{"list":"other","total":52,"rows":[{"id":"1707.06347","title":"Proximal Policy Optimization Algorithms","created":"2017-07-20","cited_by_count":15215},{"id":"2110.14168","title":"Training Verifiers to Solve Math Word Problems","created":"2021-10-27","cited_by_count":10109},{"id":"2402.03300","title":"DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models","created":"2024-02-05","cited_by_count":9379},{"id":"2505.09388","title":"Qwen3 Technical Report","created":"2025-05-14","cited_by_count":8820},{"id":"2103.03874","title":"Measuring Mathematical Problem Solving With the MATH Dataset","created":"2021-03-05","cited_by_count":5371},{"id":"2305.20050","title":"Let's Verify Step by Step","created":"2023-05-31","cited_by_count":3789},{"id":"2409.19256","title":"HybridFlow: A Flexible and Efficient RLHF Framework","created":"2024-09-28","cited_by_count":2057},{"id":"2408.03314","title":"Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters","created":"2024-08-06","cited_by_count":1986},{"id":"2310.01798","title":"Large Language Models Cannot Self-Correct Reasoning Yet","created":"2023-10-03","cited_by_count":1017},{"id":"2312.08935","title":"Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotations","created":"2023-12-14","cited_by_count":928},{"id":"2211.14275","title":"Solving math word problems with process- and outcome-based feedback","created":"2022-11-25","cited_by_count":901},{"id":"2408.15240","title":"Generative Verifiers: Reward Modeling as Next-Token Prediction","created":"2024-08-27","cited_by_count":480},{"id":"2406.06592","title":"Improve Mathematical Reasoning in Language Models by Automated Process Supervision","created":"2024-06-05","cited_by_count":441},{"id":"2306.15626","title":"LeanDojo: Theorem Proving with Retrieval-Augmented Language Models","created":"2023-06-27","cited_by_count":427},{"id":"2501.07301","title":"The Lessons of Developing Process Reward Models in Mathematical Reasoning","created":"2025-01-13","cited_by_count":415},{"id":"2109.00110","title":"MiniF2F: a cross-system benchmark for formal Olympiad-level mathematics","created":"2021-08-31","cited_by_count":391},{"id":"2412.06559","title":"ProcessBench: Identifying Process Errors in Mathematical Reasoning","created":"2024-12-09","cited_by_count":292},{"id":"2210.12283","title":"Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs","created":"2022-10-21","cited_by_count":291},{"id":"2504.21801","title":"DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decomposition","created":"2025-04-30","cited_by_count":287},{"id":"2410.08146","title":"Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning","created":"2024-10-10","cited_by_count":279},{"id":"2205.12615","title":"Autoformalization with Large Language Models","created":"2022-05-25","cited_by_count":263},{"id":"2408.08152","title":"DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search","created":"2024-08-15","cited_by_count":197},{"id":"2302.12433","title":"ProofNet: Autoformalizing and Formally Proving Undergraduate-Level Mathematics","created":"2023-02-24","cited_by_count":192},{"id":"2504.11354","title":"Kimina-Prover Preview: Towards Large Formal Reasoning Models with Reinforcement Learning","created":"2025-04-15","cited_by_count":180},{"id":"2407.11214","title":"PutnamBench: Evaluating Neural Theorem-Provers on the Putnam Mathematical Competition","created":"2024-07-15","cited_by_count":165},{"id":"2508.03613","title":"Goedel-Prover-V2: Scaling Formal Theorem Proving with Scaffolded Data Synthesis and Self-Correction","created":"2025-08-05","cited_by_count":154},{"id":"2407.00215","title":"LLM Critics Help Catch LLM Bugs","created":"2024-06-28","cited_by_count":147},{"id":"2502.07640","title":"Goedel-Prover: A Frontier Model for Open-Source Automated Theorem Proving","created":"2025-02-11","cited_by_count":133},{"id":"2406.03847","title":"Lean Workbook: A large-scale Lean problem set formalized from natural language math problems","created":"2024-06-06","cited_by_count":122},{"id":"2310.10080","title":"Let's reward step by step: Step-Level reward model as the Navigators for Reasoning","created":"2023-10-16","cited_by_count":102},{"id":"2507.23726","title":"Seed-Prover: Deep and Broad Reasoning for Automated Theorem Proving","created":"2025-07-31","cited_by_count":101},{"id":"2501.03124","title":"PRMBench: A Fine-grained and Challenging Benchmark for Process-Level Reward Models","created":"2025-01-06","cited_by_count":99},{"id":"2511.22570","title":"DeepSeekMath-V2: Towards Self-Verifiable Mathematical Reasoning","created":"2025-11-27","cited_by_count":94},{"id":"2407.13692","title":"Prover-Verifier Games improve legibility of LLM outputs","created":"2024-07-18","cited_by_count":85},{"id":"2412.16075","title":"Formal Mathematical Reasoning: A New Frontier in AI","created":"2024-12-20","cited_by_count":81},{"id":"2511.01846","title":"Towards Robust Mathematical Reasoning","created":"2025-11-03","cited_by_count":73},{"id":"2407.10040","title":"Lean-STaR: Learning to Interleave Thinking and Proving","created":"2024-07-14","cited_by_count":68},{"id":"2410.10878","title":"Herald: A Natural Language Annotated Lean 4 Dataset","created":"2024-10-09","cited_by_count":59},{"id":"2505.15034","title":"RL Tango: Reinforcing Generator and Verifier Together for Language Reasoning","created":"2025-05-21","cited_by_count":40},{"id":"2108.12099","title":"Learning to Give Checkable Answers with Prover-Verifier Games","created":"2021-08-27","cited_by_count":32},{"id":"2405.16802","title":"AutoPSV: Automated Process-Supervised Verifier","created":"2024-05-27","cited_by_count":30},{"id":"2505.23754","title":"DeepTheorem: Advancing LLM Reasoning for Theorem Proving Through Natural Language and Reinforcement Learning","created":"2025-05-29","cited_by_count":24},{"id":"2510.13744","title":"Hard2Verify: A Step-Level Verification Benchmark for Open-Ended Frontier Math","created":"2025-10-15","cited_by_count":22},{"id":"2506.04592","title":"Safe: Enhancing Mathematical Reasoning in Large Language Models via Retrospective Step-aware Formal Verification","created":"2025-06-05","cited_by_count":17},{"id":"2502.13137","title":"Theorem Prover as a Judge for Synthetic Data Generation","created":"2025-02-18","cited_by_count":14},{"id":"2511.18760","title":"HERMES: Towards Efficient and Verifiable Mathematical Reasoning in LLMs","created":"2025-11-24","cited_by_count":11},{"id":"2505.15960","title":"Efficient PRM Training Data Synthesis via Formal Verification","created":"2025-05-21","cited_by_count":8},{"id":"2606.20068","title":"Process-Verified Reinforcement Learning for Theorem Proving via Lean","created":"2026-06-18","cited_by_count":7},{"id":"2601.22642","title":"Pushing the Boundaries of Natural Reasoning: Interleaved Bonus from Formal-Logic Verification","created":"2026-01-30","cited_by_count":5},{"id":"2506.08321","title":"LeanTutor: Towards a Verified AI Mathematical Proof Tutor","created":"2025-06-10","cited_by_count":4},{"id":"2606.12594","title":"Pythagoras-Prover: Advancing Efficient Formal Proving via Augmented Lean Formalisation","created":"2026-06-10","cited_by_count":4},{"id":"2512.03244","title":"ScalePRM: Training Process Reward Models by Scaling Verification Compute Without Ground Truth","created":"2025-12-02","cited_by_count":2}],"next_cursor":null}