{"total":16,"rows":[{"id":"2505.17813","title":"Don't Overthink it. Preferring Shorter Thinking Chains for Improved LLM Reasoning","created":"2025-05-23","cited_by_count":85,"area":"lr"},{"id":"2506.05345","title":"Inference-Time Hyper-Scaling with KV Cache Compression","created":"2025-06-05","cited_by_count":27,"area":"lr"},{"id":"2505.17941","title":"VeriThinker: Learning to Verify Makes Reasoning Model Efficient","created":"2025-05-23","cited_by_count":24,"area":"lr"},{"id":"2505.19640","title":"Interleaved Reasoning for Large Language Models via Reinforcement Learning","created":"2025-05-26","cited_by_count":21,"area":"lr"},{"id":"2505.17373","title":"Value-Guided Search for Efficient Chain-of-Thought Reasoning","created":"2025-05-23","cited_by_count":13,"area":"lr"},{"id":"2505.24273","title":"How Much Backtracking is Enough? Exploring the Interplay of SFT and RL in Enhancing LLM Reasoning","created":"2025-05-30","cited_by_count":13,"area":"lr"},{"id":"2506.20544","title":"When Life Gives You Samples: The Benefits of Scaling up Inference Compute for Multilingual LLMs","created":"2025-06-25","cited_by_count":9,"area":"lr"},{"id":"2510.01459","title":"LSPO: Length-aware Dynamic Sampling for Policy Optimization in LLM Reasoning","created":"2025-10-01","cited_by_count":9,"area":"lr"},{"id":"2506.12721","title":"Strategic Scaling of Test-Time Compute: A Bandit Learning Approach","created":"2025-06-15","cited_by_count":8,"area":"lr"},{"id":"2601.11340","title":"Neural Chain-of-Thought Search: Searching the Optimal Reasoning Path to Enhance Large Language Models","created":"2026-01-16","cited_by_count":8,"area":"lr"},{"id":"2506.16043","title":"DynScaling: Efficient Verifier-free Inference Scaling via Dynamic and Integrated Sampling","created":"2025-06-19","cited_by_count":7,"area":"lr"},{"id":"2505.22290","title":"Rethinking the Unsolvable: When In-Context Search Meets Test-Time Scaling","created":"2025-05-28","cited_by_count":2,"area":"lr"},{"id":"2505.24217","title":"Semi-structured LLM Reasoners Can Be Rigorously Audited","created":"2025-05-30","cited_by_count":2,"area":"lr"},{"id":"2604.21018","title":"Adaptive Test-Time Compute Allocation with Evolving In-Context Demonstrations","created":"2026-04-22","cited_by_count":1,"area":"lr"},{"id":"2602.01120","title":"MarkovScale: Towards Optimal Sequential Scaling at Inference Time","created":"2026-02-01","cited_by_count":0,"area":"lr"},{"id":"2607.14386","title":"CIPHER: A Decoupled Exploration-Selection Framework for Test-Time Scaling of Data Science Agents","created":"2026-07-15","cited_by_count":0,"area":"lr"}],"next_cursor":null}