{"total":34,"rows":[{"id":"2406.06592","title":"Improve Mathematical Reasoning in Language Models by Automated Process Supervision","created":"2024-06-05","cited_by_count":441,"area":"lr"},{"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":"2502.17419","title":"From System 1 to System 2: A Survey of Reasoning Large Language Models","created":"2025-02-24","cited_by_count":320,"area":"lr"},{"id":"2501.04519","title":"rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking","created":"2025-01-08","cited_by_count":313,"area":"lr"},{"id":"2408.06195","title":"Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solvers","created":"2024-08-12","cited_by_count":138,"area":"lr"},{"id":"2502.06703","title":"Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling","created":"2025-02-10","cited_by_count":136,"area":"lr"},{"id":"2501.19324","title":"Reward-Guided Speculative Decoding for Efficient LLM Reasoning","created":"2025-01-31","cited_by_count":106,"area":"lr"},{"id":"2410.02884","title":"LLaMA-Berry: Pairwise Optimization for O1-like Olympiad-Level Mathematical Reasoning","created":"2024-10-03","cited_by_count":91,"area":"lr"},{"id":"2406.10858","title":"Step-level Value Preference Optimization for Mathematical Reasoning","created":"2024-06-16","cited_by_count":72,"area":"lr"},{"id":"2501.15602","title":"Rethinking External Slow-Thinking: From Snowball Errors to Probability of Correct Reasoning","created":"2025-01-26","cited_by_count":36,"area":"lr"},{"id":"2502.15815","title":"Theoretical Physics Benchmark (TPBench) -- a Dataset and Study of AI Reasoning Capabilities in Theoretical Physics","created":"2025-02-19","cited_by_count":34,"area":"lr"},{"id":"2502.12468","title":"MCTS-Judge: Test-Time Scaling in LLM-as-a-Judge for Code Correctness Evaluation","created":"2025-02-18","cited_by_count":32,"area":"lr"},{"id":"2501.01306","title":"Think More, Hallucinate Less: Mitigating Hallucinations via Dual Process of Fast and Slow Thinking","created":"2025-01-02","cited_by_count":31,"area":"lr"},{"id":"2505.13427","title":"MM-PRM: Enhancing Multimodal Mathematical Reasoning with Scalable Step-Level Supervision","created":"2025-05-19","cited_by_count":31,"area":"lr"},{"id":"2507.02076","title":"Reasoning on a Budget: A Survey of Adaptive and Controllable Test-Time Compute in LLMs","created":"2025-07-02","cited_by_count":31,"area":"lr"},{"id":"2410.13857","title":"How Numerical Precision Affects Arithmetical Reasoning Capabilities of LLMs","created":"2024-10-17","cited_by_count":24,"area":"lr"},{"id":"2410.09302","title":"Enhancing Multi-Step Reasoning Abilities of Language Models through Direct Q-Function Optimization","created":"2024-10-11","cited_by_count":22,"area":"lr"},{"id":"2502.06773","title":"On the Emergence of Thinking in LLMs I: Searching for the Right Intuition","created":"2025-02-10","cited_by_count":22,"area":"lr"},{"id":"2505.02865","title":"Accelerating Large Language Model Reasoning via Speculative Search","created":"2025-05-03","cited_by_count":16,"area":"lr"},{"id":"2504.13828","title":"Generative AI Act II: Test Time Scaling Drives Cognition Engineering","created":"2025-04-18","cited_by_count":15,"area":"lr"},{"id":"2502.11183","title":"Don't Get Lost in the Trees: Streamlining LLM Reasoning by Overcoming Tree Search Exploration Pitfalls","created":"2025-02-16","cited_by_count":13,"area":"lr"},{"id":"2505.20196","title":"Temporal Sampling for Forgotten Reasoning in LLMs","created":"2025-05-26","cited_by_count":12,"area":"lr"},{"id":"2502.14333","title":"A Survey on Feedback-based Multi-step Reasoning for Large Language Models on Mathematics","created":"2025-02-20","cited_by_count":11,"area":"lr"},{"id":"2503.14495","title":"Temporal Consistency for LLM Reasoning Process Error Identification","created":"2025-03-18","cited_by_count":10,"area":"lr"},{"id":"2510.01925","title":"Enhancing Large Language Model Reasoning with Reward Models: An Analytical Survey","created":"2025-10-02","cited_by_count":8,"area":"lr"},{"id":"2601.00536","title":"Retrieval--Reasoning Processes for Multi-hop Question Answering: A Four-Axis Design Framework and Empirical Trends","created":"2026-01-02","cited_by_count":8,"area":"lr"},{"id":"2505.19250","title":"PATS: Process-Level Adaptive Thinking Mode Switching","created":"2025-05-25","cited_by_count":6,"area":"lr"},{"id":"2503.15944","title":"From Chaos to Order: The Atomic Reasoner Framework for Fine-grained Reasoning in Large Language Models","created":"2025-03-20","cited_by_count":5,"area":"lr"},{"id":"2507.00054","title":"Enhancing Reasoning Capabilities in SLMs with Reward Guided Dataset Distillation","created":"2025-06-25","cited_by_count":0,"area":"lr"},{"id":"2509.22572","title":"Dynamic Experts Search: Enhancing Reasoning in Mixture-of-Experts LLMs at Test Time","created":"2025-09-26","cited_by_count":0,"area":"lr"},{"id":"2605.16302","title":"Reducing Credit Assignment Variance via Counterfactual Reasoning Paths","created":"2026-04-20","cited_by_count":0,"area":"lr"},{"id":"2605.24989","title":"Selective Test-Time Compute Scaling for Click-Through Rate Prediction via Uncertainty-Triggered Feature Path Exploration","created":"2026-05-24","cited_by_count":0,"area":"lr"},{"id":"2608.05643","title":"Refining Over Resampling: Test-Time Self-Correction for LLM Reasoning","created":"2026-08-06","cited_by_count":0,"area":"lr"},{"id":"2608.30395","title":"When LLM Meets Tree Search: A Systematic View of Inference as Search in Large Language Models","created":"2026-08-31","cited_by_count":0,"area":"lr"}],"next_cursor":null}