{
  "counts": {
    "adjacent": 6,
    "core": 6,
    "errors": 0,
    "negative": 78,
    "total": 90
  },
  "date": "2026-10-07",
  "errors": [],
  "fresh_content_days": 21,
  "generated_at": "2026-10-07T20:44:28Z",
  "items": [
    {
      "age_days": 2,
      "arxiv_id": "2610.05701",
      "authors": [
        "Yuxuan Jiang",
        "Aditya Vempaty",
        "Ashish Jagmohan"
      ],
      "content_date": "2026-10-05",
      "freshness": "fresh",
      "id": "arxiv:2610.05701",
      "kind": "paper",
      "label": "core",
      "matched_signals": [
        "lean_formal_proving_agents",
        "verifier_guided_reasoning"
      ],
      "published": "2026-10-05",
      "score": 9.5,
      "source": "arxiv-ai4math-core",
      "summary": "Recursive self-improvement (RSI) enables agents to iteratively optimize their workflows via execution feedback. However, standard RSI typically operates as a first-order optimizer: it repeatedly patches surface-level parameters in response to immediate failure symptoms, often leading to trial-and-error thrashing without resolving underlying mechanisms. To address this limitation, we introduce SO-RSI, a framework that elevates workflow optimization to a second-order diagnostic inquiry, investigating why failures occur before committing to structural interventions. SO-RSI passively monitors execution traces for three structural anomalies (recurrence, opposing edits, and expectation mismatch) to trigger targeted mechanism investigations. By executing lightweight diagnostic probes and maintaining persistent inquiry memory across RSI rounds, SO-RSI accumulates causal evidence to guide systematic workflow edits rather than parameter patches. Across Lean 4 proof generation and Verus-based verifiable code generation, SO-RSI improves final held-out pass rates over Naive RSI by 21.8 and 25.8 percentage points under matched 24-hour search budgets. Behavioral analyses further confirm that SO-RSI substantially suppresses failure recurrence and eliminates unproductive zero-progress optimization loops.",
      "title": "Second-Order Problem Solving for Recursive Self-Improvement in Formal Verification",
      "updated": "2026-10-05",
      "url": "https://arxiv.org/abs/2610.05701"
    },
    {
      "age_days": 1,
      "arxiv_id": "2610.08246",
      "authors": [
        "André G. Pereira",
        "Augusto B. Corrêa",
        "Felipe Meneguzzi",
        "Jendrik Seipp"
      ],
      "content_date": "2026-10-06",
      "freshness": "fresh",
      "id": "arxiv:2610.08246",
      "kind": "paper",
      "label": "core",
      "matched_signals": [
        "lean_formal_proving_agents",
        "tool_use_agents",
        "verifier_guided_reasoning"
      ],
      "published": "2026-10-06",
      "score": 7.9,
      "source": "arxiv-ai4math-core",
      "summary": "Frontier large language models (LLMs) can generate heuristic functions that guide search to achieve state-of-the-art performance in satisficing planning, where any plan is acceptable. However, these heuristics are not guaranteed to be admissible and can lead to suboptimal plans. We introduce LeanPlan, the first planning system that finds optimal plans with LLM-generated heuristics whose admissibility is machine-checked. Given a domain description and training tasks, an agentic loop uses planner feedback to iteratively improve a reusable domain-specific heuristic, its admissibility proof and the required domain assumptions. LeanPlan implements the heuristic, its proof and an efficient planner with machine-checked grounding and search in Lean 4. We evaluate LeanPlan on ten domains from the International Planning Competition and three new domains, using test tasks with up to 57 times as many objects as the training tasks. With GPT-5.6 Sol in the agentic loop, we successfully generate heuristics and admissibility proofs for all these domains. With the resulting heuristics, LeanPlan usually expands fewer states than the state-of-the-art Scorpion planner and solves more tasks overall.",
      "title": "LeanPlan: Optimal Planning with LLM-Generated Heuristics and Admissibility Proofs",
      "updated": "2026-10-06",
      "url": "https://arxiv.org/abs/2610.08246"
    },
    {
      "age_days": 1,
      "arxiv_id": "2610.08329",
      "authors": [
        "Zhiyuan Zhang",
        "Axel Delaval",
        "Leheng Chen",
        "Jinxuan Chen",
        "Jie Xu",
        "Yuxuan Liao",
        "Jiedong Jiang",
        "Chunlei Liu",
        "Bin Dong"
      ],
      "content_date": "2026-10-06",
      "freshness": "fresh",
      "id": "arxiv:2610.08329",
      "kind": "paper",
      "label": "core",
      "matched_signals": [
        "general_ai_math_reasoning",
        "lean_formal_proving_agents",
        "seed_author:Bin Dong",
        "seed_author:Jiedong Jiang"
      ],
      "published": "2026-10-06",
      "score": 7.3,
      "source": "arxiv-ai4math-core",
      "summary": "We present an AI-assisted Lean 4 formalization of the Poincaré conjecture. The project began with limited reusable formal infrastructure for the geometric analysis behind the proof. To organize this work, we combined a proof blueprint prepared by mathematicians with explicit milestone statements. These milestones enabled parallel agent work and gave mathematicians clear points to locate blockers and provide effective mathematical guidance. Our analysis identifies the human interventions and organizational choices behind this workflow. The project provides a starting point toward reusable infrastructure for future formalization projects; such infrastructure, once developed, could eventually reduce the cost of verifying mathematical results in geometric analysis.",
      "title": "An AI-Assisted Formalization of the Poincaré Conjecture",
      "updated": "2026-10-06",
      "url": "https://arxiv.org/abs/2610.08329"
    },
    {
      "age_days": 1,
      "arxiv_id": "2610.07943",
      "authors": [
        "Wei Li",
        "Kevin Vallier",
        "Tong Zhang"
      ],
      "content_date": "2026-10-06",
      "freshness": "fresh",
      "id": "arxiv:2610.07943",
      "kind": "paper",
      "label": "core",
      "matched_signals": [
        "lean_formal_proving_agents"
      ],
      "published": "2026-10-06",
      "score": 6.5,
      "source": "arxiv-ai4math-core",
      "summary": "For a finite forest $F$ let $i_k(F)$ be the number of independent sets of $F$ with $k$ vertices. Zhang and Li proved that the sequence $i_0(F),i_1(F),\\dots,i_{α(F)}(F)$ is unimodal for every finite forest $F$, which answers Erdős Problem 993. We give a second proof. It starts from their decomposition relative to a fixed independent set and from the bounds of Zhang and Li and of Fang, Lu, Nevo, Yao and Zheng that confine a valley of the sequence to an explicit window of ranks. For a forest with at least $25$ vertices, one moment argument excludes a valley at every rank of the window: at the activity where the hard-core mean equals the rank, the size of a random independent set is a mixture of binomial laws over an independent set of maximum weight, a valley is a moment inequality for this mixture, and it is excluded by duality given three bounds that hold for every forest, on the variance of the number of free vertices and on its Laplace transforms, and on the variance ratio. The variance bound is proved by hand up to finitely many interval checks and the other two bounds are verified by computer on finite interval-arithmetic coverings; on the resulting parameter domain a valley is excluded by exact tests on finitely many rational boxes while the mean number of free vertices is below an explicit starting mean between $19$ and $50$, and above it by one inequality, with explicit constants, for the fibers of a weighted valley kernel, proved by hand up to a finite list of explicit checks and averaged over the mixture. Forests with at most $24$ vertices are treated by exact counting, by hand except for exact rational evaluations of two explicit formulas at $43$ parameter triples. No forest is enumerated. A formal proof of the theorem in Lean 4 accompanies the paper.",
      "title": "Unimodality of Forest Independence Polynomials",
      "updated": "2026-10-06",
      "url": "https://arxiv.org/abs/2610.07943"
    },
    {
      "age_days": 5,
      "arxiv_id": "2610.03994",
      "authors": [
        "Traian Serbanuta",
        "Jun Xu",
        "Andrei Stefanescu",
        "Cosmin Radoi"
      ],
      "content_date": "2026-10-02",
      "freshness": "fresh",
      "id": "arxiv:2610.03994",
      "kind": "paper",
      "label": "core",
      "matched_signals": [
        "lean_formal_proving_agents",
        "verifier_guided_reasoning"
      ],
      "published": "2026-10-02",
      "score": 6.5,
      "source": "arxiv-ai4math-core",
      "summary": "VeriContest is a benchmark of 1007 competitive-programming problems in Rust, each with a Verus specification, a judge-accepted solution, and a Verus proof. Its authors report that proof generation is the bottleneck for frontier models: given the specification and the code, the best model produces an accepted Verus proof for 13.95% of the problems on the first attempt. We report on solving the same proof-generation task with Rust-Prover, a verifier for Rust backed by Lean 4. The Verus specification and the Rust code are restated and translated into Lean, each specification becomes a theorem, and agents prove the theorems with Lean's kernel as the final check. All 1325 theorems of all 1007 problems were proved. 1259 of them were proved in one run of under 32 hours on Claude Opus 5.5, at a median of 3.2 minutes and $1.17 per proof, and 70% of them on the first iteration. The restated specifications were checked against the benchmark's test suites, and reviewed where no suite applies. None was wrong or weakened. The translated Lean programs were run on 21,413 of the benchmark's test cases and produced the same output as the Rust programs on every one. Across four Claude and four GPT models at five reasoning-effort settings, every current frontier model proves nearly all of a ten-theorem sample at every setting, and more effort raises the cost without raising the number of proofs. The cheapest Claude setting, Sonnet 5.5 at low effort, proves all of the 50 hardest theorems. We also rerun the benchmark's own Verus protocol with Claude Opus 5.5 on the 50 problems with the longest reference proofs. Opus 5.5 alone fails to prove one of them.",
      "title": "Solving VeriContest with a Lean-Backed Rust Verifier",
      "updated": "2026-10-02",
      "url": "https://arxiv.org/abs/2610.03994"
    },
    {
      "age_days": 3,
      "arxiv_id": "2610.05367",
      "authors": [
        "Prithwish Jana",
        "Viet Bach Hoang",
        "Logan Luna",
        "Viresh Pati",
        "Akash Singirikonda",
        "Cy Xie",
        "Lisa Carbone",
        "Wuyang Chen",
        "Walter Moreira",
        "Joe Stubbs",
        "Sriram Vishwanath",
        "Vijay Ganesh"
      ],
      "content_date": "2026-10-04",
      "freshness": "fresh",
      "id": "arxiv:2610.05367",
      "kind": "paper",
      "label": "core",
      "matched_signals": [
        "reasoning_rl_distillation",
        "tool_use_agents",
        "verifier_guided_reasoning"
      ],
      "published": "2026-10-04",
      "score": 6.3,
      "source": "arxiv-ai4math-core",
      "summary": "Proof auto-formalization translates natural-language (NL) theorems and proofs into a formal language (FL) such as Lean, enabling mechanical verification. Despite rapid progress, research-level proofs often depend on concepts missing from leading proof assistant libraries (e.g., Lean's Mathlib), and successful compilation does not guarantee that a translation preserves the theorem's meaning or the proof's reasoning. Furthermore, aligned NL-FL training data are scarce, and leading agents often rely on costly frontier models and manually engineered harnesses. To address the above issues, we present AIProver, an agentic framework for autonomous proof auto-formalization and proof synthesis (AFPS) that jointly post-trains a 119B open-weight language model and evolves its agentic, tool-calling harness with HarnessEvolve. Verifiers assess type correctness, proof completeness, and semantic correctness, returning rewards and diagnostic certificates that drive model fine-tuning and alternating reinforcement learning via symbolic feedback and HarnessEvolve, a certificate-driven evolutionary search over the whole harness control flow that re-tailors the harness to the updated model. For research-level training and evaluation, we introduce LoCoBench, 58.9k instances from Mathlib, CSLib, Mizar Math Library, and a bounded-arithmetic textbook, with a 771-instance validation split whose theorem-proof pairs have no public Lean formalization. Against 39 frameworks spanning AFPS agents, frontier LLMs, and coding agents, AIProver lifts pass@4 semantic correctness over its Leanstral-1.5 base from 15.7% to 36.7% and outperforms every other open-weight system and Aristotle. As a Claude Code and Codex skill, it lifts their semantic correctness from 41.9% and 34.1% to 79.8% and 62.4%, respectively. Further, it is also 24% cheaper than Numina-Lean-Agent, pushing the accuracy-cost frontier of research-level AFPS.",
      "title": "AIProver: Agentic Auto-Formalization of Mathematical Research via Certificate-Driven Evolving Harness",
      "updated": "2026-10-04",
      "url": "https://arxiv.org/abs/2610.05367"
    },
    {
      "age_days": 2,
      "arxiv_id": "2610.06531",
      "authors": [
        "Lilin Yan",
        "Hongwei Zhao"
      ],
      "content_date": "2026-10-05",
      "freshness": "fresh",
      "id": "arxiv:2610.06531",
      "kind": "paper",
      "label": "adjacent",
      "matched_signals": [
        "general_ai_math_reasoning",
        "lean_formal_proving_agents"
      ],
      "published": "2026-10-05",
      "score": 4.9,
      "source": "arxiv-ai4math-core",
      "summary": "Let all pairwise distances of an arbitrary configuration of points in $\\mathbb{R}^{\\ell}$ be known exactly. We prove that every second-order stationary point of the complete-graph squared-stress objective over configurations in $\\mathbb{R}^{k}$ has zero residual whenever $k > \\ell$. The result holds for every number of points, without a genericity assumption, and allows repeated points and degenerate ground-truth configurations. It resolves the one-extra-dimension conjecture for complete, uniformly weighted data. The proof combines positivity of the residual stress, polar normalization of the candidate configuration, a row-wise rank-nullity argument, and propagation of zero curvature through the full Hessian. The theorem, including the passage from derivatives of the original quartic objective to its matrix formulation, has been formalized in Lean 4. The accompanying verification records include a kernel check with zero trust level and a transitive axiom audit.",
      "title": "One Extra Dimension Suffices for the Complete-Graph Squared-Stress",
      "updated": "2026-10-05",
      "url": "https://arxiv.org/abs/2610.06531"
    },
    {
      "age_days": 3,
      "arxiv_id": "2610.05412",
      "authors": [
        "Chenghua Liu",
        "Boning Meng"
      ],
      "content_date": "2026-10-04",
      "freshness": "fresh",
      "id": "arxiv:2610.05412",
      "kind": "paper",
      "label": "adjacent",
      "matched_signals": [
        "lean_formal_proving_agents"
      ],
      "published": "2026-10-04",
      "score": 3.5,
      "source": "arxiv-ai4math-core",
      "summary": "We prove a complete complexity dichotomy for planar graph homomorphism counting with any fixed symmetric nonnegative matrix of arbitrary finite order, giving an explicit criterion for tractability. We also characterize exactly which fixed positive vertex weights preserve tractability, with both classifications extending from algebraic weights to fixed real weights in a prescribed exact representation. Our proof hinges on an entropy-based continuation argument: maximal logarithmic support identifies distance kernels as maximum-entropy completions, extending their positive definiteness throughout the parameter interval. This enables distance geometry to recover hidden product coordinates even when planar gadgets cannot distinguish colors; counting-hardness arguments then force the factors to be zero-field Boolean Ising interactions. The classification also yields complete tractability criteria for clock models, coupled Ising systems, and planar contractions of stoquastic imaginary-time kernels. All results have been formally verified in Lean 4.",
      "title": "A Dichotomy for Planar Graph Homomorphisms with Nonnegative Weights",
      "updated": "2026-10-04",
      "url": "https://arxiv.org/abs/2610.05412"
    },
    {
      "age_days": 4,
      "arxiv_id": "2610.04275",
      "authors": [
        "Ruoran Xu"
      ],
      "content_date": "2026-10-03",
      "freshness": "fresh",
      "id": "arxiv:2610.04275",
      "kind": "paper",
      "label": "adjacent",
      "matched_signals": [
        "lean_formal_proving_agents"
      ],
      "published": "2026-10-03",
      "score": 3.5,
      "source": "arxiv-ai4math-core",
      "summary": "Formal theorem proving increasingly combines learned semantic guidance with verified symbolic execution. The quality of the symbolic search substrate therefore determines how much useful mathematical structure can be accumulated, reused, and exposed under a finite inference budget. We introduce ViaLean, a Lean4 prover that organizes symbolic reasoning as bounded exploration of a persistent proof-state graph. Its search preserves coverage across complementary reasoning modes, merges semantically equivalent goals, retains verified intermediate structure, and observes short symbolic futures before committing to a transition. On the complete miniF2F test split, the model-free configuration solves 122/244 problems (50.0% pass@1). Historical and recent symbolic reference points range from Lean's earlier tidy search to modern grind and SMT-backed verification, showing that proof-space organization remains a substantial source of capability. The same persistent state also provides a natural interface for neural--symbolic agents: neural reasoning can operate over verified regions and intermediate objects while Lean continuously expands and validates the local proof space.",
      "title": "Symbolic Search Is Not Exhausted: Persistent Proof-Space Exploration in Lean4",
      "updated": "2026-10-03",
      "url": "https://arxiv.org/abs/2610.04275"
    },
    {
      "age_days": 1,
      "arxiv_id": "2610.08319",
      "authors": [
        "Hanchao Zhou",
        "Jialei Li"
      ],
      "content_date": "2026-10-06",
      "freshness": "fresh",
      "id": "arxiv:2610.08319",
      "kind": "paper",
      "label": "adjacent",
      "matched_signals": [
        "tool_use_agents"
      ],
      "published": "2026-10-06",
      "score": 1.9,
      "source": "arxiv-ai4math-core",
      "summary": "In proof assistants such as Lean, a generated proof must pass machine compilation checks, so evaluation needs no human scoring. Direct generation fails on multi-step numeric propositions: a proof is valid only if every content integer is correct, so the pass rate is bounded by the k-th power of the per-integer accuracy. Controlled corruption across 2,617 reference proofs confirms this power law. SCOPE (State-Conditioned Operator Planning and Execution) enforces the natural division of labor: the model plans over an operator vocabulary, a symbolic engine executes the numerics, and a compiler renders the proof. On a 218-problem suite it certifies 191/218 (87.6%) with a 135M backbone; the 7B DeepSeek-Prover-V1.5-RL certifies 18/218 at 27.5 times the tokens and 37.5 times the wall-clock, and DeepSeek-Prover-V2-7B certifies zero on a bidirectional dual suite. Multi-step thinking costs 6.12 discrete decision actions per problem and produces no natural-language thinking text. Replacing the lagged engine state in the decision frame with the current one lifts the pass rate from 117/218 to 191/218, while up-weighting the chain-end loss hurts. On the public Lean-Workbook library, 2,132 of 3,536 gradeable admissible problems certify (60.29%) with zero regression on the main suite. All readings come from a version-frozen review with independent rechecks and reverse verification. Restricting free generation and keeping decision-time information visible is a more direct route than enlarging the model.",
      "title": "SCOPE: Certified Theorem Proving with a Language Model as the Policy Planner",
      "updated": "2026-10-06",
      "url": "https://arxiv.org/abs/2610.08319"
    },
    {
      "age_days": 1,
      "arxiv_id": "2610.07905",
      "authors": [
        "Gábor P. Nagy",
        "Douglas S. McNeil",
        "Attila Vajda"
      ],
      "content_date": "2026-10-06",
      "freshness": "fresh",
      "id": "arxiv:2610.07905",
      "kind": "paper",
      "label": "adjacent",
      "matched_signals": [
        "general_ai_math_reasoning"
      ],
      "published": "2026-10-06",
      "score": 1.9,
      "source": "arxiv-ai4math-core",
      "summary": "Let $K$ be a finite field of characteristic two with $|K| = 2^{n}$, let $\\gcd(k,n) = 1$, let $d_{k} = 4^{k} - 2^{k} + 1$ be the Kasami exponent, and let $Δ_{k} = \\{(b+1)^{d_{k}} + b^{d_{k}} + 1 : b \\in K\\}$ be the image of the normalised derivative of the Kasami monomial in the direction $1$. We show that, for all distinct nonzero $v_{1},v_{2} \\in K$, \\[ \\bigl|\\{(x,y,z) \\in Δ_{k}^{3} : v_{1}x + v_{2}y + (v_{1}+v_{2})z = 0\\}\\bigr| = 2^{2n-3}. \\] This establishes the cyclic-additive difference-set condition introduced by Carlet and later posed for the Kasami functions at NSUCRYPTO~2019. Starting from the known half-size property of the derivative image, we express the Fourier correction as twisted root counts and prove their required nonnegativity by an incidence argument on the Fermat cubic. An exact average over the slopes then forces equality pointwise. The argument covers every admissible pair $(n,k)$ and has been formalised and machine-checked in Lean~4 with Mathlib.",
      "title": "Carlet's cyclic-additive conjecture for the Kasami monomials",
      "updated": "2026-10-06",
      "url": "https://arxiv.org/abs/2610.07905"
    },
    {
      "age_days": 2,
      "arxiv_id": "2610.06336",
      "authors": [
        "Jordi Daura Serrano",
        "Aron Gohr",
        "Marie-Amélie Lawn",
        "Travis Schedler"
      ],
      "content_date": "2026-10-05",
      "freshness": "fresh",
      "id": "arxiv:2610.06336",
      "kind": "paper",
      "label": "adjacent",
      "matched_signals": [
        "general_ai_math_reasoning"
      ],
      "published": "2026-10-05",
      "score": 1.9,
      "source": "arxiv-ai4math-core",
      "summary": "We prove the LeBrun--Salamon conjecture for positive quaternionic Kähler manifolds of quaternionic dimension n <= 14. To do so, we first show that the isometry group Isom(M) of any minimal counterexample M has rank at most one, hence dimension at most three. On the other hand, we consider a characteristic number which equals dim Isom(M) - (n+3) if n is even and dim Isom(M) - (n+1) if n is odd, and show that this index is a sum of positive quantities when n <= 14, yielding a contradiction. The toolset used to show positivity enlarges in stages. Projection curvature moments suffice through n=8; positive-semidefinite curvature moments extend the argument through n=10; and signed scalar orbital moments give the new inequalities needed for n=11,12. Scalar orbital moments alone fail at n=13; combining them with Hodge--Riemann positivity for squares of cohomology classes extends the proof to n=13,14. We give exact separating obstructions explaining the changes of method.",
      "title": "The Lebrun--Salamon conjecture is true in dimension up to 56",
      "updated": "2026-10-05",
      "url": "https://arxiv.org/abs/2610.06336"
    },
    {
      "age_days": 0,
      "authors": [
        "Henrik Böving"
      ],
      "content_date": "2026-10-07",
      "freshness": "fresh",
      "id": "github:leanprover/lean4:153e01180e59",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-10-07",
      "repo": "leanprover/lean4",
      "score": 0.8,
      "source": "lean4-github",
      "summary": "Recent commit on leanprover/lean4.",
      "title": "leanprover/lean4: refactor: implement `String.toList` in Lean (#15533)",
      "updated": "2026-10-07",
      "url": "https://github.com/leanprover/lean4/commit/153e01180e59305df575e24b803cf7416a251bcf"
    },
    {
      "age_days": 0,
      "authors": [
        "Sebastian Ullrich"
      ],
      "content_date": "2026-10-07",
      "freshness": "fresh",
      "id": "github:leanprover/lean4:3bd0c26d4730",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-10-07",
      "repo": "leanprover/lean4",
      "score": 0.8,
      "source": "lean4-github",
      "summary": "Recent commit on leanprover/lean4.",
      "title": "leanprover/lean4: perf: store imported module names in the environment header (#15543)",
      "updated": "2026-10-07",
      "url": "https://github.com/leanprover/lean4/commit/3bd0c26d4730fb2ece12d54c600ffa97099a77d3"
    },
    {
      "age_days": 0,
      "authors": [
        "Sebastian Ullrich"
      ],
      "content_date": "2026-10-07",
      "freshness": "fresh",
      "id": "github:leanprover/lean4:0cea69c5d0c1",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-10-07",
      "repo": "leanprover/lean4",
      "score": 0.8,
      "source": "lean4-github",
      "summary": "Recent commit on leanprover/lean4.",
      "title": "leanprover/lean4: perf: read reducibility status of theorems without waiting for their proofs (#15534)",
      "updated": "2026-10-07",
      "url": "https://github.com/leanprover/lean4/commit/0cea69c5d0c17d6d7eb81e6d3da7bed4c61953c0"
    },
    {
      "age_days": 0,
      "authors": [
        "Carlo Hamalainen"
      ],
      "content_date": "2026-10-07",
      "freshness": "fresh",
      "id": "github:leanprover/lean4:e7f3d517cd66",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-10-07",
      "repo": "leanprover/lean4",
      "score": 0.8,
      "source": "lean4-github",
      "summary": "Recent commit on leanprover/lean4.",
      "title": "leanprover/lean4: fix: use the RFC 9110 `GMT` date format for the HTTP `Date` header (#15469)",
      "updated": "2026-10-07",
      "url": "https://github.com/leanprover/lean4/commit/e7f3d517cd664fdd533f90d785d1a4e50263c8c6"
    },
    {
      "age_days": 0,
      "authors": [
        "Henrik Böving"
      ],
      "content_date": "2026-10-07",
      "freshness": "fresh",
      "id": "github:leanprover/lean4:7e9f797401dd",
      "kind": "github_update",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-10-07",
      "repo": "leanprover/lean4",
      "score": 0.8,
      "source": "lean4-github",
      "summary": "Recent commit on leanprover/lean4.",
      "title": "leanprover/lean4: fix: race condition in IR interpreter debug code (#15539)",
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      "source": "lean4-github",
      "summary": "Recent commit on leanprover/lean4.",
      "title": "leanprover/lean4: chore: move the lattice lemmas into one file per topic (#15396)",
      "updated": "2026-10-05",
      "url": "https://github.com/leanprover/lean4/commit/fcf20f7274de113fefa79cfe6e86b8e1c51eb44f"
    },
    {
      "age_days": 1,
      "arxiv_id": "2610.08144",
      "authors": [
        "Alexander Bastounis",
        "Fabian Circelli",
        "Anders C. Hansen"
      ],
      "content_date": "2026-10-06",
      "freshness": "fresh",
      "id": "arxiv:2610.08144",
      "kind": "paper",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-10-06",
      "score": 0.5,
      "source": "arxiv-ai4math-core",
      "summary": "Autoformalisation is increasingly used to verify mathematical texts, including those generated by AI, as in OpenAI's announced proof of blow-up of solutions to the Navier-Stokes equations. In this process, an AI system translates the text from a natural language (NL) into a formal language such as Lean. Once this translation is done, the argument expressed in the formal language can easily be mechanically verified. The purpose of this article is to demonstrate why this process may offer no confidence in the original NL argument, owing to the various difficulties in performing the translation semantically faithfully. In particular, we highlight that the problem of resolving ambiguities in mathematical NL text, which is necessary in order to provide semantically faithful translation, is arbitrarily high up in the Solvability Complexity Index (SCI) hierarchy/arithmetical hierarchy (the SCI $= \\infty$). Hence, informally, providing semantically faithful AI autoformalisation is harder than any computational problem including the Halting problem (which has SCI $= 1$). To demonstrate the effect of this result we provide several examples of AI mistranslations of NL statements and proofs into Lean in practice, resulting in mismatches between NL proofs and their Lean `verifications'. These include OpenAI's announced Navier-Stokes proof. In particular, we show that the formalised Lean proof does not correspond to the NL proof of blow-up of solutions to the Navier-Stokes equations.",
      "title": "Navier-Stokes lost in translation: Why Lean verification of AI autoformalisation does not guarantee correct natural language proofs",
      "updated": "2026-10-06",
      "url": "https://arxiv.org/abs/2610.08144"
    },
    {
      "age_days": 1,
      "arxiv_id": "2610.08723",
      "authors": [
        "Erfan Amidi",
        "Ali Asadian",
        "Ali Hamed Moosavian"
      ],
      "content_date": "2026-10-06",
      "freshness": "fresh",
      "id": "arxiv:2610.08723",
      "kind": "paper",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-10-06",
      "score": 0.5,
      "source": "arxiv-ai4math-core",
      "summary": "We prove that unknown pure fermionic states prepared from disjoint-branch fixed-particle-number blocks can be reconstructed after general quadratic evolution, including pair creation and annihilation. For a fixed particle cap per block, adaptive or nonadaptive single-copy Gaussian measurements yield classical input and circuit descriptions with prescribed fidelity and confidence, using polynomial resources in system size and inverse infidelity. The adaptive procedure has the sharper copy guarantee. Connected quartic correlations and a covariance-compatible commutant identify the hidden blocks; local states are recovered from fresh measurements or a predetermined bounded-degree moment table. Stable branch recovery gives valid preparation descriptions. Neither particle-number conservation nor block homogeneity is required; no lower bound on branch weights or covariance gaps is assumed. A certified variant returns a passive preparation whenever one exists within the promised family, without advance membership information. On the full Gaussian orbit of paired magic states, quartic measurements alone suffice, with an explicit bound converting observable error into state error.",
      "title": "Efficient Learning of Structured Fermionic States under General Quadratic Evolution",
      "updated": "2026-10-06",
      "url": "https://arxiv.org/abs/2610.08723"
    },
    {
      "age_days": 1,
      "arxiv_id": "2610.07605",
      "authors": [
        "Jinseong Kim",
        "Hyunchang Lee",
        "Keeman Lee",
        "Assaad R. Masri"
      ],
      "content_date": "2026-10-06",
      "freshness": "fresh",
      "id": "arxiv:2610.07605",
      "kind": "paper",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-10-06",
      "score": 0.5,
      "source": "arxiv-ai4math-core",
      "summary": "In this study, the lean extinction behaviors of CH4 and a 16% cracked ammonia surrogate fuel, CR16, in counterflow premixed flames were compared. Experiments were conducted along with one-dimensional simulations using OPPDIF; the GRI-Mech 3.0 and UCSD mechanisms were applied to CH4 and CR16, respectively. CR16 exhibited higher extinction strain rates and resilience to strain-induced blow-out (RSIB) than those of CH4 under lean conditions. At Phi = 0.66, although both flames had the same extinction strain rate, CR16 showed a higher RSIB because of its longer flame time. Near its extinction, CR16 sustained H2 consumption, radical reactions, and heat release through the interflame region toward the stagnation plane. Hydrogen oxidation coupled with nitrogen-related pathways, including NH2 + NO and HNO reactions, supported this behavior. These results clarify the chemical basis for the superior extinction resistance of economically favorable low-cracking-ratio ammonia fuel.",
      "title": "Characteristics of extinction behavior of ammonia partial cracking simulated fuels in counterflow premixed flames under lean condition",
      "updated": "2026-10-06",
      "url": "https://arxiv.org/abs/2610.07605"
    },
    {
      "age_days": 2,
      "arxiv_id": "2610.06742",
      "authors": [
        "Patrick Hayden",
        "Alexander Maloney",
        "Jinzhao Wang",
        "Yuxiang Yang"
      ],
      "content_date": "2026-10-05",
      "freshness": "fresh",
      "id": "arxiv:2610.06742",
      "kind": "paper",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-10-05",
      "score": 0.5,
      "source": "arxiv-ai4math-core",
      "summary": "We study a variant of Schumacher compression. The task asks for the minimal memory cost for compressing many copies of a density matrix with known spectrum and unknown eigenbasis, without preserving its purification. For fixed dimension and distinct positive eigenvalues, we obtain the cost through its additive constant. Achievability uses a generalization of Werner's cloning map to $\\mathrm{GL}(d,\\mathbb C)$ irreducible representations, with finite trace-distance bounds controlled by highest-weight differences and row gaps. The matching converse follows from a quantitative form of Koashi--Imoto incompressibility for irreducible group orbits under a spectral-gap assumption. We also identify the relation between this quantum minimum description length and universal lossless coding overhead, and its connection to free entropy is explained in a companion letter. We provide a Lean certificate for our proofs.",
      "title": "Quantum minimum description of density matrices",
      "updated": "2026-10-05",
      "url": "https://arxiv.org/abs/2610.06742"
    },
    {
      "age_days": 2,
      "arxiv_id": "2610.06674",
      "authors": [
        "Srija Chakraborty"
      ],
      "content_date": "2026-10-05",
      "freshness": "fresh",
      "id": "arxiv:2610.06674",
      "kind": "paper",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-10-05",
      "score": 0.5,
      "source": "arxiv-ai4math-core",
      "summary": "Nighttime lights from NASA's Black Marble product suite capture thermal and light emission signals from anomalous events including fires, volcanic eruptions, and gas flaring. Existing detection approaches rely primarily on thermal bands, limiting sensitivity to weaker signals. We propose a novel machine learning framework that jointly models Black Marble M-band and Day/Night Band (DNB) signals to derive a generalized, spatio-temporally robust ensemble of anomaly detectors. The framework iteratively builds detectors that scale across regions, seasons, anomaly classes, and extends over land and ocean. Detection sets at varying confidence levels are derived based on relevant bands and detector agreement. The approach improves true detection rate while reducing spurious detections and results demonstrate strong generalizability with applications in natural hazard monitoring and energy extraction.",
      "title": "Detecting Nighttime Anomalies from NASA Black Marble Using a Generalized Spatio-Temporally Robust Framework of Machine Leaning Ensembles",
      "updated": "2026-10-05",
      "url": "https://arxiv.org/abs/2610.06674"
    },
    {
      "age_days": 2,
      "arxiv_id": "2610.06368",
      "authors": [
        "Jörg Endrullis",
        "Ievgen Ivanov",
        "Femke van Raamsdonk"
      ],
      "content_date": "2026-10-05",
      "freshness": "fresh",
      "id": "arxiv:2610.06368",
      "kind": "paper",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-10-05",
      "score": 0.5,
      "source": "arxiv-ai4math-core",
      "summary": "Confluence is a fundamental property of nondeterministic computations, arising from parallelism, concurrency, or freedom in the evaluation order. It guarantees that such a computation always yields the same result, regardless of the order in which steps are taken. The decreasing diagrams technique of van Oostrom is one of the most versatile methods for establishing confluence of transition systems (abstract rewriting systems). It reduces global confluence to local confluence: a system is confluent whenever its transitions admit a locally decreasing labeling. Essentially all classical confluence criteria arise as corollaries. A central question, posed by van Oostrom in 1993, asks whether the decreasing diagrams technique is complete: Does every confluent transition system admit a locally decreasing labeling? This is Problem 56 of the RTA List of Open Problems. A positive answer was known only for countable systems, and recently up to the first uncountable cardinal $\\aleph_1$. The general case remained open. We settle this thirty-three-year-old problem in full. We prove that every confluent transition system admits a locally decreasing labeling using only three labels. This bound is optimal, as two labels do not suffice even at the first uncountable cardinality. It follows that this single criterion can, in principle, certify the confluence of every confluent system, and hence of every confluent program. The entire development is machine-checked in the Isabelle/HOL and Lean proof assistants and relies only on classical logic and the axiom of choice.",
      "title": "Decreasing Diagrams are Complete for Confluence",
      "updated": "2026-10-05",
      "url": "https://arxiv.org/abs/2610.06368"
    },
    {
      "age_days": 2,
      "arxiv_id": "2610.07292",
      "authors": [
        "Jyotishka Ray Choudhury",
        "Kabir Aladin Verchand",
        "Richard J. Samworth",
        "Ashwin Pananjady"
      ],
      "content_date": "2026-10-05",
      "freshness": "fresh",
      "id": "arxiv:2610.07292",
      "kind": "paper",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-10-05",
      "score": 0.5,
      "source": "arxiv-ai4math-core",
      "summary": "Missing covariates are frequently encountered in supervised learning problems, and classical methods for estimation using such data use carefully chosen imputation schemes for missing data, or likelihood approximations that lead to nonconvex $M$-estimation problems. These methods and their relatives are suitable for scenarios in which the covariate distribution is known, and more broadly, have enjoyed tremendous success in linear models. But even in basic nonlinear problems such as logistic regression in moderate dimensions, such methods can experience drastic failure modes when the covariate distribution is unknown. Motivated by the need for reliable alternatives, we consider the problem of parameter estimation in logistic regression with missing covariates. Crucially, we operate in the assumption-lean setting where the covariate distribution is unknown (but bounded). We design a stochastic approximation method that is based on $Z$-estimation with a novel monotone operator, and establish that our algorithm is computationally efficient and achieves provable signal recovery at parametric rates under the hypothesis that covariates are missing completely at random. Our theory sharply characterizes the $\\ell_2^2$ risk of the estimator in terms of the missingness profile, accommodating heterogeneous observation probabilities. Importantly, it shows that our method always outperforms the de facto ``complete-case'' estimator that ignores observations with any missing data. Even in the setting with homogeneous missingness (in which each covariate is observed independently with probability $q$), our bounds exhibit intricate and nonstandard dependence on $q$ that can yield significant improvements over using only complete cases. We complement our upper bounds with new information-theoretic lower bounds that show that this intricate dependence on $q$ is fundamental in a minimax sense.",
      "title": "Assumption-lean logistic regression with missing covariates",
      "updated": "2026-10-05",
      "url": "https://arxiv.org/abs/2610.07292"
    },
    {
      "age_days": 3,
      "arxiv_id": "2610.05490",
      "authors": [
        "Leo Brunswic"
      ],
      "content_date": "2026-10-04",
      "freshness": "fresh",
      "id": "arxiv:2610.05490",
      "kind": "paper",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-10-04",
      "score": 0.5,
      "source": "arxiv-ai4math-core",
      "summary": "Generative flows sample from an unnormalized target by training a flow to be balanced, and the training loss is the signal a practitioner watches. We ask what that signal is worth: whether a small loss certifies an accurate sampler, whether the loss can be driven to zero, and how fast gradient descent does so. The loss decides the first. Losses that compare the two sides of the balance by their difference bound, in total variation, the error of the sampler the flow implies, with explicit constants that do not involve the policy; flow-matching losses that compare them through a ratio admit no such bound, already on a single cycle, whenever their generator is continuous at balance. On graphs, the backward policy decides the other two. Once it is frozen, balance becomes invariance under the backward chain, so that existence is free on finite graphs, and one constant --- the norm of that chain's Green operator, which plays the role of an inverse spectral gap --- fixes the order of the curvature of the loss around the balanced flow, from above and below, and sets a floor under the rate at which training converges near it. The mechanism is that gradient descent diffuses the flow along the backward policy. For the squared-logarithm generator of detailed and trajectory balance, training the balance loss on states converges globally on every finite path-connected graph, from every positive initialization. The constant can be infinite while backward trajectories are short on average, and exact flow matching can then fail. The bounds and rates are tested by exact computation on enumerable state spaces, and every theorem carries a certification status computed from a Lean~4 development.",
      "title": "Universality and Convergence of Generative Flows",
      "updated": "2026-10-04",
      "url": "https://arxiv.org/abs/2610.05490"
    },
    {
      "age_days": 3,
      "arxiv_id": "2610.05186",
      "authors": [
        "Jeff Calder",
        "Nadejda Drenska"
      ],
      "content_date": "2026-10-04",
      "freshness": "fresh",
      "id": "arxiv:2610.05186",
      "kind": "paper",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-10-04",
      "score": 0.5,
      "source": "arxiv-ai4math-core",
      "summary": "We prove that no single rank ordered adversary strategy is globally optimal for the prediction with expert advice problem with six or more experts, in both the geometric stopping and finite time horizon settings. The proof is based on establishing a leading order correction when one expert moves far ahead of the others. This allows us to connect optimal strategies between $n$ and $j<n$ experts and utilize recent results on the exact optimality set for the five expert problem.",
      "title": "On prediction from expert advice with more than five experts",
      "updated": "2026-10-04",
      "url": "https://arxiv.org/abs/2610.05186"
    },
    {
      "age_days": 4,
      "arxiv_id": "2610.06935",
      "authors": [
        "Arjun Pemmasani"
      ],
      "content_date": "2026-10-03",
      "freshness": "fresh",
      "id": "arxiv:2610.06935",
      "kind": "paper",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-10-03",
      "score": 0.5,
      "source": "arxiv-ai4math-core",
      "summary": "A ball bounces down a Galton board, where its first bounce's direction is fair while every later bounce repeats the previous bounce's direction with probability $p$, all the way down to some bin. We ask for which $p$ the middle bin is exactly as likely as the end bins, a question originally posed by Kagey. We find that for $N$ bounces, the tie occurs when the ball changes direction (turns) approximately $\\log N$ times on average. We compare the central bin with a Bessel function, with an error bound that is explicit for all $N$. This yields an explicit interval for the tie at every $N \\geq 2$, rather than just for large $N$. This is done analytically for $N \\geq 175$, and for smaller $N$ exactly by integer arithmetic, cross-verified in Lean. We also find the tie of every other bin with the end bins and the shift caused by periodic boundaries.",
      "title": "Uniform Bessel bounds for endpoint crossings in the persistent random walk",
      "updated": "2026-10-03",
      "url": "https://arxiv.org/abs/2610.06935"
    },
    {
      "age_days": 4,
      "arxiv_id": "2610.04774",
      "authors": [
        "Matteo Nerini",
        "Xuekang Liu",
        "Bruno Clerckx"
      ],
      "content_date": "2026-10-03",
      "freshness": "fresh",
      "id": "arxiv:2610.04774",
      "kind": "paper",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-10-03",
      "score": 0.5,
      "source": "arxiv-ai4math-core",
      "summary": "Analog computing with microwave signals can perform linear transformations directly in the analog domain, as the signals propagate through a microwave network. A fundamental question is which transformations can be computed with a given set of microwave components. In our previous work, we answered this question for networks of hybrid couplers and phase shifters by deriving a necessary and sufficient condition on the transformations these networks can compute, and we showed that the discrete Fourier transform (DFT) satisfies it. In this paper, we take a first step toward the formalization of analog computing with microwaves in Lean, a programming language and proof assistant that is increasingly adopted in mathematics. We formalize the considered components, their series and parallel connections, and the class of networks they can implement. Then, we formally prove the necessary and sufficient condition characterizing these networks, as well as the implementability of the DFT of any size power of two. All proofs are checked by the Lean kernel, and the code is openly available at: https://github.com/matteonerini/formalizing-analog-computing.",
      "title": "Toward a Lean Formalization of Analog Computing with Microwaves",
      "updated": "2026-10-03",
      "url": "https://arxiv.org/abs/2610.04774"
    },
    {
      "age_days": 4,
      "arxiv_id": "2610.04511",
      "authors": [
        "Marianna Girlando",
        "Fabrizio Montesi"
      ],
      "content_date": "2026-10-03",
      "freshness": "fresh",
      "id": "arxiv:2610.04511",
      "kind": "paper",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-10-03",
      "score": 0.5,
      "source": "arxiv-ai4math-core",
      "summary": "Modal logic comprises a broad family of logics to reason about relational structures. The literature presents many such logics, displaying diverse operators, semantics, and applications. This plurality is reflected in a zoo of mechanised modal logics, which often duplicate syntax, semantics, metatheory, and reasoning infrastructure. We present a library-grade formalisation of modal logic in Lean, developed as part of CSLib (the Lean Computer Science Library) and designed around two complementary forms of reuse: vertical reuse, whereby specialised logics inherit from common abstractions, and horizontal reuse, whereby modal logic becomes a reasoning tool for independently formalised domains. Our development provides a generic framework for polyadic modal languages, reusable metatheory and proof automation, and derived interfaces for specialised modal logics. We exemplify our infrastructure by deriving basic modal logic, basic temporal logic, and Hennessy-Milner Logic; the latter subsumes and extends CSLib's previous implementation while reducing its logic-specific code by 67%. We further apply the same modal infrastructure to reasoning about mathematics (radicals of ideals), theory of programming languages (the type safety strategy for the simply typed $λ$-calculus), and concurrency theory (reasoning about processes in the Calculus of Communicating Systems). Our experience suggests that reuse, automation, and integration with the strong Lean ecosystem should be treated as first-class design concerns when formalising theories for shared libraries.",
      "title": "Library-Grade Modal Logic",
      "updated": "2026-10-03",
      "url": "https://arxiv.org/abs/2610.04511"
    },
    {
      "age_days": 4,
      "arxiv_id": "2610.04182",
      "authors": [
        "Levi Boxell",
        "Jacob Conway",
        "Nicolas Longuet-Marx"
      ],
      "content_date": "2026-10-03",
      "freshness": "fresh",
      "id": "arxiv:2610.04182",
      "kind": "paper",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-10-03",
      "score": 0.5,
      "source": "arxiv-ai4math-core",
      "summary": "What role do journalists play in determining the political slant of the news they produce? We develop and estimate a model where journalists and newspaper outlets contract over both slant and wages. The model implies a set of conditions under which we can consistently estimate the role of journalist preferences in driving the observed variation in slant across outlets by leveraging journalist transitions between outlets. To measure slant, we train a transformer-based, machine learning model using articles tweeted by politicians and apply it to a full-text database of 9+ million newspaper articles published in the US between 2013 and 2018. Under our model and identifying assumptions, our estimates (a) reject the hypothesis that journalists have zero ideological preferences over the content they produce and (b) imply that 10% of the variation in slant can be explained by journalists. When journalists move across outlets, their average slant shifts by 77% of the gap between their destination and origin outlet averages. In counterfactuals that reweight journalist party composition, moving from the observed left-leaning distribution to an even distribution of Democrats, Republicans, and non-partisans shifts average article slant in a more conservative direction, but only by 0.04 standard deviations in slant.",
      "title": "Journalist Ideology and the Production of News: Evidence from Movers",
      "updated": "2026-10-03",
      "url": "https://arxiv.org/abs/2610.04182"
    },
    {
      "age_days": 4,
      "arxiv_id": "2610.04666",
      "authors": [
        "Zijian Gong",
        "Zhaobin Lyu",
        "Jingjing Hu",
        "Dengfeng Li",
        "Shuoming An"
      ],
      "content_date": "2026-10-03",
      "freshness": "fresh",
      "id": "arxiv:2610.04666",
      "kind": "paper",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-10-03",
      "score": 0.5,
      "source": "arxiv-ai4math-core",
      "summary": "Quantum computers are claimed to produce samples ordinary classical computers cannot reproduce. The sharpest such claim known pits constant-depth quantum circuits, given one entangled state per run, against shallow classical circuits of few-input gates and limited randomness. No efficient test was known that certifies such a claim from classical samples alone. Here we show that what such a test must read is decided by the classical class's pattern of single-bit and pair correlations, not by a distance. The test rests on one inequality: any machine producing the samples sits no further from the target than the fraction it mislabels plus the deviation of its string half, the bits beyond the label, from uniform. A collapse theorem, machine-checked in the Lean~4 proof assistant, confines that second term, one setting of the sampler's random input bits at a time. Four natural checks provably fail; a fifth, reading those same correlations, catches a far-from-target construction they cannot reach, and is exact on the class of few-input gates. The label test is proven and sample-optimal in its own tolerance up to a logarithmic factor; the fifth check is sound, not only effective, on the bounded pinned-residue class, pairwise-uniform samplers whose residue, the string's weight modulo the prime, is pinned by few seeds and whose seed sharing is bounded. What binds an experiment is the $43$-qubit entangled resource state at fidelity near $0.99$, not the readout. What remains are two named open problems; a positive answer to the first would extend the guarantee to the full class.",
      "title": "Correlations decide a shallow-circuit advantage",
      "updated": "2026-10-03",
      "url": "https://arxiv.org/abs/2610.04666"
    },
    {
      "age_days": 5,
      "arxiv_id": "2610.02814",
      "authors": [
        "Naing Oo Lwin"
      ],
      "content_date": "2026-10-02",
      "freshness": "fresh",
      "id": "arxiv:2610.02814",
      "kind": "paper",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-10-02",
      "score": 0.5,
      "source": "arxiv-ai4math-core",
      "summary": "Keeping a Python program and its formal guarantees aligned is a continuing maintenance problem. Specifications must describe the implementation that actually runs, and updates must preserve the behavior on which existing callers depend. VeriPy brings these obligations into a common workflow for annotated Python components. Developers and agents express contracts, invariants, and proof hooks as Python comments, then refine checked auxiliary lemmas using source-located diagnostics. Direct encoders produce Dafny or Lean artifacts while retaining admitted executable bodies and explicit models of their dependencies. A relational product checks whether an updated component still admits old inputs and preserves returned values and modeled exceptions. The resulting workflow connects source-level proof development with functional verification and backward compatibility, recording the assumptions under which each guarantee applies. The code is available at https://github.com/astrio-labs/veripy.",
      "title": "VeriPy Source-Preserving Verification and Compatibility Checking for Python Components",
      "updated": "2026-10-02",
      "url": "https://arxiv.org/abs/2610.02814"
    },
    {
      "age_days": 5,
      "arxiv_id": "2610.02833",
      "authors": [
        "Deep Bhattacharjee",
        "Priyabrata Mandal",
        "Ushashi Bhattacharya"
      ],
      "content_date": "2026-10-02",
      "freshness": "fresh",
      "id": "arxiv:2610.02833",
      "kind": "paper",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-10-02",
      "score": 0.5,
      "source": "arxiv-ai4math-core",
      "summary": "We prove both Erdős-Ulam conjectures on monochromatic union-closed families. Every two-colouring of the subsets of a finite set contains a monochromatic union-closed family whose size grows faster than any fixed power of the size of the set, while suitable colourings admit no monochromatic union-closed family of exponential size. Both results hold for any number of colours and are verified in Lean.",
      "title": "Resolving Erdős-Ulam Monochromatic Union-Closed Family Conjectures",
      "updated": "2026-10-02",
      "url": "https://arxiv.org/abs/2610.02833"
    },
    {
      "age_days": 5,
      "arxiv_id": "2610.03651",
      "authors": [
        "Sean Culatana",
        "Shang-En Huang",
        "Kang Li"
      ],
      "content_date": "2026-10-02",
      "freshness": "fresh",
      "id": "arxiv:2610.03651",
      "kind": "paper",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-10-02",
      "score": 0.5,
      "source": "arxiv-ai4math-core",
      "summary": "Dense-retrieval services must switch among embedding-prefix dimensions and index bit rates as latency, quality, and memory budgets change. Tuning a quantizer separately for each rate gives the best quality, but the retrieval tier then holds several code streams and quantizer states at once. We introduce Matryoshka Residual Vector Quantization (MRVQ), a post-hoc residual quantizer for frozen embeddings. Its maximum-rate code can be truncated two ways: dropping residual stages lowers the rate, and dropping embedding coordinates lowers the dimension. One resident artifact therefore serves every (dimension, rate) pair we evaluate. Across FiQA and NFCorpus, four embedding families, and {4, 8, 16}-byte codes, MRVQ is the lowest-RAM design we evaluate. It uses 17.8-22.0x less memory than three separately trained QINCo2 indices, and 1.89-2.02x less than a lean shared-model steelman. The saving is not free: per-rate QINCo2 is 0.026-0.107 nDCG@10 better on FiQA. But MRVQ beats PQ, OPQ, and AdANNS-OPQ at matched code size. We also evaluate a low-build-cost PCA-scalar design that attains quality comparable to RaBitQ and its extension while fitting 420x faster at the median. Finally, we report two negative results: QINCo2 collapses when trained at high rates, and a ranking-bound hypothesis misses its pre-specified acceptance criteria. MRVQ is therefore a low-memory operating point for elastic retrieval, not a universal quality winner.",
      "title": "MRVQ: One Resident Index for Dimension- and Rate-Elastic Vector Search",
      "updated": "2026-10-02",
      "url": "https://arxiv.org/abs/2610.03651"
    },
    {
      "age_days": 5,
      "arxiv_id": "2610.03364",
      "authors": [
        "Jens Palsberg",
        "Keli Huang",
        "Abdullah Almanei"
      ],
      "content_date": "2026-10-02",
      "freshness": "fresh",
      "id": "arxiv:2610.03364",
      "kind": "paper",
      "label": "negative",
      "matched_signals": [],
      "published": "2026-10-02",
      "score": 0.5,
      "source": "arxiv-ai4math-core",
      "summary": "A well-known theorem states that the Clifford+T gate set is universal for quantum computing. The theorem combines approximation using a distance measure on unitary matrices with equality up to global phase. Previous proofs combine these two notions for specific distance measures, but do not identify the properties that govern how they work together. Which properties are sufficient to state and prove the theorem? We answer this question by defining projective distance measures using four axioms. We prove that the universality theorem holds for every distance measure satisfying these axioms. Thus, our formulation of the theorem is independent of any particular choice of distance measure. We show that the Hilbert-Schmidt distance is already a projective distance measure. We also develop a general construction that transforms a large class of distance measures into projective distance measures and apply it to obtain projective versions of the operator-norm distance, the Frobenius distance, and the trace distance. Finally, we formalize the proof of the universality theorem in Lean.",
      "title": "Distance-Independent Universality of Clifford+T",
      "updated": "2026-10-02",
      "url": "https://arxiv.org/abs/2610.03364"
    }
  ],
  "lookback_days": 21,
  "schema": "ai4math-radar-run-v1",
  "timezone": "America/Los_Angeles"
}
