{"total":28,"rows":[{"id":"2503.09567","title":"Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models","created":"2025-03-12","cited_by_count":384,"area":"lr"},{"id":"2401.08967","title":"ReFT: Reasoning with Reinforced Fine-Tuning","created":"2024-01-17","cited_by_count":239,"area":"lr"},{"id":"2402.14830","title":"Orca-Math: Unlocking the potential of SLMs in Grade School Math","created":"2024-02-16","cited_by_count":151,"area":"lr"},{"id":"2402.10176","title":"OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset","created":"2024-02-15","cited_by_count":143,"area":"lr"},{"id":"2504.07912","title":"Echo Chamber: RL Post-training Amplifies Behaviors Learned in Pretraining","created":"2025-04-10","cited_by_count":129,"area":"lr"},{"id":"2407.20311","title":"Physics of Language Models: Part 2.1, Grade-School Math and the Hidden Reasoning Process","created":"2024-07-29","cited_by_count":108,"area":"lr"},{"id":"2502.18439","title":"MAPoRL: Multi-Agent Post-Co-Training for Collaborative Large Language Models with Reinforcement Learning","created":"2025-02-25","cited_by_count":86,"area":"lr"},{"id":"2401.09003","title":"Augmenting Math Word Problems via Iterative Question Composing","created":"2024-01-17","cited_by_count":59,"area":"lr"},{"id":"2402.02658","title":"Multi-step Problem Solving Through a Verifier: An Empirical Analysis on Model-induced Process Supervision","created":"2024-02-05","cited_by_count":52,"area":"lr"},{"id":"2506.08446","title":"A Survey on Large Language Models for Mathematical Reasoning","created":"2025-06-10","cited_by_count":52,"area":"lr"},{"id":"2408.16293","title":"Physics of Language Models: Part 2.2, How to Learn From Mistakes on Grade-School Math Problems","created":"2024-08-29","cited_by_count":50,"area":"lr"},{"id":"2503.18866","title":"Reasoning to Learn from Latent Thoughts","created":"2025-03-24","cited_by_count":45,"area":"lr"},{"id":"2402.01620","title":"MAGDi: Structured Distillation of Multi-Agent Interaction Graphs Improves Reasoning in Smaller Language Models","created":"2024-02-02","cited_by_count":43,"area":"lr"},{"id":"2404.10346","title":"Self-Explore: Enhancing Mathematical Reasoning in Language Models with Fine-grained Rewards","created":"2024-04-16","cited_by_count":31,"area":"lr"},{"id":"2404.14963","title":"Achieving >97% on GSM8K: Deeply Understanding the Problems Makes LLMs Better Solvers for Math Word Problems","created":"2024-04-23","cited_by_count":31,"area":"lr"},{"id":"2403.02178","title":"Masked Thought: Simply Masking Partial Reasoning Steps Can Improve Mathematical Reasoning Learning of Language Models","created":"2024-03-04","cited_by_count":20,"area":"lr"},{"id":"2412.10673","title":"Proposing and solving olympiad geometry with guided tree search","created":"2024-12-14","cited_by_count":19,"area":"lr"},{"id":"2404.14604","title":"Describe-then-Reason: Improving Multimodal Mathematical Reasoning through Visual Comprehension Training","created":"2024-04-22","cited_by_count":17,"area":"lr"},{"id":"2510.04265","title":"Don't Pass@k: A Bayesian Framework for Large Language Model Evaluation","created":"2025-10-05","cited_by_count":15,"area":"lr"},{"id":"2410.10735","title":"Embedding Self-Correction as an Inherent Ability in Large Language Models for Enhanced Mathematical Reasoning","created":"2024-10-14","cited_by_count":13,"area":"lr"},{"id":"2412.16964","title":"System-2 Mathematical Reasoning via Enriched Instruction Tuning","created":"2024-12-22","cited_by_count":7,"area":"lr"},{"id":"2408.15565","title":"SIaM: Self-Improving Code-Assisted Mathematical Reasoning of Large Language Models","created":"2024-08-28","cited_by_count":6,"area":"lr"},{"id":"2408.04226","title":"Mathfish: Evaluating Language Model Math Reasoning via Grounding in Educational Curricula","created":"2024-08-08","cited_by_count":5,"area":"lr"},{"id":"2602.08167","title":"Self-Supervised Bootstrapping of Action-Predictive Embodied Reasoning","created":"2026-02-09","cited_by_count":3,"area":"lr"},{"id":"2609.15903","title":"Discrete Beckmann Transport Models for One-Step Language Modeling and Reasoning","created":"2026-09-14","cited_by_count":3,"area":"lr"},{"id":"2412.04291","title":"Evolutionary Pre-Prompt Optimization for Mathematical Reasoning","created":"2024-12-05","cited_by_count":2,"area":"lr"},{"id":"2606.00683","title":"OCC-RAG: Optimal Cognitive Core for Faithful Question Answering","created":"2026-05-30","cited_by_count":0,"area":"lr"},{"id":"2609.25643","title":"Ladders of Thought: A Self-Evolving Curriculum of Progressively Simplified Reasoning Traces","created":"2026-09-22","cited_by_count":0,"area":"lr"}],"next_cursor":null}