Daily field radar

AI4Math Radar

Start with Rtl2lean: Automated RTL-to-Lean Translation with Hierarchical Theorem Generation and Lemma Reuse, then CausalForge: A Formally Grounded, Self-Improving Agentic Framework for Automated Research in Causal Inference. 19 fresh useful item(s) are inside the 21-day content window.

2026-07-27
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America/Los_Angeles Generated 2026-07-27T17:18:53Z JSON data
4core
15adjacent
70downweighted
0warnings

Today's Scan

Start with Rtl2lean: Automated RTL-to-Lean Translation with Hierarchical Theorem Generation and Lemma Reuse, then CausalForge: A Formally Grounded, Self-Improving Agentic Framework for Automated Research in Causal Inference. 19 fresh useful item(s) are inside the 21-day content window.

Source Mix

  • arXiv19

Best Use

Open only the first lane during a busy morning. Older recurring seeds are kept below the daily scan instead of competing with fresh items.

Start Here

The top few items most likely to matter for formal proof agents or Lean-facing AI4Math work.

1
core score 9.5 2026-07-18 arXiv

Rtl2lean: Automated RTL-to-Lean Translation with Hierarchical Theorem Generation and Lemma Reuse

Hongqin Lyu, Junxing Dong, Yonghao Wang et al.

Formal verification with interactive theorem provers can provide strong correctness guarantees for register transfer level designs, but applying it to existing SystemVerilog code requires substantial manual effort in semantic modeling and proof construction...

Why it matters Most relevant if you are tracking proof-search loops that use verifier feedback instead of treating Lean as a binary oracle.

Skim cue Skim which definitions entered Lean and whether the work adds reusable library surface.

Read if Read if you have 5 minutes and want a direct AI4Math signal.

Lean proof agentsverifier feedback
Open PDF Semantic Scholar
2
core score 7.9 2026-07-24 arXiv

CausalForge: A Formally Grounded, Self-Improving Agentic Framework for Automated Research in Causal Inference

Jiyuan Tan, Vasilis Syrgkanis

Automating theoretical research is constrained not only by the generation of candidate results, but also by their reliable evaluation. A common approach is to close the research loop with a large language model (LLM) reviewer. However, such reviewers remain...

Why it matters Most relevant if you are tracking proof-search loops that use verifier feedback instead of treating Lean as a binary oracle.

Skim cue Skim the search loop: proposal source, verifier call, retry strategy, and stopping rule.

Read if Read if you have 5 minutes and want a direct AI4Math signal.

mathlib searchtool-use agentsverifier feedback
Open PDF Semantic Scholar
3
core score 7.9 2026-07-19 arXiv

Self-Modifying Lean Proof Agents with Verifier-Grounded Benchmark Coevolution

Yuqing Li, Zeguan Wu, Yu Gan et al.

Designing effective Lean proof agents is a central challenge in formal mathematical reasoning. Beyond building stronger provers, recent work emphasizes the workflow around Lean: how an agent decomposes proof obligations, uses tools and compiler feedback, di...

Why it matters Most relevant if you are tracking proof-search loops that use verifier feedback instead of treating Lean as a binary oracle.

Skim cue Skim the task definition, metric, and whether the benchmark has Lean-checkable artifacts.

Read if Read if you have 5 minutes and want a direct AI4Math signal.

AI math reasoningverifier feedback
Open PDF Semantic Scholar

Worth Opening

Good candidates after the first three. These are plausible paper-tab opens, not a mandatory reading list.

4
core score 6.5 2026-07-23 arXiv

Benchmarking Agents for Proving Theorems in Quantum Algorithms and Quantum Information

Lei Zhang, Yusheng Zhao, Yimeng Cao et al.

Formal verification is becoming increasingly practical for quantum computing, yet the ability of AI agents to construct machine-checkable proofs in this domain remains unmeasured. We introduce Lean-QuantumAlg-Bench and Lean-QIT-Bench, two Lean 4 benchmarks...

Why it matters Most relevant if you are tracking proof-search loops that use verifier feedback instead of treating Lean as a binary oracle.

Skim cue Skim the task definition, metric, and whether the benchmark has Lean-checkable artifacts.

Read if Read if you have 5 minutes and want a direct AI4Math signal.

Lean proof agentsverifier feedback
Open PDF Semantic Scholar
5
adjacent score 4.9 2026-07-21 arXiv

Single Link Removal Perturbation in Szegedy Quantum Walk: from Graph Completeness Testing to Integrity Monitoring

Sara Giordano, Miguel A. Martin-Delgado

We present a rigorous perturbative analysis of the Szegedy quantum walk search algorithm on the complete graph with marked nodes, when a specific anomaly is present in the graph. This is motivated by the problem of monitoring the integrity of dense trusted...

Why it matters Direct Lean signal: likely relevant to the formalization or theorem-proving environment around AI4Math agents.

Skim cue Skim the search loop: proposal source, verifier call, retry strategy, and stopping rule.

Read if Save for later unless the title matches your current proof-agent work.

AI math reasoningLean proof agents
Open PDF Semantic Scholar
6
adjacent score 3.5 2026-07-24 arXiv

Machine-Checked Arithmetic Bit Complexity of the Kannan-Bachem Smith Normal Form in Lean 4

Junye Ji

We formalize in Lean 4 the Kannan-Bachem Smith normal form algorithm for nonsingular square integer matrices. The program returns $S,U,U^{-1},V,V^{-1}$ and proves $UAV=S$, $U^{-1}SV^{-1}=A$, four inverse identities, the Smith divisibility conditions, and eq...

Why it matters Direct Lean signal: likely relevant to the formalization or theorem-proving environment around AI4Math agents.

Skim cue Skim which definitions entered Lean and whether the work adds reusable library surface.

Read if Save for later unless the title matches your current proof-agent work.

Lean proof agents
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7
adjacent score 3.5 2026-07-23 arXiv

Cofinite Zeros of High Derivatives

Eric Hou

We construct a nonzero transcendental entire function such that every nonempty open subset of the complex plane contains a zero of every sufficiently high derivative; equivalently, the union of the zero sets along every infinite increasing sequence of deriv...

Why it matters Direct Lean signal: likely relevant to the formalization or theorem-proving environment around AI4Math agents.

Skim cue Skim which definitions entered Lean and whether the work adds reusable library surface.

Read if Save for later unless the title matches your current proof-agent work.

Lean proof agents
Open PDF Semantic Scholar
8
adjacent score 3.5 2026-07-23 arXiv

Case study: proving sqrt(2) irrational with LPTP and an LLM

Fred Mesnard, Étienne Payet, Wim Vanhoof

We present the interactions with an LLM (Large Language Model) aiming at proving that the square root of 2 is not a rational number in an LP (Logic Programming) context. We start from a few basic pure logic programming predicate definitions. We rely on the...

Why it matters Direct Lean signal: likely relevant to the formalization or theorem-proving environment around AI4Math agents.

Skim cue Skim the abstract first; open the paper only if the method touches proof agents or formal verification.

Read if Save for later unless the title matches your current proof-agent work.

Lean proof agents
Open PDF Semantic Scholar
9
adjacent score 3.5 2026-07-22 arXiv

Pure-DP Statistical Query Release at the Conjectured Square-Root Rate

Jack Fitzsimons

Nikolov and Ullman asked whether k statistical queries on a universe of size T can be released under pure differential privacy with expected worst-coordinate error at the square-root rate suggested by known lower bounds. We prove their conjectured upper bou...

Why it matters Direct Lean signal: likely relevant to the formalization or theorem-proving environment around AI4Math agents.

Skim cue Skim which definitions entered Lean and whether the work adds reusable library surface.

Read if Save for later unless the title matches your current proof-agent work.

Lean proof agents
Open PDF Semantic Scholar
10
adjacent score 3.5 2026-07-22 arXiv

From Dag-Like Proofs to Boolean Circuits in Lean

Lorenzo Saraiva, Edward Hermann Haeusler

In this article, we present a method for encoding Dag-Like Derivability Structures (DLDS), obtained via horizontal compression of Natural Deduction proofs in purely implicational minimal logic, as Boolean circuits. These DLDS compress Natural Deduction tree...

Why it matters Direct Lean signal: likely relevant to the formalization or theorem-proving environment around AI4Math agents.

Skim cue Skim which definitions entered Lean and whether the work adds reusable library surface.

Read if Save for later unless the title matches your current proof-agent work.

Lean proof agents
Open PDF Semantic Scholar
11
adjacent score 3.5 2026-07-22 arXiv

A Machine-checked Proof of Consistency for Impredicative Pure Type Systems

Sebastián Urciuoli

In this paper we continue assessing the feasibility of the approach to the mechanization of type theory by using classical syntax and Stoughton's multiple substitutions and report some substantial progress. We present formal proofs of confluence for beta-re...

Why it matters Most relevant if you are tracking proof-search loops that use verifier feedback instead of treating Lean as a binary oracle.

Skim cue Skim the abstract first; open the paper only if the method touches proof agents or formal verification.

Read if Save for later unless the title matches your current proof-agent work.

verifier feedback
Open PDF Semantic Scholar
12
adjacent score 3.5 2026-07-21 arXiv

The Limits of Quantum Computers for Power Flow

Cameron Khanpour, Samuel Talkington

This letter proves realistic grid properties limit the applicability of quantum computers for power flow. Grids that split into two large regions meeting at only a few buses, common in transmission networks, force the pseudo condition number of the DC susce...

Why it matters Direct Lean signal: likely relevant to the formalization or theorem-proving environment around AI4Math agents.

Skim cue Skim which definitions entered Lean and whether the work adds reusable library surface.

Read if Save for later unless the title matches your current proof-agent work.

Lean proof agents
Open PDF Semantic Scholar

Watch Later

Adjacent formalization or infrastructure signals. Keep them in peripheral vision unless they match an active project.

13
adjacent score 3.5 2026-07-20 arXiv

1-out-of-5 Maximin-Share Allocations Always Exist for Four Agents

Christoph Schwerdtfeger

For four agents with nonnegative additive valuations, a complete 1-out-of-5 maximin-share allocation always exists, improving the previous 1-out-of-6 guarantee. Together with known exact-MMS counterexamples, this completely characterizes the four-agent case...

Why it matters Direct Lean signal: likely relevant to the formalization or theorem-proving environment around AI4Math agents.

Skim cue Skim which definitions entered Lean and whether the work adds reusable library surface.

Read if Save for later unless the title matches your current proof-agent work.

Lean proof agents
Open PDF Semantic Scholar
14
adjacent score 3.5 2026-07-18 arXiv

Half the Experts, All the Code: One-Shot Domain Pruning of Mixture-of-Experts LLMs for Coding

Anik Jha

The strongest open-weight coding models are mixture-of-experts (MoE) networks: most of their size comes from large pools of "expert" subnetworks, of which only a few act on any token. That pool is why these models do not fit on the machines most developers...

Why it matters Most relevant if you are tracking proof-search loops that use verifier feedback instead of treating Lean as a binary oracle.

Skim cue Skim the task definition, metric, and whether the benchmark has Lean-checkable artifacts.

Read if Save for later unless the title matches your current proof-agent work.

verifier feedback
Open PDF Semantic Scholar
15
adjacent score 3.5 2026-07-17 arXiv

Oblivious Probabilistic Outcome Logic: Verifying Probabilistic Programs with an Oblivious Adversary

Hanxi Chen, Noam Zilberstein, Andrew C. Myers et al.

In the context of probabilistic programs, an oblivious adversary resolves nondeterminism without seeing the outcomes of random draws. Obliviousness is a common assumption in online algorithms and distributed protocols, but the complex interaction between ra...

Why it matters Direct Lean signal: likely relevant to the formalization or theorem-proving environment around AI4Math agents.

Skim cue Skim which definitions entered Lean and whether the work adds reusable library surface.

Read if Save for later unless the title matches your current proof-agent work.

Lean proof agents
Open PDF Semantic Scholar
16
adjacent score 3.5 2026-07-17 arXiv

Feedback Attribution and Representation Geometry: Metrics for Comparing Individual and Shared Rewards in MARL

Tasha Pais, Richard Higgins

Cooperative multi-agent RL systems routinely use team-averaged rewards, a feedback-attribution choice that gives each agent the team outcome regardless of its individual contribution. We ask whether this leaves a measurable signature, geometric or behaviora...

Why it matters Most relevant if you are tracking proof-search loops that use verifier feedback instead of treating Lean as a binary oracle.

Skim cue Skim the reward construction and whether failures provide dense learning signal.

Read if Save for later unless the title matches your current proof-agent work.

verifier feedback
Open PDF Semantic Scholar
17
adjacent score 1.9 2026-07-22 arXiv

Molt: A Scalable PyTorch-Native Training Framework for Agentic Reinforcement Learning

Jian Hu, Huiying Li, Hao Zhang et al.

Agentic reinforcement learning research is constant algorithm modification, new estimators, new pipeline stages, new rollout schemes, and in mainstream frameworks each change threads through layers of trainer, distributed backend, and rollout glue: the cost...

Why it matters Training signal: worth scanning for reward design, experience collection, or process supervision that could transfer to theorem proving.

Skim cue Skim the search loop: proposal source, verifier call, retry strategy, and stopping rule.

Read if Save for later unless the title matches your current proof-agent work.

RL or distillation
Open PDF Semantic Scholar
18
adjacent score 1.9 2026-07-21 arXiv

Circuit Claims Depend on What Is Extracted and How It Is Compared

Yang Sheng, Jie Fu

Circuit extraction identifies a small set of model components whose presence preserves a target behavior under ablation, and the resulting circuit is often read as the mechanism behind that behavior. We argue that this reading is under-determined: preservin...

Why it matters Training signal: worth scanning for reward design, experience collection, or process supervision that could transfer to theorem proving.

Skim cue Skim the task definition, metric, and whether the benchmark has Lean-checkable artifacts.

Read if Save for later unless the title matches your current proof-agent work.

RL or distillation
Open PDF Semantic Scholar

Older but Useful

0 relevant item(s) are outside the 21-day content window. Keep them for context, but do not let them drive today's scan.

No older useful items were retained in this run.

Downweighted 70 low-priority match(es), folded for daily reading.
1
negative score 0.8 2026-07-27 GitHub

leanprover/lean4: refactor: split `registerParametricAttribute` into extension creation and registration (#14344)

Wojciech Różowski

Recent commit on leanprover/lean4.

Why it matters Toolchain signal: open only if the commit touches proof search, elaboration, tactics, Lake, or mathlib behavior you depend on.

Skim cue Skim only the changed subsystem and whether it affects your Lean workflow.

Read if Open only if you are debugging Lean or mathlib locally.

Open Semantic Scholar
2
negative score 0.8 2026-07-27 GitHub

leanprover/lean4: perf: compare `forbiddenTks` by pointer first in parser cache keys (#14562)

Sebastian Graf

Recent commit on leanprover/lean4.

Why it matters Toolchain signal: open only if the commit touches proof search, elaboration, tactics, Lake, or mathlib behavior you depend on.

Skim cue Skim only the changed subsystem and whether it affects your Lean workflow.

Read if Open only if you are debugging Lean or mathlib locally.

Open Semantic Scholar
3
negative score 0.8 2026-07-27 GitHub

leanprover/lean4: feat: support code actions in linters (#14402)

Wojciech Różowski

Recent commit on leanprover/lean4.

Why it matters Toolchain signal: open only if the commit touches proof search, elaboration, tactics, Lake, or mathlib behavior you depend on.

Skim cue Skim only the changed subsystem and whether it affects your Lean workflow.

Read if Open only if you are debugging Lean or mathlib locally.

Open Semantic Scholar
4
negative score 0.8 2026-07-27 GitHub

leanprover/lean4: feat: intrinsic verification syntax for do-notation loops and def contracts (#14389)

Sebastian Graf

Recent commit on leanprover/lean4.

Why it matters Toolchain signal: open only if the commit touches proof search, elaboration, tactics, Lake, or mathlib behavior you depend on.

Skim cue Skim only the changed subsystem and whether it affects your Lean workflow.

Read if Open only if you are debugging Lean or mathlib locally.

Open Semantic Scholar
5
negative score 0.8 2026-07-27 GitHub

leanprover/lean4: feat: display deprecated module warnings in the right positions (#14564)

Wojciech Różowski

Recent commit on leanprover/lean4.

Why it matters Toolchain signal: open only if the commit touches proof search, elaboration, tactics, Lake, or mathlib behavior you depend on.

Skim cue Skim only the changed subsystem and whether it affects your Lean workflow.

Read if Open only if you are debugging Lean or mathlib locally.

Open Semantic Scholar
6
negative score 0.8 2026-07-27 GitHub

leanprover/lean4: chore: update stage0

Lean stage0 autoupdater

Recent commit on leanprover/lean4.

Why it matters Toolchain signal: open only if the commit touches proof search, elaboration, tactics, Lake, or mathlib behavior you depend on.

Skim cue Skim only the changed subsystem and whether it affects your Lean workflow.

Read if Open only if you are debugging Lean or mathlib locally.

Open Semantic Scholar
8
negative score 0.8 2026-07-27 GitHub

leanprover-community/mathlib4: refactor: generalize `Module.Finite.of_surjective` to arbitrary ring homomorphisms (#42054)

Yi.Yuan

Recent commit on leanprover-community/mathlib4.

Why it matters Infrastructure signal: this may improve premise discovery, dependency retrieval, or library navigation for agents.

Skim cue Skim only the changed subsystem and whether it affects your Lean workflow.

Read if Open only if you are debugging Lean or mathlib locally.

Open Semantic Scholar

Source Health

Warnings are preserved so failed sources do not silently disappear from the brief.

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