mlsanityData to 7 Oct 2026

FATE: A Formal Benchmark Series for Frontier Algebra of Multiple Difficulty Levels

arXiv 2511.02872 ↗First posted 4 Nov 2025cs.LG cs.AI cs.FLcited by 23

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Abstract (arXiv)

Recent advances in large language models (LLMs) have demonstrated impressive capabilities in formal theorem proving, particularly on contest-based mathematical benchmarks like the IMO. However, these contests do not reflect the depth, breadth, and abstraction of modern mathematical research. To bridge this gap, we introduce FATE (Formal Algebra Theorem Evaluation), a new benchmark series in formal algebra designed to chart a course toward advanced mathematical reasoning. We present two new components, FATE-H and FATE-X, each with 100 problems in abstract and commutative algebra. The FATE series spans a difficulty spectrum from undergraduate exercises to problems exceeding PhD qualifying exams. Notably, FATE-X is the first formal benchmark to surpass both PhD-level exam difficulty and the coverage of the Mathlib library. Our evaluations of state-of-the-art LLM provers on this new benchmark reveal a stark performance gap compared to contest math: the best model achieves only 3% (pass@64) accuracy on FATE-H and 0% on FATE-X. Our two-stage evaluation reveals that models' natural-language reasoning is notably more accurate than their ability to formalize this reasoning. We systematically classify the common errors that arise during this formalization process. Furthermore, a comparative study shows that a specialized prover can exhibit less effective reflection than general-purpose models, reducing its accuracy at the natural-language stage. We believe FATE provides a robust and challenging benchmark that establishes essential checkpoints on the path toward research-level formal mathematical reasoning.

Key facts. Cited by 23 papers in the map (data through 7 Oct 2026). Builds on 32 of its 68 references that are in the map. First posted on arXiv 4 Nov 2025.

Builds on

32 of 68 references.

References · 32

  1. 2021Training Verifiers to Solve Math Word Problemscited by 9,743
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  3. 2021Evaluating Large Language Models Trained on Codecited by 8,053
  4. 2025DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learningcited by 6,146
  5. 2021Measuring Mathematical Problem Solving With the MATH Datasetcited by 5,203
  6. 2025Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilitiescited by 3,655
  7. 2024OlympiadBench: A Challenging Benchmark for Promoting AGI with Olympiad-Level Bilingual Multimodal Scientific Problemscited by 1,099
  8. 2023LeanDojo: Theorem Proving with Retrieval-Augmented Language Modelscited by 414
  9. 2021MiniF2F: a cross-system benchmark for formal Olympiad-level mathematicscited by 380
  10. 2020Generative Language Modeling for Automated Theorem Provingcited by 379
  11. 2024Omni-MATH: A Universal Olympiad Level Mathematic Benchmark For Large Language Modelscited by 277
  12. 2025DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decompositioncited by 270
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  1. 2024FrontierMath: A Benchmark for Evaluating Advanced Mathematical Reasoning in AIcited by 227
  2. 2022HyperTree Proof Search for Neural Theorem Provingcited by 192
  3. 2024DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Searchcited by 189
  4. 2025Kimina-Prover Preview: Towards Large Formal Reasoning Models with Reinforcement Learningcited by 173
  5. 2024PutnamBench: Evaluating Neural Theorem-Provers on the Putnam Mathematical Competitioncited by 153
  6. 2025Goedel-Prover-V2: Scaling Formal Theorem Proving with Scaffolded Data Synthesis and Self-Correctioncited by 140
  7. 2025Seed-Prover: Deep and Broad Reasoning for Automated Theorem Provingcited by 96
  8. 2025BFS-Prover: Scalable Best-First Tree Search for LLM-based Automatic Theorem Provingcited by 82
  9. 2023ARB: Advanced Reasoning Benchmark for Large Language Modelscited by 60
  10. 2023FIMO: A Challenge Formal Dataset for Automated Theorem Provingcited by 54
  11. 2025FormalMATH: Benchmarking Formal Mathematical Reasoning of Large Language Modelscited by 45
  12. 2024miniCTX: Neural Theorem Proving with (Long-)Contextscited by 35
  13. 2025Solving Formal Math Problems by Decomposition and Iterative Reflectioncited by 35
  14. 2024InternLM2.5-StepProver: Advancing Automated Theorem Proving via Critic-Guided Searchcited by 34
  15. 2024HARDMath: A Benchmark Dataset for Challenging Problems in Applied Mathematicscited by 32
  16. 2024HunyuanProver: A Scalable Data Synthesis Framework and Guided Tree Search for Automated Theorem Provingcited by 32
  17. 2025RealMath: A Continuous Benchmark for Evaluating Language Models on Research-Level Mathematicscited by 30
  18. 2025CombiBench: Benchmarking LLM Capability for Combinatorial Mathematicscited by 28
  19. 2025REAL-Prover: Retrieval Augmented Lean Prover for Mathematical Reasoningcited by 18
  20. 2025A Combinatorial Identities Benchmark for Theorem Proving via Automated Theorem Generationcited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 21.

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  1. 2025Seed-Prover 1.5: Mastering Undergraduate-Level Theorem Proving via Learning from Experiencecited by 36
  2. 2026Automated Conjecture Resolution with Formal Verificationcited by 21
  3. 2026A Minimal Agent for Automated Theorem Provingcited by 13
  4. 2026M2F: Automated Formalization of Mathematical Literature at Scalecited by 12
  5. 2026LeanSearch v2: Global Premise Retrieval for Lean 4 Theorem Provingcited by 7
  6. 2026TaoBench: Do Automated Theorem Prover LLMs Generalize Beyond MathLib?cited by 5
  7. 2026Formal Conjectures: An Open and Evolving Benchmark for Verified Discovery in Mathematicscited by 5
  8. 2025LeanCat: A Benchmark Suite for Formal Category Theory in Lean (Part I: 1-Categories)cited by 4
  9. 2026SorryDB: Can AI Provers Complete Real-World Lean Theorems?cited by 4
  10. 2026Cog-DRIFT: Exploration on Adaptively Reformulated Instances Enables Learning from Hard Reasoning Problemscited by 4
  11. 2026Not All Proofs Are Equal: Evaluating LLM Proof Quality Beyond Correctnesscited by 3
  12. 2026Optimizing the Cost-Quality Tradeoff of Agentic Theorem Provers in Leancited by 3
11 more
  1. 2026Theory-Scale Auto-Formalization of Logics for Computer Sciencecited by 3
  2. 2026MathAtlas: A Benchmark for Autoformalization in the Wildcited by 2
  3. 2026TheoremForge: Scaling up Formal Data Synthesis with Low-Budget Agentic Workflowcited by 1
  4. 2026Decompose, Structure, and Repair: A Neuro-Symbolic Framework for Autoformalization via Operator Treescited by 1
  5. 2026MA-ProofBench: A Two-Tiered Evaluation of LLMs for Theorem Proving in Mathematical Analysiscited by 1
  6. 2026From Solvers to Research: Large Language Model-Driven Formal Mathematics at the Research Frontiercited by 1
  7. 2026AoA: Theorem Proving Agent over Abstract Syntax Tree of Redesigned Languagecited by 1
  8. 2026CAM-Bench: A Benchmark for Computational and Applied Mathematics in Leancited by 0
  9. 2026FVSpec: Real-World Property-Based Tests as Lean Challengescited by 0
  10. 2026Lean-GAP: A Dataset of Formalized Graduate Algebra Problemscited by 0
  11. 2026MathForm: Scaling Mathematical Autoformalization with Knowledge Retrieval and Verification-Guided Refinementcited by 0

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  7. 2025Evaluating Frontier LLMs on PhD-Level Mathematical Reasoning: A Benchmark on a Textbook in Theoretical Computer Science about Randomized Algorithms
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