "2026-08-31",
      "freshness": "fresh",
      "id": "arxiv:2608.30238",
      "kind": "paper",
      "label": "core",
      "matched_signals": [
        "lean_formal_proving_agents",
        "verifier_guided_reasoning"
      ],
      "published": "2026-08-31",
      "score": 6.5,
      "source": "arxiv-ai4math-core",
      "summary": "Classical lower bounds show that multiplying two degree-three polynomials over $\\mathbb F_2$ requires nine scalar products in bilinear or quadratic models. They do not settle unrestricted Boolean multiplicative complexity: an XOR--AND circuit may reuse nonlinear intermediate wires, and Boolean equality is taken modulo $x_i^2=x_i$, so a multiplication can lower algebraic degree. Let $\\operatorname{Mul}_4:\\mathbb F_2^8\\to\\mathbb F_2^7$ output the seven coefficients of the product of two four-term binary polynomials. We prove that its unrestricted XOR--AND multiplicative complexity is exactly nine. This resolves, for a natural vector-valued quadratic function, the Boyar--Find question of whether a quadratic-circuit lower bound can persist against unrestricted nonlinear reuse. The proof is structural rather than exhaustive. A useful purely quadratic prefix is forced onto the three rational places of $\\mathbb P^1(\\mathbb F_2)$. In a hypothetical eight-AND circuit, the unique non-useful gate must carry a cubic high part. Any useful continuation then forces a rational tangent and exposes a first Hasse jet, while exterior jet separation together with Boolean idempotence prevents the same defect from exposing the second Hasse jet. The required useful suffix therefore cannot exist. A complete Lean 4 formalization verifies the Boolean-ANF semantics, the unrestricted circuit model, and the exact theorem; it uses no project-specific axiom or native decision procedure. The same zero-defect flag argument gives multiplicative complexity six for three-term multiplication, and the method isolates the multi-defect obstruction for five terms.",
      "title": "Unrestricted Boolean Multiplicative Complexity of Four-Term Binary Polynomial Multiplication: Rational Places, Hasse Jets, and the Failure of Nonlinear Feedback",
      "updated": "2026-08-31",
      "url": "https://arxiv.org/abs/2608.30238"
    },
    {
      "age_days": 3,
      "arxiv_id": "2608.29270",
      "authors": [
        "Hojae Han",
        "Jongyoon Kim",
        "Sanghyuk Park",
        "Dongwook Cheon",
        "Myungjae Jeon",
        "Sunjong Choi",
        "Soonho Kong",
        "Wonseok Heo",
        "Seung-won Hwang",
        "Donghoon Hyeon"
      ],
      "content_date": "2026-08-29",
      "freshness": "fresh",
      "id": "arxiv:2608.29270",
      "kind": "paper",
      "label": "core",
      "matched_signals": [
        "autoformalization",
        "lean_formal_proving_agents"
      ],
      "published": "2026-08-29",
      "score": 6.5,
      "source": "arxiv-ai4math-core",
      "summary": "Autoformalization translates informal mathematical theorems into code for proof assistants such as Lean. A central challenge is that current evaluation metrics can accept type-correct but misaligned statements or reject correct statements written in a different formulation. Inspired by Pass@$k$, we propose SA-Pass (*Semantic Alignment Pass*), which tests formal statements using auxiliary statements called *shadows* that characterize the intended statement. A generated statement receives full credit only when it compiles, implies each shadow (forward check), and is implied by their conjunction (backward check). We instantiate SA-Pass in ShadowBench, a Lean 4 full autoformalization benchmark of 178 postgraduate- to research-level problems spanning eight mathematical areas. Claude Code (Opus 4.8) with Numina-Lean-Agent reaches $61.8\\%$ compile rate and $11.2\\%$ SA-Pass. Across outputs generated by six agentic configurations, SA-Pass achieves $98.8\\%$ binary agreement with expert judgments. An early version of ShadowBench served as the benchmark for Track 4 of the ICML 2026 AI4Math Challenge.",
      "title": "SHADOWBENCH: Toward Reliable Automatic Evaluation of Semantic Alignment in Autoformalization",
      "updated": "2026-08-29",
      "url": "https://arxiv.org/abs/2608.29270"
    },
    {
      "age_days": 4,
      "arxiv_id": "2608.28433",
      "authors": [
        "Shuze Chen",
        "Kunal Marwaha",
        "Xiaoyang Lu",
        "Henry Yuen",
        "Tianyi Peng"
      ],
      "content_date": "2026-08-28",
      "freshness": "fresh",
      "id": "arxiv:2608.28433",
      "kind": "paper",
      "label": "core",
      "matched_signals": [
        "lean_formal_proving_agents",
        "verifier_guided_reasoning"
      ],
      "published": "2026-08-28",
      "score": 6.5,
      "source": "arxiv-ai4math-core",
      "summary": "Proof assistants such as Lean 4 promise the paradigm of formally verified mathematics, but large-scale formalization projects have faced major barriers to entry, including the need for expertise in formal verification (as well as the underlying mathematics) and the significant time required for writing formal proofs. AI coding agents have dramatically reduced these barriers; human users can now use natural language to prompt agents to write complex proofs in Lean. This opens up the intriguing possibility of internet-scale mathematical collaboration involving both humans and AI agents, where correctness is machine-checked. To realize this possibility, we introduce Prove2Me (https://prove2.me), an open collaborative platform for formalizing mathematics. Users launch formalization \"missions\", to which AI agents contribute formal proofs toward completion. We designed mechanisms and a specialized harness in Prove2Me that enable large-scale collaboration so that agents can build on one another's work and freely reuse existing results. In doing so, Prove2Me aims to turn math formalization into a scalable, crowd-sourced effort open to anyone with an agent.",
      "title": "Prove2Me: An Open Collaborative Platform for Scaling Math Formalization",
      "updated": "2026-08-31",
      "url": "https://arxiv.org/abs/2608.28433"
    },
    {
      "age_days": 6,
      "arxiv_id": "2608.26334",
      "authors": [
        "Wenqian Ye",
        "Ziwei Guan",
        "Eric Xie",
        "Bohan Liu",
        "Shivani Modi",
        "Buyun Zhang",
        "Ellie Dingqiao Wen",
        "Henry Kautz",
        "Aidong Zhang"
      ],
      "content_date": "2026-08-26",
      "freshness": "fresh",
      "id": "arxiv:2608.26334",
      "kind": "paper",
      "label": "core",
      "matched_signals": [
        "lean_formal_proving_agents",
        "verifier_guided_reasoning"
      ],
      "published": "2026-08-26",
      "score": 6.5,
      "source": "arxiv-ai4math-core",
      "summary": "Automated theorem proving offers a natural foundation for recursive self-improvement in scientific discovery. However, existing neural provers do not fully preserve this recursive structure, where the learning process should be self-improving over time. Existing methods either embed proof experience into model parameters through expensive weight updates, or keep verified intermediate deductions only within the current problem. In addition, these methods also heavily rely on sparse whole-proof feedback, even when unsuccessful partial attempts contain useful discoveries. To close the gap, we propose ProofEvolve, a neuro-symbolic framework that evolves explicit, formally verified symbolic proof structures with neural models to decisively expand the knowledge boundary. In this framework, the neural model proposes variation operators, including decompositions, repairs, and schema recombinations. The symbolic Lean kernel verifies every proof transition. Over the evolution loops, ProofEvolve computes verified closure over the resulting proof directed acyclic graphs (DAGs). Within each problem, ProofEvolve evolves partial AND-OR proof DAGs in a behaviorally indexed archive. Across problems, kernel-checked schema extraction adds newly proved sub-DAGs to a persistent schema library. Proof DAGs inherit the solved results through typed schema recombination, with every residual premise exposed as a new subgoal. This evolutionary process preserves verified results from incomplete attempts and makes them available for later proofs without weakening formal soundness. Across three competition-level Lean benchmarks, ProofEvolve achieves the highest average solve rate among the evaluated proof systems.",
      "title": "ProofEvolve: Neuro-Symbolic Evolution for Formal Automated Theorem Proving",
      "updated": "2026-08-26",
      "url": "https://arxiv.org/abs/2608.26334"
    },
    {
      "age_days": 7,
      "arxiv_id": "2608.25117",
      "authors": [
        "Hwei-Shin Harriman",
        "Wode Ni",
        "Yuchen Jin",
        "Dominik Moritz",
        "Joshua Sunshine"
      ],
      "content_date": "2026-08-25",
      "freshness": "fresh",
      "id": "arxiv:2608.25117",
      "kind": "paper",
      "label": "core",
      "matched_signals": [
        "lean_formal_proving_agents",
        "verifier_guided_reasoning"
      ],
      "published": "2026-08-25",
      "score": 6.5,
      "source": "arxiv-ai4math-core",
      "summary": "Geometric proof is a foundational yet challenging topic in mathematics, requiring students to integrate visual, logical, and notational skills. While technology has enhanced learning in other mathematical domains, its impact on geometric proof remains limited. To investigate this gap, we interviewed 18 geometry teachers to establish the technical requirements of educational proof tools. These requirements inform our review of 33 commercial and research tools. Our findings reveal a critical mismatch: while teachers value certain digital tools for initial planning and exploration activities, they revert to pen-and-paper for formal proof because it supports diagram annotation and provides space for multiple approaches to proof-solving. Annotating the diagram is a key component of the proof-solving workflow that existing tools do not support. We propose four technical and human-centered design guidelines for educational proof tools to meet teacher needs at scale: integrating diagram and proof, generating problems and feedback automatically, supporting multiple proof formats, and reducing accidental complexity in the user experience.",
      "title": "Teaching Geometric Proof with Tech: Pitfalls and Possibilities",
      "updated": "2026-08-25",
      "url": "https://arxiv.org/abs/2608.25117"
    },
    {
      "age_days": 2,
      "arxiv_id": "2608.29750",
      "authors": [
        "Yinjie Li"
      ],
      "content_date": "2026-08-30",
      "freshness": "fresh",
      "id": "arxiv:2608.29750",
      "kind": "paper",
      "label": "adjacent",
      "matched_signals": [
        "general_ai_math_reasoning",
        "lean_formal_proving_agents"
      ],
      "published": "2026-08-30",
      "score": 4.9,
      "source": "arxiv-ai4math-core",
      "summary": "Harwit and Sloane conjectured that every nonsingular entrywise-nonnegative matrix $A\\in\\mathbb R^{n\\times n}$ satisfies $\\|A^{-1}\\|_F\\ge 2n(n+1)^{-1}\\|A\\|_{\\max}^{-1}$, with equality precisely for positive multiples of $S$-matrices. Cheng proved the conjecture in odd dimensions, while Frankel and Urschel proved the even-dimensional case for $n\\ge1000$. We complete the remaining even-dimensional cases. Starting from the structural identities in Frankel--Urschel Lemma 2.1, we derive an exact global defect budget and combine binary rounding with Gram projection. A refined ten-row obstruction handles every even $n\\ge66$; a finite exact calculation handles $4\\le n\\le64$, $n\\ne6$; and a separate multi-column energy argument treats $n=6$. The order-two case follows from a direct calculation. The new even-dimensional proof has been formalized in Lean 4, with Frankel--Urschel Lemma 2.1 as its sole external mathematical input. Together with Cheng's odd-dimensional theorem, this proves the S-matrix conjecture in every dimension.",
      "title": "The S-matrix conjecture",
      "updated": "2026-08-30",
      "url": "https://arxiv.org/abs/2608.29750"
    },
    {
      "age_days": 2,
      "arxiv_id": "2608.29592",
      "authors": [
        "Jungyeom Kim",
        "Jihyeok Park"
      ],
      "content_date": "2026-08-30",
      "freshness": "fresh",
      "id": "arxiv:2608.29592",
      "kind": "paper",
      "label": "adjacent",
      "matched_signals": [
        "general_ai_math_reasoning",
        "lean_formal_proving_agents"
      ],
      "published": "2026-08-30",
      "score": 4.9,
      "source": "arxiv-ai4math-core",
      "summary": "We resolve three open problems concerning parsing expression grammars (PEGs). We construct a single language $C$ satisfying $C\\in\\mathsf{LIN}\\cap\\mathsf{PEG}$ and $C^R\\in\\mathsf{LIN}\\setminus\\mathsf{PEG}$. This proves that some linear context-free language is not a PEG language and that PEG languages are not closed under reversal, confirming a conjecture of Loff, Moreira, and Reis. Factoring the same witness resolves the concatenation-closure problem of Rubtsov and Chudinov negatively, in the strong form $\\mathsf{PEG}\\cdot\\mathsf{REG}\\not\\subseteq\\mathsf{PEG}$ despite $\\mathsf{REG}\\cdot\\mathsf{PEG}\\subseteq\\mathsf{PEG}$. It also refutes closure under Kleene star, homomorphisms, and substitutions. Our main technique converts scaffolding automata (SCAs), which characterize reversals of PEG languages, into dynamic data structures in the cell-probe model. For any suitably local serialization of a problem with preprocessing, updates, and a final Boolean query, an SCA recognizer yields an exact deterministic cell-probe data structure whose operation costs are proportional to the corresponding encoding lengths. Cell-probe lower bounds can therefore prove SCA non-membership and, by reversal, PEG non-membership. We apply this transfer to Multiphase Inner Product using one-symbol update blocks and a query suffix of length $O(\\log n)$, while keeping both the language and its reversal linear context-free. Ko's cell-probe lower bound then yields the witness above. The arguments are additionally formalized in Lean 4.",
      "title": "Separating Parsing Expression Grammars using Cell-Probe Lower Bounds",
      "updated": "2026-08-30",
      "url": "https://arxiv.org/abs/2608.29592"
    },
    {
      "age_days": 3,
      "arxiv_id": "2608.28997",
      "authors": [
        "Maher Kallel",
        "Mohamed El Louadi"
      ],
      "content_date": "2026-08-29",
      "freshness": "fresh",
      "id": "arxiv:2608.28997",
      "kind": "paper",
      "label": "adjacent",
      "matched_signals": [
        "general_ai_math_reasoning",
        "lean_formal_proving_agents"
      ],
      "published": "2026-08-29",
      "score": 4.9,
      "source": "arxiv-ai4math-core",
      "summary": "In May 2026 an OpenAI model produced a counterexample to the Erdős unit distance conjecture. Five mathematicians published a human-verified version the same day, and the result entered the literature within weeks. In August 2026 the same laboratory published ten mathematical and theoretical computer science results, each accompanied by a machine-checkable Lean 4 certificate with no unproved steps. Four weeks later, one remained the subject of an unresolved dispute over whether its formalization meant what it claimed. We argue that this difference is structural. We distinguish three layers of verification: derivational validity, which a kernel checks; representational fidelity, whether the formal statement means the intended question; and epistemic significance. Only the first is mechanizable. Making it effectively free therefore does not eliminate verification work but shifts the burden to layers dependent on scarce expert attention. Measurements of the August corpus illustrate the shift. The kernel-checked proofs total 20.6 MB, while the statements requiring human audit total 55.6 KB, a ratio of 379 to 1. Yet those statements contain 218 bespoke definitions rather than relying on community-vetted ones. The audit surface is therefore small in volume but irreducibly expert. We argue that machine checking produces verification abundance while leaving adjudication scarce. We propose a six-category taxonomy of representational mismatch, a disclosure schema for machine-generated mathematical claims, and implications for software, cryptography, and regulated decision systems.",
      "title": "Verification abundance, adjudication scarcity: what happens to mathematical knowledge when proof checking becomes free",
      "updated": "2026-08-29",
      "url": "https://arxiv.org/abs/2608.28997"
    },
    {
      "age_days": 4,
      "arxiv_id": "2608.28133",
      "authors": [
        "Zhaorui Wu"
      ],
      "content_date": "2026-08-28",
      "freshness": "fresh",
      "id": "arxiv:2608.28133",
      "kind": "paper",
      "label": "adjacent",
      "matched_signals": [
        "lean_formal_proving_agents"
      ],
      "published": "2026-08-28",
      "score": 3.5,
      "source": "arxiv-ai4math-core",
      "summary": "A $p$-ary bent partition of $\\mathbb{F}_p^n$ is a partition into $K$ nonempty cells such that every balanced assignment of its cells to $\\mathbb{F}_p$ produces a bent function. It was asked whether every possible depth $K$ is a power of $p$; for general $p$, previous affirmative results required regularity or cell-symmetry hypotheses. We prove the stronger unconditional statement that, for every nonzero $h$, exactly $p^n/K$ points remain in the same fine cell under translation by $h$. Thus the fine cells form a partitioned difference family and the fine label map is zero-difference balanced. Consequently $K\\mid p^n$, so $K=p^t$; nonempty cells further give $1\\le t<n$. In even dimension, the classical cell-size theorem yields $K\\mid p^{n/2}$. Together with the known odd-dimensional ternary three-fibre parameter restriction, this gives the global bound $t\\le\\lfloor n/2\\rfloor$. The proof is an exact finite average over balanced coarsenings. The main counting identity and selected consequences are formalized and kernel-checked in Lean 4.",
      "title": "Fine Difference Structure and Prime-Power Depth of Bent Partitions",
      "updated": "2026-08-28",
      "url": "https://arxiv.org/abs/2608.28133"
    },
    {
      "age_days": 4,
      "arxiv_id": "2608.28337",
      "authors": [
        "Julien Grain",
        "Hugo Holland",
        "Lucas Pinol"
      ],
      "content_date": "2026-08-28",
      "freshness": "fresh",
      "id": "arxiv:2608.28337",
      "kind": "paper",
      "label": "adjacent",
      "matched_signals": [
        "lean_formal_proving_agents"
      ],
      "published": "2026-08-28",
      "score": 3.5,
      "source": "arxiv-ai4math-core",
      "summary": "General relativity coupled to multiple scalar fields is a diffeomorphism-invariant constrained system. Consequently, a naive counting of the perturbative degrees of freedom unavoidably overestimates the true number of physical modes propagating in the theory, as gauge redundancies and constraint equations remove non-dynamical ones. While this problem has been solved for linear fluctuations, this work presents the first explicit calculation of all large-scale gauge-invariant phase-space variables in multifield inflation and at second order in perturbation theory, in a Hamiltonian language. Building upon the well-known Sasaki-Mukhanov variables, we show how to construct a finite-dimensional basis of quadratic corrections which are invariant under gauge transformations. Although our procedure is generic to any number of fields and at any scale, we restrict to super-Hubble scales for their explicit solution, which we deliver. Henceforth, we prove that it is possible to recover the usual flat-gauge and comoving-gauge fluctuations as large-scale gauge-invariant combinations, making for a robust consistency check of the gauge-fixed procedure to connect theoretical predictions above the horizon to observations. We derive the quadratic and cubic Hamiltonian of multifield inflation in a gauge independent manner, then we gauge fix our theory by going into the flat gauge, and we show perfect agreement with the literature on this topic, usually based on a Lagrangian approach. After these concrete steps, we propose a more formal proof of the existence of gauge-invariant variables at quadratic order, and we provide a sketch of the procedure that should allow to go to higher orders in perturbation theory.",
      "title": "Explicit gauge-invariant variables in multifield inflation beyond linear order and Hamiltonian dynamics",
      "updated": "2026-08-28",
      "url": "https://arxiv.org/abs/2608.28337"
    },
    {
      "age_days": 4,
      "arxiv_id": "2608.28432",
      "authors": [
        "Jiayan Lin",
        "Yujia Liu",
        "Zijin Hong",
        "Zheng Yuan",
        "Yilin Xiao",
        "Hao Chen",
        "Qinggang Zhang",
        "Xiao Huang",
        "Feiran Huang"
      ],
      "content_date": "2026-08-28",
      "freshness": "fresh",
      "id": "arxiv:2608.28432",
      "kind": "paper",
      "label": "adjacent",
      "matched_signals": [
        "verifier_guided_reasoning"
      ],
      "published": "2026-08-28",
      "score": 3.5,
      "source": "arxiv-ai4math-core",
      "summary": "Recent advances in in-context learning (ICL) text-to-SQL have substantially improved execution accuracy on public benchmarks by assembling increasingly elaborate pipelines around the base generator, yet existing studies typically report aggregate end-to-end accuracy, without quantifying the marginal accuracy-cost contribution of individual design choices. Consequently, providing a unified, paradigm-level cost-accuracy quantification remains a critical challenge for understanding and configuring modern text-to-SQL. To address this, we instantiate 17 paradigm-level configurations across five recurring modules of the ICL text-to-SQL pipeline under a single controlled implementation, and attribute each paradigm's marginal contribution and incurred cost across all four backbones spanning diverse capability levels and reasoning styles. Our analysis reveals that execution-feedback refinement is the only paradigm whose benefit holds universally at consistently low cost, while most other modules help only under backbone-dependent conditions. Token accounting shows that input demand is more closely tied to pipeline structure, whereas output demand is more sensitive to backbone generation behavior. Cross-module analysis further shows that stacking improves accuracy on most backbones, although how the gains compose varies with backbone capability. We also find that a fixed budget is often better spent engineering a more elaborate pipeline over a mid-tier backbone than upgrading to a frontier model with a lean pipeline. These findings distill into an actionable, cost-aware tiered guideline that transfers to five additional backbones without per-paradigm search.",
      "title": "Are These Modules Worth Their Cost? A Paradigm-Level Accuracy-Cost Analysis of In-context Learning Text-to-SQL",
      "updated": "2026-08-28",
      "url": "https://arxiv.org/abs/2608.28432"
    },
    {
      "age_days": 5,
      "arxiv_id": "2608.27451",
      "authors": [
        "Chiké Abuah"
      ],
      "content_date": "2026-08-27",
      "freshness": "fresh",
      "id": "arxiv:2608.27451",
      "kind": "paper",
      "label": "adjacent",
      "matched_signals": [
        "lean_formal_proving_agents"
      ],
      "published": "2026-08-27",
      "score": 3.5,
      "source": "arxiv-ai4math-core",
      "summary": "Empirical comparisons between systems are a standard form of evidence in computer science research, but few are checked for statistical validity: most are never framed as statistical tests at all. Existing multiple-comparison procedures could control the resulting error, but need inputs (what an analysis examined, and how its observations are arranged) that are not recoverable from a list of p-values. We introduce Tacet, a language in which an analysis declares what it generated, states what it expects to find, and is refused any claim it cannot afford or cannot properly test. Its core calculus T pairs a free estimation sublanguage, carrying a reported footprint and a purity bit that records whether any outcome was consulted in building a value, with a priced claim sublanguage, carrying a wealth transformer, connected only by a mechanism that prices a comparison. A sample selected by reading outcomes sets the purity bit and is recorded as having examined everything it read, permanently, so it can never be granted a one-sided or confirmatory price, without the system ever asking whether the analyst intended to cherry-pick. Whether a comparison is paired or clustered is computed statically from the artifact schema, from declared functional dependencies between key fields alone and before any data is read, and a mechanism that assumes that structure away is refused rather than priced. Because the wealth transformer is antitone in the realized p-value, affordability can be checked before the analysis runs too, turning pre-registration into a typing rule. We prove the metatheory machine-checked in Lean 4 with no admitted gaps, and demonstrate the approach on a reference implementation and two case studies on published artifacts, the SWE-bench Verified leaderboard and BIG-Bench Hard.",
      "title": "Tacet: A Language and Type System for Automatic Statistical Validity Accounting",
      "updated": "2026-08-27",
      "url": "https://arxiv.org/abs/2608.27451"
    },
    {
      "age_days": 5,
      "arxiv_id": "2608.27321",
      "authors": [
        "Floris van Doorn",
        "Polona Durcik",
        "Joris Roos",
        "Lenka Slavíková",
        "Christoph Thiele"
      ],
      "content_date": "2026-08-27",
      "freshness": "fresh",
      "id": "arxiv:2608.27321",
      "kind": "paper",
      "label": "adjacent",
      "matched_signals": [
        "lean_formal_proving_agents"
      ],
      "published": "2026-08-27",
      "score": 3.5,
      "source": "arxiv-ai4math-core",
      "summary": "This blueprint serves as a companion to a forthcoming, shorter traditional mathematical paper. The purpose of this blueprint is two-fold: first, it has served as the foundation for a formalization in Lean 4 of these results. This formalization has been completed largely automatically, making essential use of current frontier large language models. Second, it will serve as a resource to readers of the main paper who are interested in further technical details of the proofs. The main result concerns norm-variation estimates for multiple ergodic averages associated with $n\\ge 2$ commuting measure preserving transformations, providing a quantitative strengthening of Tao's norm-convergence theorem and answering an open question of Avigad and Rute. At the core of the analysis lies an explicit real-variable estimate for twisted multilinear averages that is closely related to certain singular Brascamp--Lieb inequalities.",
      "title": "A blueprint for the formalization of norm-variation of multiple ergodic averages for commuting transformations",
      "updated": "2026-08-27",
      "url": "https://arxiv.org/abs/2608.27321"
    },
    {
      "age_days": 7,
      "arxiv_id": "2608.25194",
      "authors": [
        "Ashutosh S. Jogalekar"
      ],
      "content_date": "2026-08-25",
      "freshness": "fresh",
      "id": "arxiv:2608.25194",
      "kind": "paper",
      "label": "adjacent",
      "matched_signals": [
        "lean_formal_proving_agents"
      ],
      "published": "2026-08-25",
      "score": 3.5,
      "source": "arxiv-ai4math-core",
      "summary": "RNA inverse folding asks for an RNA sequence whose prescribed secondary structure is the unique maximum-base-pair compatible fold. In the four-letter Watson-Crick model (A-U and C-G pairs only, no pseudoknots, and zero minimum base-pair span), Hales et al. introduced a separated-coloring certificate and an even-odd device, while Boury et al. generalized this to modulo-$m$ separability, gave an $O(n 2^m)$ decision algorithm, and guaranteed designability when every helix has length at least 3. We prove that the guarantee still holds when a motif-free target has at most two maximal helices of length 2, no maximal helix of length 1, and all remaining helices of length at least 3. The proof builds on Boury et al.'s local helix-coloring transfers and adds a global counting argument showing that the demands created by at most two short helices can always be coordinated. This is a structural success guarantee for the existing modulo-2 algorithm, not a new general decision capability. The resulting coloring yields an explicit sequence whose every distinct compatible noncrossing fold has fewer pairs. No claim is made for nearest-neighbor thermodynamic energy models. The theorem and supporting lemmas are formalized in Lean 4 against pinned Mathlib and reproduced from a frozen public artifact; the kernel-reported axiom set is $\\{\\mathrm{propext},\\mathrm{Classical.choice},\\mathrm{Quot.sound}\\}$. The work was developed with foundational generative-AI assistance under the author's direction and has not yet received independent human expert review.",
      "title": "Designability of RNA Targets with Up to Two Length-2 Helices",
      "updated": "2026-08-25",
      "url": "https://arxiv.org/abs/2608.25194"
    },
    {
      "age_days": 1,
      "arxiv_id": "2608.30221",
      "authors": [
        "Zijun Gao",
        "Weihan Zhang"
      ],
      "content_date": "2026-08-31",
      "freshness": "fresh",
      "id": "arxiv:2608.30221",
      "kind": "paper",
      "label": "adjacent",
      "matched_signals": [
        "general_ai_math_reasoning"
      ],
      "published": "2026-08-31",
      "score": 1.9,
      "source": "arxiv-ai4math-core",
      "summary": "For Gaussian approximation over high-dimensional rectangles under unrestricted covariance, Chernozhukov et al. (2023b) conjectured that the $n^{-1/4}$ rate, up to logarithmic factors, is near-optimal. We show that, under the coordinatewise subexponential condition with scale $B_n$ and the marginal variance lower bound condition with constant $b$ in Chernozhukov et al. (2023b), the approximation error in dimension $d$ is bounded by \\begin{align*} C_b\\min\\left\\{ 1,\\, \\left(\\frac{B_n^2}{n}\\right)^{1/3}\\{\\log(2dn)\\}^{7/3} + \\frac{B_n}{\\sqrt n}\\{\\log(2dn)\\}^{5/2} \\right\\}. \\end{align*} In particular, for bounded $B_n$ and polynomial dimension, the new bound is $n^{-1/3}$ and therefore falsifies the polynomial-dimensional $n^{-1/4}$ near-optimality conjecture. The proof uses a two-stage interpolation and a rank-free matrix-weighted Gaussian surface bound, which may be of independent interest. The initial proof attempt was generated by ChatGPT 5.6 Pro (OpenAI) and subsequently corrected and rewritten by the authors. The machine-checked Lean formalization of the proof can be found at the GitHub repository (https://github.com/WeihanZhang2001/cubic-root-gaussian-approximation-under-unrestricted-covariance).",
      "title": "Cubic-Root Gaussian Approximation under Unrestricted Covariance",
      "updated": "2026-08-31",
      "url": "https://arxiv.org/abs/2608.30221"
    },
    {
      "age_days": 5,
      "arxiv_id": "2608.27718",
      "authors": [
        "Colin Defant",
        "Sidharth Hariharan",
        "Kenny Lau",
        "Ken Ono"
      ],
      "content_date": "2026-08-27",
      "freshness": "fresh",
      "id": "arxiv:2608.27718",
      "kind": "paper",
      "label": "adjacent",
      "matched_signals": [
        "general_ai_math_reasoning"
      ],
      "published": "2026-08-27",
      "score": 1.9,
      "source": "arxiv-ai4math-core",
      "summary": "The rows and columns of the character table of the symmetric group $S_n$ are both naturally indexed by partitions of $n$. Let $D(n)$ denote the number of conjugacy classes of $S_n$ whose column contains no zero entry. The identity column is always zero-free, so $D(n)\\geq 1$. It is known that $D(n)\\ll n^2$. We prove that $D(n)\\ll n^{3/4}$. Second, we prove for almost all positive integers $n$ that $D(n)\\ll_B n^{1/2}(\\log n)^B$ for every $B>5/6$, with a quantitative bound for the exceptional set, using work of Matomäki and Radziwill. Finally, we offer a heuristic supporting our conjecture that $D(n)\\ll_{\\varepsilon} n^{\\varepsilon}$. AxiomProver formalized the results in this paper in Lean assuming preexisting literature.",
      "title": "Zero-free columns in character tables of symmetric groups",
      "updated": "2026-08-27",
      "url": "https://arxiv.org/abs/2608.27718"
    },
    {
      "age_days": 5,
      "arxiv_id": "2608.27708",
      "authors": [
        "Colin Defant",
        "Ken Ono"
      ],
      "content_date": "2026-08-27",
      "freshness": "fresh",
      "id": "arxiv:2608.27708",
      "kind": "paper",
      "label": "adjacent",
      "matched_signals": [
        "general_ai_math_reasoning"
      ],
      "published": "2026-08-27",
      "score": 1.9,
      "source": "arxiv-ai4math-core",
      "summary": "Let $D_n$ be the dihedral group of order $2n$. Consider a continuous-time random walk on $D_n$ driven by arbitrary symmetric rates whose support generates $D_n$. For $p\\in[1,\\infty]$, we say the pair $(D_n,p)$ is rate-monotonic if for each fixed time $t$, the $\\ell^p$-distance between the random walk's distribution at time $t$ and the uniform distribution is monotonically decreasing as a function of the rates. Lyons and White proved that $(D_n,2)$ and $(D_n,\\infty)$ are rate-monotonic. Somewhat counterintuitively, they found several pairs $(D_n,p)$ with ${p\\in[1,1.997]\\cup[2.001,3.999]\\cup[4.001,5.995]}$ that are not rate-monotonic, and they asked whether any such pairs exist with $p=4$ or $p=6$. We resolve their question, proving that $(D_n,2m)$ is rate-monotonic for all positive integers $m$ and $n$. In fact, we prove a generalization of this result to a broader family of groups that includes generalized dihedral groups, dicyclic groups, and generalized quaternion groups. In the other direction, we prove that for every real $p\\geq 1$ that is not an even integer, there exists a positive integer $n$ such that $(D_n,p)$ is not rate-monotonic. The results of this paper were formally verified in Lean by AxiomProver assuming standard literature.",
      "title": "Proof of the Lyons--White Conjecture",
      "updated": "2026-08-27",
      "url": "https://arxiv.org/abs/2608.27708"
    },
    {
      "age_days": 6,
      "arxiv_id": "2608.26321",
      "authors": [
        "Benjamin Dozier"
      ],
      "content_date": "2026-08-26",
      "freshness": "fresh",
      "id": "arxiv:2608.26321",
      "kind": "paper",
      "label": "adjacent",
      "matched_signals": [
        "general_ai_math_reasoning"
      ],
      "published": "2026-08-26",
      "score": 1.9,
      "source": "arxiv-ai4math-core",
      "summary": "We show a birthday paradox for random non-backtracking walk on regular graphs of degree at least $3$: such a walk of length $k$ has high probability of self-intersecting when $k$ is significantly greater than $\\sqrt n$, where $n$ is the number of vertices of the graph. This resolves a conjecture of Noga Alon and Yuval Peres for the fixed degree case.",
      "title": "The Birthday Paradox for non-backtracking walks on regular graphs",
      "updated": "2026-08-26",
      "url": "https://arxiv.org/abs/2608.26321"
    },
    {
      "age_days": 6,
      "arxiv_id": "2608.26310",
      "authors": [
        "Ziyu Wang",
        "Qiming Dai",
        "Yishan Wu",
        "Zaiwen Wen"
      ],
      "content_date": "2026-08-26",
      "freshness": "fresh",
      "id": "arxiv:2608.26310",
      "kind": "paper",
      "label": "adjacent",
      "matched_signals": [
        "general_ai_math_reasoning"
      ],
      "published": "2026-08-26",
      "score": 1.9,
      "source": "arxiv-ai4math-core",
      "summary": "Large language models can now generate complex, multi-step mathematical proofs, but reliably determining their correctness and localizing early logical errors remains a critical challenge. Existing evaluation approaches largely depend on model-based natural-language judgments, which often overlook local reasoning gaps. While formal theorem provers like Lean offer a path to rigorous verification, using them to evaluate informal text requires solving locality and semantic mismatches: a prover might bypass a local flaw by proving an overly broad target, or validate an auto-formalized statement that drifts from the original mathematical intent. To address this, we introduce FaithSieve, a Lean-assisted framework for fine-grained evaluation of natural-language mathematical proofs. FaithSieve decomposes coarse proof steps into local reasoning units, extracts typed proof obligations, and verifies them through a formal evaluation agent. Formal validation is gated by semantic alignment scoring, so Lean evidence is incorporated only when the formal statement faithfully preserves the context, objects, and logical form of the original claim. We construct two expert-verified datasets, ProofLoc-Olympiad and ProofLoc-University, to benchmark first-error localization. On the 350-problem Olympiad dataset, FaithSieve using a GPT-5.4 backbone achieves 81.43% exact first-error accuracy, outperforming the direct-judging baseline of 72.29%. Furthermore, on the 200-problem ProofLoc-University benchmark spanning six advanced domains, FaithSieve reaches 84.5% exact accuracy, compared to 75.0% for the direct judge. Our work demonstrates that decomposing proofs into fine-grained units and grounding them with faithful formal evidence significantly improves reliable evaluation of natural-language reasoning.",
      "title": "FaithSieve: Fine-Grained Evaluation of Math Proofs with Faithful Formal Evidence",
      "updated": "2026-08-26",
      "url": "https://arxiv.org/abs/2608.26310"
    },
    {
      "age_days": 0,
      "authors": [
        "Aaron Liu"
      ],
      "content_date": "2026-09-01",
      "freshness": "fresh",
      "id": "github:leanprover/lean4:552755077915",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-09-01",
      "repo": "leanprover/lean4",
      "score": 0.8,
      "source": "lean4-github",
      "summary": "Recent commit on leanprover/lean4.",
      "title": "leanprover/lean4: fix: swap names of `Dyadic.not_lt` and `Dyadic.not_le` (#14890)",
      "updated": "2026-09-01",
      "url": "https://github.com/leanprover/lean4/commit/552755077915ae65e0740ecd1aee3ac9a0de0757"
    },
    {
      "age_days": 0,
      "authors": [
        "Jeremy Tan Jie Rui"
      ],
      "content_date": "2026-09-01",
      "freshness": "fresh",
      "id": "github:leanprover-community/mathlib4:c3be5ef0d4f0",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-09-01",
      "repo": "leanprover-community/mathlib4",
      "score": 0.8,
      "source": "mathlib4-github",
      "summary": "Recent commit on leanprover-community/mathlib4.",
      "title": "leanprover-community/mathlib4: refactor: `Quaternion` as `abbrev` (#43078)",
      "updated": "2026-09-01",
      "url": "https://github.com/leanprover-community/mathlib4/commit/c3be5ef0d4f00c743c9e035b49f1c2810eb0bd10"
    },
    {
      "age_days": 0,
      "authors": [
        "Rao Xiaojia"
      ],
      "content_date": "2026-09-01",
      "freshness": "fresh",
      "id": "github:leanprover-community/mathlib4:27e07a3212b3",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-09-01",
      "repo": "leanprover-community/mathlib4",
      "score": 0.8,
      "source": "mathlib4-github",
      "summary": "Recent commit on leanprover-community/mathlib4.",
      "title": "leanprover-community/mathlib4: refactor(Tactic/Echelon): extract certificate construction and split the product cert (#43300)",
      "updated": "2026-09-01",
      "url": "https://github.com/leanprover-community/mathlib4/commit/27e07a3212b3b9a3396f6e1cb05d96eccf73207f"
    },
    {
      "age_days": 0,
      "authors": [
        "Thomas Browning"
      ],
      "content_date": "2026-09-01",
      "freshness": "fresh",
      "id": "github:leanprover-community/mathlib4:0e002cab7ddd",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-09-01",
      "repo": "leanprover-community/mathlib4",
      "score": 0.8,
      "source": "mathlib4-github",
      "summary": "Recent commit on leanprover-community/mathlib4.",
      "title": "leanprover-community/mathlib4: refactor(Analysis/Normed/Unbundled/SpectralNorm): extract, generalize, and golf `algNormFromConst` (#43019)",
      "updated": "2026-09-01",
      "url": "https://github.com/leanprover-community/mathlib4/commit/0e002cab7dddc97b86a09826102a4169e172337a"
    },
    {
      "age_days": 0,
      "authors": [
        "Snir Broshi"
      ],
      "content_date": "2026-09-01",
      "freshness": "fresh",
      "id": "github:leanprover-community/mathlib4:742ca0e71693",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-09-01",
      "repo": "leanprover-community/mathlib4",
      "score": 0.8,
      "source": "mathlib4-github",
      "summary": "Recent commit on leanprover-community/mathlib4.",
      "title": "leanprover-community/mathlib4: perf(Order/CompleteLattice/PiLex): exclude `iInf_of_isEmpty` in the `simp` call in `sInf_apply` (#42875)",
      "updated": "2026-09-01",
      "url": "https://github.com/leanprover-community/mathlib4/commit/742ca0e71693a5c31ba28dd35f0ec82cf2f82d42"
    },
    {
      "age_days": 0,
      "authors": [
        "Rémy Degenne"
      ],
      "content_date": "2026-09-01",
      "freshness": "fresh",
      "id": "github:leanprover-community/mathlib4:14011ea84ca5",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-09-01",
      "repo": "leanprover-community/mathlib4",
      "score": 0.8,
      "source": "mathlib4-github",
      "summary": "Recent commit on leanprover-community/mathlib4.",
      "title": "leanprover-community/mathlib4: feat: define `riskIncrease` (statistical information) (#41194)",
      "updated": "2026-09-01",
      "url": "https://github.com/leanprover-community/mathlib4/commit/14011ea84ca535623d58822fd53948ff6be06950"
    },
    {
      "age_days": 0,
      "authors": [
        "Anatole Dedecker"
      ],
      "content_date": "2026-09-01",
      "freshness": "fresh",
      "id": "github:leanprover-community/mathlib4:e8b1229d6fbe",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-09-01",
      "repo": "leanprover-community/mathlib4",
      "score": 0.8,
      "source": "mathlib4-github",
      "summary": "Recent commit on leanprover-community/mathlib4.",
      "title": "leanprover-community/mathlib4: feat: `IsLocallyClosedAt` predicate (#42196)",
      "updated": "2026-09-01",
      "url": "https://github.com/leanprover-community/mathlib4/commit/e8b1229d6fbecc270e13ac04c378d3b3da4d7a59"
    },
    {
      "age_days": 0,
      "authors": [
        "Weiyi Wang"
      ],
      "content_date": "2026-09-01",
      "freshness": "fresh",
      "id": "github:leanprover-community/mathlib4:98ef485d217e",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-09-01",
      "repo": "leanprover-community/mathlib4",
      "score": 0.8,
      "source": "mathlib4-github",
      "summary": "Recent commit on leanprover-community/mathlib4.",
      "title": "leanprover-community/mathlib4: feat(combinatorics): pentagonal number theorem for normed ring (#42185)",
      "updated": "2026-09-01",
      "url": "https://github.com/leanprover-community/mathlib4/commit/98ef485d217e48d24735e2637a46b1b01c41019b"
    },
    {
      "age_days": 0,
      "authors": [
        "emlis"
      ],
      "content_date": "2026-09-01",
      "freshness": "fresh",
      "id": "github:leanprover-community/mathlib4:e1e223a0db9f",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-09-01",
      "repo": "leanprover-community/mathlib4",
      "score": 0.8,
      "source": "mathlib4-github",
      "summary": "Recent commit on leanprover-community/mathlib4.",
      "title": "leanprover-community/mathlib4: feat(SetTheory/Ordinal): prove that `ε₀` and `Γ₀` are countable (#40551)",
      "updated": "2026-09-01",
      "url": "https://github.com/leanprover-community/mathlib4/commit/e1e223a0db9fa01edf5e2346973e160f0be6cd11"
    },
    {
      "age_days": 0,
      "authors": [
        "TJHeeringa"
      ],
      "content_date": "2026-09-01",
      "freshness": "fresh",
      "id": "github:leanprover-community/mathlib4:e076e1ca8f39",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-09-01",
      "repo": "leanprover-community/mathlib4",
      "score": 0.8,
      "source": "mathlib4-github",
      "summary": "Recent commit on leanprover-community/mathlib4.",
      "title": "leanprover-community/mathlib4: feat(Integral/Lebesque/Add): add lintegral_lintegral_mul_le (#43283)",
      "updated": "2026-09-01",
      "url": "https://github.com/leanprover-community/mathlib4/commit/e076e1ca8f3970dfcc12618499a8acedf79bbd89"
    },
    {
      "age_days": 0,
      "authors": [
        "JX-Mo"
      ],
      "content_date": "2026-09-01",
      "freshness": "fresh",
      "id": "github:leanprover-community/mathlib4:1ebc9ab2811e",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-09-01",
      "repo": "leanprover-community/mathlib4",
      "score": 0.8,
      "source": "mathlib4-github",
      "summary": "Recent commit on leanprover-community/mathlib4.",
      "title": "leanprover-community/mathlib4: feat(GroupTheory): add two simp lemmas for `DoubleCoset.mk` (#43278)",
      "updated": "2026-09-01",
      "url": "https://github.com/leanprover-community/mathlib4/commit/1ebc9ab2811ee1bcafb50fd32654af986030a500"
    },
    {
      "age_days": 0,
      "authors": [
        "Joël Riou"
      ],
      "content_date": "2026-09-01",
      "freshness": "fresh",
      "id": "github:leanprover-community/mathlib4:8d48831c7fd4",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-09-01",
      "repo": "leanprover-community/mathlib4",
      "score": 0.8,
      "source": "mathlib4-github",
      "summary": "Recent commit on leanprover-community/mathlib4.",
      "title": "leanprover-community/mathlib4: feat(Geometry): affine maps from the standard simplex (#43260)",
      "updated": "2026-09-01",
      "url": "https://github.com/leanprover-community/mathlib4/commit/8d48831c7fd441adf29ff4ad0eb3b572c86945bb"
    },
    {
      "age_days": 0,
      "authors": [
        "Seewoo Lee"
      ],
      "content_date": "2026-09-01",
      "freshness": "fresh",
      "id": "github:leanprover-community/mathlib4:783b745dbf1e",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-09-01",
      "repo": "leanprover-community/mathlib4",
      "score": 0.8,
      "source": "mathlib4-github",
      "summary": "Recent commit on leanprover-community/mathlib4.",
      "title": "leanprover-community/mathlib4: feat(DihedralGroup): center of $D_n$ for even $n\\ne 2$ (#40410)",
      "updated": "2026-09-01",
      "url": "https://github.com/leanprover-community/mathlib4/commit/783b745dbf1eca238f8d192c624a9d229e080507"
    },
    {
      "age_days": 0,
      "authors": [
        "Tian Chen"
      ],
      "content_date": "2026-09-01",
      "freshness": "fresh",
      "id": "github:leanprover-community/mathlib4:97014c82b03b",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-09-01",
      "repo": "leanprover-community/mathlib4",
      "score": 0.8,
      "source": "mathlib4-github",
      "summary": "Recent commit on leanprover-community/mathlib4.",
      "title": "leanprover-community/mathlib4: feat(Data/Set/Finite): `Set.Finite.sigma` (#41967)",
      "updated": "2026-09-01",
      "url": "https://github.com/leanprover-community/mathlib4/commit/97014c82b03bffce2cf5be227d05811049c89da9"
    },
    {
      "age_days": 0,
      "authors": [
        "Moritz Firsching"
      ],
      "content_date": "2026-09-01",
      "freshness": "fresh",
      "id": "github:leanprover-community/mathlib4:def8bfd07114",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-09-01",
      "repo": "leanprover-community/mathlib4",
      "score": 0.8,
      "source": "mathlib4-github",
      "summary": "Recent commit on leanprover-community/mathlib4.",
      "title": "leanprover-community/mathlib4: feat(Data/Finset/Powerset): disjointness lemmas for `powersetCard_finset` et al (#42522)",
      "updated": "2026-09-01",
      "url": "https://github.com/leanprover-community/mathlib4/commit/def8bfd0711437861a2f9f63fe2b576a0fc074ab"
    },
    {
      "age_days": 0,
      "authors": [
        "Monica Omar"
      ],
      "content_date": "2026-09-01",
      "freshness": "fresh",
      "id": "github:leanprover-community/mathlib4:2494e1f675f3",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-09-01",
      "repo": "leanprover-community/mathlib4",
      "score": 0.8,
      "source": "mathlib4-github",
      "summary": "Recent commit on leanprover-community/mathlib4.",
      "title": "leanprover-community/mathlib4: feat(Analysis/CStarAlgebra/CFC/Order): `e * e ≤ e` when `e` is an element of the nonnegative closed unit ball (#43266)",
      "updated": "2026-09-01",
      "url": "https://github.com/leanprover-community/mathlib4/commit/2494e1f675f3b609d4bb8498bf1d82b970580c69"
    },
    {
      "age_days": 0,
      "authors": [
        "David Kurniadi Angdinata"
      ],
      "content_date": "2026-09-01",
      "freshness": "fresh",
      "id": "github:leanprover-community/mathlib4:eaab0d3ad46c",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-09-01",
      "repo": "leanprover-community/mathlib4",
      "score": 0.8,
      "source": "mathlib4-github",
      "summary": "Recent commit on leanprover-community/mathlib4.",
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      "id": "github:leanprover/lean4:a57be6641c51",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-08-28",
      "repo": "leanprover/lean4",
      "score": 0.8,
      "source": "lean4-github",
      "summary": "Recent commit on leanprover/lean4.",
      "title": "leanprover/lean4: perf: update to LLVM 23 (#14531)",
      "updated": "2026-08-28",
      "url": "https://github.com/leanprover/lean4/commit/a57be6641c51438c02c51fd65c166ca71e137734"
    },
    {
      "age_days": 4,
      "authors": [
        "Henrik Böving"
      ],
      "content_date": "2026-08-28",
      "freshness": "fresh",
      "id": "github:leanprover/lean4:3129edaa4cc6",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-08-28",
      "repo": "leanprover/lean4",
      "score": 0.8,
      "source": "lean4-github",
      "summary": "Recent commit on leanprover/lean4.",
      "title": "leanprover/lean4: fix: working with RAT proofs (#14951)",
      "updated": "2026-08-28",
      "url": "https://github.com/leanprover/lean4/commit/3129edaa4cc655915c89f2202a382ea0d86f8e84"
    },
    {
      "age_days": 4,
      "authors": [
        "Wojciech Różowski"
      ],
      "content_date": "2026-08-28",
      "freshness": "fresh",
      "id": "github:leanprover/lean4:4ad88fe794e0",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-08-28",
      "repo": "leanprover/lean4",
      "score": 0.8,
      "source": "lean4-github",
      "summary": "Recent commit on leanprover/lean4.",
      "title": "leanprover/lean4: fix: do not unfold partially applied constants in `cbv` (#14939)",
      "updated": "2026-08-28",
      "url": "https://github.com/leanprover/lean4/commit/4ad88fe794e04a7b8fa5f98218ed7ae87e1a7a4c"
    },
    {
      "age_days": 4,
      "authors": [
        "Wojciech Różowski"
      ],
      "content_date": "2026-08-28",
      "freshness": "fresh",
      "id": "github:leanprover/lean4:41bdd5d01845",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-08-28",
      "repo": "leanprover/lean4",
      "score": 0.8,
      "source": "lean4-github",
      "summary": "Recent commit on leanprover/lean4.",
      "title": "leanprover/lean4: fix: `deprecated_syntax` warnings for syntax that has `.original` source info (#14940)",
      "updated": "2026-08-28",
      "url": "https://github.com/leanprover/lean4/commit/41bdd5d018452ed9f556f9991d0e6ccacc62c2ba"
    },
    {
      "age_days": 4,
      "authors": [
        "Sebastian Ullrich"
      ],
      "content_date": "2026-08-28",
      "freshness": "fresh",
      "id": "github:leanprover/lean4:b5466a1aa841",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-08-28",
      "repo": "leanprover/lean4",
      "score": 0.8,
      "source": "lean4-github",
      "summary": "Recent commit on leanprover/lean4.",
      "title": "leanprover/lean4: feat: run `lake challenge` dependency resolution inside the sandbox (#14947)",
      "updated": "2026-08-28",
      "url": "https://github.com/leanprover/lean4/commit/b5466a1aa841d9a3f533c9ffde1d0dc6ae9c2ad4"
    },
    {
      "age_days": 4,
      "authors": [
        "Sebastian Ullrich"
      ],
      "content_date": "2026-08-28",
      "freshness": "fresh",
      "id": "github:leanprover/lean4:2a7175c74ba1",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-08-28",
      "repo": "leanprover/lean4",
      "score": 0.8,
      "source": "lean4-github",
      "summary": "Recent commit on leanprover/lean4.",
      "title": "leanprover/lean4: feat: remove deprecated in-kernel native reduction (#14953)",
      "updated": "2026-08-28",
      "url": "https://github.com/leanprover/lean4/commit/2a7175c74ba17b160299accd7e6ea6984d7ea86f"
    },
    {
      "age_days": 4,
      "authors": [
        "Henrik Böving"
      ],
      "content_date": "2026-08-28",
      "freshness": "fresh",
      "id": "github:leanprover/lean4:35cf6e487c28",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-08-28",
      "repo": "leanprover/lean4",
      "score": 0.8,
      "source": "lean4-github",
      "summary": "Recent commit on leanprover/lean4.",
      "title": "leanprover/lean4: feat: min/max support in bv_decide (#14956)",
      "updated": "2026-08-28",
      "url": "https://github.com/leanprover/lean4/commit/35cf6e487c2825ea83f33ddf717aea523c6da0d5"
    },
    {
      "age_days": 4,
      "authors": [
        "Sebastian Ullrich"
      ],
      "content_date": "2026-08-28",
      "freshness": "fresh",
      "id": "github:leanprover/lean4:fe1939c0b3bf",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-08-28",
      "repo": "leanprover/lean4",
      "score": 0.8,
      "source": "lean4-github",
      "summary": "Recent commit on leanprover/lean4.",
      "title": "leanprover/lean4: feat: add `lake challenge` as a `comparator` frontend (#14885)",
      "updated": "2026-08-28",
      "url": "https://github.com/leanprover/lean4/commit/fe1939c0b3bf148eb2c3e64fa02ce2f9311d8f96"
    },
    {
      "age_days": 4,
      "authors": [
        "Peter Limkilde Svendsen"
      ],
      "content_date": "2026-08-28",
      "freshness": "fresh",
      "id": "github:leanprover/lean4:4edc42d4330b",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-08-28",
      "repo": "leanprover/lean4",
      "score": 0.8,
      "source": "lean4-github",
      "summary": "Recent commit on leanprover/lean4.",
      "title": "leanprover/lean4: doc: clarify that BitVec intMin/intMax refer to two's complement interpretation (#13336)",
      "updated": "2026-08-28",
      "url": "https://github.com/leanprover/lean4/commit/4edc42d4330b786c3310515d6ce072253930340a"
    },
    {
      "age_days": 4,
      "authors": [
        "Julia Markus Himmel"
      ],
      "content_date": "2026-08-28",
      "freshness": "fresh",
      "id": "github:leanprover/lean4:424cc7309957",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-08-28",
      "repo": "leanprover/lean4",
      "score": 0.8,
      "source": "lean4-github",
      "summary": "Recent commit on leanprover/lean4.",
      "title": "leanprover/lean4: chore: delete bootstrapping workarounds (#14946)",
      "updated": "2026-08-28",
      "url": "https://github.com/leanprover/lean4/commit/424cc73099573b57d6ca8d6f1ceeb443cf6aef69"
    },
    {
      "age_days": 5,
      "authors": [
        "Henrik Böving"
      ],
      "content_date": "2026-08-27",
      "freshness": "fresh",
      "id": "github:leanprover/lean4:f3c6b8462d6c",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-08-27",
      "repo": "leanprover/lean4",
      "score": 0.8,
      "source": "lean4-github",
      "summary": "Recent commit on leanprover/lean4.",
      "title": "leanprover/lean4: refactor: new LRAT checker (#14842)",
      "updated": "2026-08-27",
      "url": "https://github.com/leanprover/lean4/commit/f3c6b8462d6cbfcd2fb09599bf5820c59ca6773c"
    },
    {
      "age_days": 5,
      "authors": [
        "Sebastian Ullrich"
      ],
      "content_date": "2026-08-27",
      "freshness": "fresh",
      "id": "github:leanprover/lean4:e991a05e359a",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-08-27",
      "repo": "leanprover/lean4",
      "score": 0.8,
      "source": "lean4-github",
      "summary": "Recent commit on leanprover/lean4.",
      "title": "leanprover/lean4: perf: initialize only the core modules `leanchecker-paranoid` needs (#14936)",
      "updated": "2026-08-27",
      "url": "https://github.com/leanprover/lean4/commit/e991a05e359a25988f49bff3ab8af986e959b866"
    },
    {
      "age_days": 5,
      "authors": [
        "Salkutsan Aleksey"
      ],
      "content_date": "2026-08-27",
      "freshness": "fresh",
      "id": "github:leanprover/lean4:459d43013417",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-08-27",
      "repo": "leanprover/lean4",
      "score": 0.8,
      "source": "lean4-github",
      "summary": "Recent commit on leanprover/lean4.",
      "title": "leanprover/lean4: fix: avoid exposing Fin.foldl implementation (#14554)",
      "updated": "2026-08-27",
      "url": "https://github.com/leanprover/lean4/commit/459d4301341708de7c16350aeea647b112c62321"
    },
    {
      "age_days": 5,
      "authors": [
        "Julia Markus Himmel"
      ],
      "content_date": "2026-08-27",
      "freshness": "fresh",
      "id": "github:leanprover/lean4:b66d310c2420",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-08-27",
      "repo": "leanprover/lean4",
      "score": 0.8,
      "source": "lean4-github",
      "summary": "Recent commit on leanprover/lean4.",
      "title": "leanprover/lean4: feat: sane `rwa` (#14937)",
      "updated": "2026-08-27",
      "url": "https://github.com/leanprover/lean4/commit/b66d310c242069d99fccc0d5dd30ef72aec090c7"
    },
    {
      "age_days": 5,
      "authors": [
        "Wojciech Różowski"
      ],
      "content_date": "2026-08-27",
      "freshness": "fresh",
      "id": "github:leanprover/lean4:61bb5655d092",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-08-27",
      "repo": "leanprover/lean4",
      "score": 0.8,
      "source": "lean4-github",
      "summary": "Recent commit on leanprover/lean4.",
      "title": "leanprover/lean4: feat: lake: read persisted code quality entries in `lake lint --code-quality` (#14933)",
      "updated": "2026-08-27",
      "url": "https://github.com/leanprover/lean4/commit/61bb5655d092c910d5f1b9f671ceeab87db6a964"
    },
    {
      "age_days": 1,
      "arxiv_id": "2608.30604",
      "authors": [
        "Samuil Petkov"
      ],
      "content_date": "2026-08-31",
      "freshness": "fresh",
      "id": "arxiv:2608.30604",
      "kind": "paper",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-08-31",
      "score": 0.5,
      "source": "arxiv-ai4math-core",
      "summary": "Let $ζ(G)$ denote the minimum number of parts in a partition of $V(G)$ in which every part induces either a clique or an independent set. Erdős and Gimbel asked whether, for $G_n\\sim G(n,1/2)$, the difference $χ(G_n)-ζ(G_n)$ tends to infinity with high probability. We resolve this problem along the full sequence $n\\to\\infty$ and prove that $\\mathbb P(χ(G_n)-ζ(G_n)\\ge ((\\log 2)^2/4)\\log(200/153)\\,n/(\\log n)^3)\\to1$. This gives a lower bound at the conjectured scale $n/(\\log n)^3$. We also obtain a phase-resolved refinement: if $δ_n$ is the fractional part of the standard independence-number center, then the coefficient may be replaced by $(\\log 2)^2A_4(δ_n)/4-o(1)$, where $A_4$ is explicit, continuous, nonconstant, and satisfies $A_4(δ)>\\log(200/153)$ for every $δ\\in[0,1]$. The proof uses signed cocoloring profiles supported on four consecutive class sizes and remains uniform across jumps of the natural class-size cutoff. An exact signed-overlap identity separates local cell rewards from a binary cycle-space factor. A canonical decomposition into high cells and a capped residual matching, together with an endpoint-table comparison and an injective restriction of residual even edge sets, yields the required second-moment bound. A bounded-differences argument then amplifies the resulting rare signed witness to a high-probability cocoloring.",
      "title": "A Full-Sequence Quantitative Gap Between the Chromatic and Cochromatic Numbers of a Random Graph",
      "updated": "2026-08-31",
      "url": "https://arxiv.org/abs/2608.30604"
    },
    {
      "age_days": 2,
      "arxiv_id": "2608.29734",
      "authors": [
        "Jef Pauwels"
      ],
      "content_date": "2026-08-30",
      "freshness": "fresh",
      "id": "arxiv:2608.29734",
      "kind": "paper",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-08-30",
      "score": 0.5,
      "source": "arxiv-ai4math-core",
      "summary": "In 2010, Pál and Vértesi found a family of finite-dimensional strategies for the $I_{3322}$ Bell inequality whose optimized values appeared to converge as the local Hilbert-space dimension grew. They conjectured that this limit is the supremum over all finite-dimensional quantum strategies, but that no finite-dimensional strategy attains it. We prove both claims. The proof uses the symmetry of the Bell functional to associate every strategy with a finite matrix of probabilities, one for each pair of spectral subspaces of Alice and Bob. This matrix gives an upper bound on the Bell value, and finite-dimensional strategies built from the repeating structure found by Pál and Vértesi approach it as the dimension grows. If the bound were attained exactly in finite dimension, the optimality conditions would then require a state that cannot be normalized. Consequently, the set of finite-dimensional quantum correlations is not closed in the $(3,3,2,2)$ scenario, the smallest Bell scenario where this can happen. Moreover, approaching the supremum requires unbounded local dimension. The core of the proof was formalized in Lean~4.",
      "title": "The quantum supremum of the $I_{3322}$ Bell inequality is not attained in finite dimension",
      "updated": "2026-08-30",
      "url": "https://arxiv.org/abs/2608.29734"
    },
    {
      "age_days": 2,
      "arxiv_id": "2608.29496",
      "authors": [
        "Nadejda Drenska",
        "Matthew Lemoine",
        "Gowri Priya Sunkara",
        "Yu Wang",
        "Sri Lakshmi Sravani Devarakonda",
        "Steven B. Heymsfield"
      ],
      "content_date": "2026-08-30",
      "freshness": "fresh",
      "id": "arxiv:2608.29496",
      "kind": "paper",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-08-30",
      "score": 0.5,
      "source": "arxiv-ai4math-core",
      "summary": "Accurate estimation of body-composition outcomes, including body fat percentage (BFP), bone mineral density (BMD), and appendicular lean mass (ALM), is important for evaluating metabolic, skeletal, and muscular health. Direct assessment using dual-energy X-ray absorptiometry (DXA), however, requires specialized equipment and involves ionizing radiation. We propose a target-aware, state-adaptive $p$-Dirichlet energy-flow graph neural regression ($p$SADE-GNR) framework for estimating these outcomes from non-invasive anthropometric measurements. A neural encoder maps participant representations to hidden states that are propagated over an outcome-specific participant-similarity graph by a state-adaptive forward-Euler discretization of the graph $p$-Dirichlet energy flow. Graph distances weight each original or latent coordinate by its normalized absolute training-fold correlation with the outcome. Using clinical data from the Pennington Biomedical Research Center and five-fold cross-validation, the correlation-weighted model using the original standardized measurements achieved the lowest root mean squared error in all nine primary outcome-cohort combinations and outperformed previously reported support vector regression or least-squares support vector regression reference values in eight of nine comparisons. Autoencoder, variational-autoencoder, and Gaussian-mixture variational-autoencoder representations generally did not improve primary-outcome prediction or reduce computational cost. In an exploratory age-prediction analysis including ALM, BMD, and BFP as predictors, the correlation-weighted GMVAE model achieved the lowest mean error in all three cohorts. These results support target-aware, state-adaptive $p$-Dirichlet graph neural regression for non-invasive body-composition estimation.",
      "title": "Target-Aware State-Adaptive $p$-Dirichlet Graph Neural Regression for Non-Invasive Body-Composition Estimation",
      "updated": "2026-08-30",
      "url": "https://arxiv.org/abs/2608.29496"
    },
    {
      "age_days": 3,
      "arxiv_id": "2608.29391",
      "authors": [
        "George Xi Wang",
        "Henghao Li",
        "Shan Lin",
        "Yunge Wen",
        "Jiaqian Hu",
        "Yuhua Jin"
      ],
      "content_date": "2026-08-29",
      "freshness": "fresh",
      "id": "arxiv:2608.29391",
      "kind": "paper",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-08-29",
      "score": 0.5,
      "source": "arxiv-ai4math-core",
      "summary": "Floating things invite touch. We present Feelium, a blimp-based telepresence platform that enables visual embodiment and touch interaction through its inflatable skin. Through a VR headset, a remote person inhabits the blimp, looking out of it first-person, appearing on its skin as a face or avatar, and steering it through the room. Partners in the room pat it, press a palm against it, draw on it, or lean into it; the skin senses each contact, renders it into the wearer's view in VR spaces. Touch thus provides a physical interaction channel for remote presence, turning the skin into a shared surface between remote and co-located partners.",
      "title": "Feelium: A Touchable Blimp Body for Aerial Telepresence",
      "updated": "2026-08-29",
      "url": "https://arxiv.org/abs/2608.29391"
    },
    {
      "age_days": 4,
      "arxiv_id": "2608.28031",
      "authors": [
        "Nima Anari"
      ],
      "content_date": "2026-08-28",
      "freshness": "fresh",
      "id": "arxiv:2608.28031",
      "kind": "paper",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-08-28",
      "score": 0.5,
      "source": "arxiv-ai4math-core",
      "summary": "The canonical Bethe approximation gives a deterministic approximation to the permanent of every nonnegative matrix within a factor of $(\\sqrt{2})^n$. We improve the base of this exponential factor: for some absolute constant $c<\\sqrt{2}$, there is a deterministic polynomial-time $c^n$-approximation for the permanent of every nonnegative matrix. This shows that the canonical Bethe guarantee is not a barrier for deterministic approximation of the permanent. The proof augments the Bethe lower bound with a new certificate tailored to matrices on which that lower bound loses nearly the full factor. The author supplied the high-level plan of attack, and the proof was developed in an interaction with ChatGPT 5.6 Sol Pro. The author subsequently verified the results. Codex assisted with proof checking, manuscript assembly, and typesetting.",
      "title": "Beyond the Bethe Approximation of the Permanent",
      "updated": "2026-08-28",
      "url": "https://arxiv.org/abs/2608.28031"
    },
    {
      "age_days": 6,
      "arxiv_id": "2608.26418",
      "authors": [
        "Architect Labs"
      ],
      "content_date": "2026-08-26",
      "freshness": "fresh",
      "id": "arxiv:2608.26418",
      "kind": "paper",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-08-26",
      "score": 0.5,
      "source": "arxiv-ai4math-core",
      "summary": "Modern AI workloads and the hardware that runs them evolve on different timescales: architectural definition precedes volume silicon by years, while target workloads shift in months. Design decisions are therefore committed under deep uncertainty and paid for twice, once in the generality added as a hedge, and again when new workloads map poorly onto frozen silicon. As Moore's Law stagnates, specialization is the main remaining source of performance-per-watt and demands a design cycle that runs at the cadence of the workloads. We present an end-to-end AI system that collapses the software-to-silicon stack into a single optimization loop, where hardware and software are co-designed and verified under one objective. Its first demonstration is Redwood, a frontier AI accelerator built for single-batch, low-power, ultra-low-latency inference for physical AI. From a high-level specification by two human architects, the system autonomously generated the performance model, RTL design, UVM environments, formal proofs, firmware, and kernels in under two weeks with no human intervention below the specification. Every block reached 95% coverage via commercial EDA tools, our proprietary formal engine, and hardware-in-the-loop validation. Specification changes were reverified and redeployed to hardware in under 48 hours. Redwood Nano, its ultra-low-power FPGA variant, runs multi-billion-parameter models like Llama and Qwen. Projected onto Samsung 8 nm, the Jetson Orin Nano's process class, Redwood delivers 1.75x the throughput at 1.9x lower power, a 3.4x performance-per-watt gain against a measured Jetson baseline on the same models. Qwen running on Redwood also helped design next-generation Redwood, an early step toward recursive self-improvement. To our knowledge, this is the first production-worthy AI accelerator designed end-to-end by an AI system and running a modern AI model.",
      "title": "Redwood: A Frontier AI Accelerator Designed, Verified, and Deployed from Scratch in 2 Weeks by AI",
      "updated": "2026-08-28",
      "url": "https://arxiv.org/abs/2608.26418"
    },
    {
      "age_days": 6,
      "arxiv_id": "2608.26435",
      "authors": [
        "Chao Xu",
        "Yiqing Wang",
        "Riccardo Scarcelli"
      ],
      "content_date": "2026-08-26",
      "freshness": "fresh",
      "id": "arxiv:2608.26435",
      "kind": "paper",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-08-26",
      "score": 0.5,
      "source": "arxiv-ai4math-core",
      "summary": "In this study, direct numerical simulations (DNS) are employed to investigate NOx formation in turbulent lean premixed hydrogen-air flames under engine-relevant conditions. Various turbulence intensities and molecular transport models are examined to isolate the individual impacts of turbulence intensity, Lewis number, and preferential diffusion on NOx production. Results show that NOx production is significantly enhanced in all turbulent cases relative to the laminar flame, reaching approximately five times the laminar value at a mixture residence time of 0.15 ms. Increasing turbulence intensity is found to have three competing effects on NOx formation: (1) it strengthens turbulence-instability interactions by inducing local super-adiabatic hot spots and elevating key flame radical concentrations within the flame brush, thereby promoting NOx formation locally; (2) it accelerates the turbulent flame speed, reducing the flame-brush residence time and thus suppressing NOx production globally; and (3) it reduces post-flame temperature fluctuations, suppressing thermal NOx enhancement in the post-flame zone. Lewis number effects are identified as the primary mechanism driving thermodiffusive NOx enhancement, with preferential diffusion playing a secondary role, as evidenced by the nearly identical NOx reaction rates between unity Lewis number turbulent flames and their laminar counterparts. Finally, an excellent correlation between the peak conditional mean NOx reaction rate and the stretch factor is identified, and a conceptual model is proposed to predict NOx enhancement in practical engine simulations. The findings highlight that turbulence--chemistry interaction is critical for accurately predicting NOx formation in thermodiffusively unstable hydrogen flames.",
      "title": "Direct numerical simulation of NOx formation in turbulent lean premixed hydrogen-air flames under engine-relevant conditions",
      "updated": "2026-08-26",
      "url": "https://arxiv.org/abs/2608.26435"
    },
    {
      "age_days": 6,
      "arxiv_id": "2608.26365",
      "authors": [
        "Cynthia Bortolotto",
        "João P. G. Ramos"
      ],
      "content_date": "2026-08-26",
      "freshness": "fresh",
      "id": "arxiv:2608.26365",
      "kind": "paper",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-08-26",
      "score": 0.5,
      "source": "arxiv-ai4math-core",
      "summary": "We give a short complex-analytic proof of a square-restricted form of local stable phase retrieval at the Gaussian in one-dimensional Fock space. The main estimate is a coercivity inequality for the map $F\\mapsto F^2$: \\[ \\|F^2-F(0)^2|_{\\mathcal{F}^2(\\mathbb{C})} \\lesssim \\inf_{c\\in\\mathbb{R}}\\||F|^2-c\\|_{L^2(d γ)}. \\] The proof uses a weighted derivative norm, two integrations by parts, and a weighted Cauchy inequality. The proof has been completely verified in Lean with the aid of Large Language Models.",
      "title": "A complex-analytic proof of square-restricted stable phase retrieval in Fock space",
      "updated": "2026-08-26",
      "url": "https://arxiv.org/abs/2608.26365"
    },
    {
      "age_days": 7,
      "arxiv_id": "2608.25220",
      "authors": [
        "Henry Robbins",
        "Connor Lawless",
        "Madeleine Udell",
        "Ellen Vitercik"
      ],
      "content_date": "2026-08-25",
      "freshness": "fresh",
      "id": "arxiv:2608.25220",
      "kind": "paper",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-08-25",
      "score": 0.5,
      "source": "arxiv-ai4math-core",
      "summary": "Mixed-Integer Linear Programming (MILP) is a fundamental tool for combinatorial optimization with extensive real-world applications. A central challenge is designing computationally efficient MILP formulations. Large Language Models (LLMs) offer new opportunities to automate the modeling process, from deriving formulations to strengthening them. Reliable automation requires robust methods for verifying that proposed formulations preserve the underlying optimization problem. However, existing approaches evaluate formulations numerically and fail to reason about general problem instances. We resolve this limitation by introducing a constructive definition of MILP reformulation that can be formalized in Lean and machine-checked. We develop FLARE (Formulation-Level Automated Reformulation Evaluation), a method that uses an LLM-based agent and the Lean proof assistant to verify proposed reformulations against a reference formulation. To evaluate our approach, we introduce FormulationBench, a challenging dataset of 20 problems and 109 formulations. FLARE outperforms existing methods, with 100% accuracy on the NP-hard subset of FormulationBench. Furthermore, FLARE produces a machine-checkable certificate for every reformulation it accepts. For cases where formal guarantees are not necessary, we introduce FLARE-NL, a fast and cheap LLM proxy that matches FLARE's accuracy but produces no certificate. These methods enable reliable verification in automated optimization modeling.",
      "title": "FLARE: Verifying MILP Reformulations with LLM-Based Theorem Proving",
      "updated": "2026-08-25",
      "url": "https://arxiv.org/abs/2608.25220"
    },
    {
      "age_days": 4,
      "arxiv_id": "2608.28541",
      "authors": [
        "Javier Aguilar Martín"
      ],
      "content_date": "2026-08-28",
      "freshness": "fresh",
      "id": "arxiv:2608.28541",
      "kind": "paper",
      "label": "negative",
      "matched_signals": [
        "negative:vision_world_models",
        "tool_use_agents"
      ],
      "published": "2026-08-28",
      "score": -1.1,
      "source": "arxiv-ai4math-core",
      "summary": "A code world model accepted by a sampling gate can be exactly right on everything the gate can see and arbitrarily wrong beyond it. We characterize what a certified model can know, and what its errors can cost, when the omission is an annular freeze mode enclosing an unreachable interior. The gate quotient makes the question precise: acceptance-with-certainty determines the model exactly on the reachable query set; beyond reach is gauge. On a minimal ring instrument we prove the extreme case (a wrong-topology filled-disc artifact unfalsifiable by any sampling gate and bitwise harmless at play) and measure, with LLM synthesis across three model families, how one knob (a channel of width gamma) walks the same artifact through three regimes: unfalsifiable-and-harmless, falsifiable-and-costly, and instantly falsified. Three principles organize the empirics. First, danger is topology relative to reach: a channel the planner can use collapses the blind model's exploitation (play cost 1.09 to ~0 over a knee at gamma ~ 0.1), while a hidden channel with the same first Betti number keeps it at full strength (1.12). Second, repair is parameter-bound and sensor-bound: no family recovers the region from outside evidence; from inside, models pose the right topology but cannot pin its parameters, and the posed topology tracks the guiding persistent-homology summary's wrong beta_1 (a sensor with a measured geometric resolution limit), not the truth. Third, mitigation must match the error's dimension and direction: point fences fail against the one-dimensional boundary, a dimension-matched persisted fence collapses exploitation to a two-lesson transient (0.999 to 0.058), and the dual freedom certificate collapses the invented-mode failure symmetrically (1.769 to 0.029). In n dimensions the shell makes misidentification near-certain while the danger stays fully exploitable: the two axes are independent.",
      "title": "An Enclosed Mode Is a Gauge Choice: Topology Relative to Reach in Certified Code World Models",
      "updated": "2026-08-28",
      "url": "https://arxiv.org/abs/2608.28541"
    }
  ],
  "lookback_days": 21,
  "schema": "ai4math-radar-run-v1",
  "timezone": "America/Los_Angeles"
}
