{"list":"other","total":52,"rows":[{"id":"2110.14168","title":"Training Verifiers to Solve Math Word Problems","created":"2021-10-27","cited_by_count":10109},{"id":"2107.03374","title":"Evaluating Large Language Models Trained on Code","created":"2021-07-07","cited_by_count":8320},{"id":"2203.11171","title":"Self-Consistency Improves Chain of Thought Reasoning in Language Models","created":"2022-03-21","cited_by_count":5708},{"id":"2303.11366","title":"Reflexion: Language Agents with Verbal Reinforcement Learning","created":"2023-03-20","cited_by_count":4276},{"id":"2303.17651","title":"Self-Refine: Iterative Refinement with Self-Feedback","created":"2023-03-30","cited_by_count":3442},{"id":"2305.10601","title":"Tree of Thoughts: Deliberate Problem Solving with Large Language Models","created":"2023-05-17","cited_by_count":3211},{"id":"2203.07814","title":"Competition-Level Code Generation with AlphaCode","created":"2022-02-08","cited_by_count":1462},{"id":"2407.21787","title":"Large Language Monkeys: Scaling Inference Compute with Repeated Sampling","created":"2024-07-31","cited_by_count":991},{"id":"2203.14465","title":"STaR: Bootstrapping Reasoning With Reasoning","created":"2022-03-28","cited_by_count":940},{"id":"2308.09687","title":"Graph of Thoughts: Solving Elaborate Problems with Large Language Models","created":"2023-08-18","cited_by_count":886},{"id":"1707.06887","title":"A Distributional Perspective on Reinforcement Learning","created":"2017-07-21","cited_by_count":765},{"id":"1710.10044","title":"Distributional Reinforcement Learning with Quantile Regression","created":"2017-10-27","cited_by_count":474},{"id":"2309.11495","title":"Chain-of-Verification Reduces Hallucination in Large Language Models","created":"2023-09-20","cited_by_count":324},{"id":"1812.02690","title":"Provably Efficient Maximum Entropy Exploration","created":"2018-12-06","cited_by_count":242},{"id":"2405.00451","title":"Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning","created":"2024-05-01","cited_by_count":241},{"id":"2405.14333","title":"DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data","created":"2024-05-23","cited_by_count":234},{"id":"2010.03950","title":"Reward Machines: Exploiting Reward Function Structure in Reinforcement Learning","created":"2020-10-06","cited_by_count":191},{"id":"1906.03804","title":"Model-Based Reinforcement Learning with a Generative Model is Minimax Optimal","created":"2019-06-10","cited_by_count":127},{"id":"2007.02151","title":"Variational Policy Gradient Method for Reinforcement Learning with General Utilities","created":"2020-07-04","cited_by_count":111},{"id":"2005.12900","title":"Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model","created":"2020-05-26","cited_by_count":109},{"id":"1510.08906","title":"Sample Complexity of Episodic Fixed-Horizon Reinforcement Learning","created":"2015-10-29","cited_by_count":106},{"id":"2010.03531","title":"Episodic Reinforcement Learning in Finite MDPs: Minimax Lower Bounds Revisited","created":"2020-10-07","cited_by_count":106},{"id":"1406.3339","title":"Algorithms for CVaR Optimization in MDPs","created":"2014-06-12","cited_by_count":99},{"id":"2412.15287","title":"Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models","created":"2024-12-18","cited_by_count":89},{"id":"2505.15201","title":"Pass@K Policy Optimization: Solving Harder Reinforcement Learning Problems","created":"2025-05-21","cited_by_count":87},{"id":"2106.00661","title":"Reward is enough for convex MDPs","created":"2021-06-01","cited_by_count":84},{"id":"1602.07182","title":"Explore First, Exploit Next: The True Shape of Regret in Bandit Problems","created":"2016-02-23","cited_by_count":79},{"id":"2006.13827","title":"Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in Regret","created":"2020-06-22","cited_by_count":58},{"id":"2503.19595","title":"Optimizing Language Models for Inference Time Objectives using Reinforcement Learning","created":"2025-03-25","cited_by_count":53},{"id":"1912.02552","title":"Reinforcement Learning with Non-Markovian Rewards","created":"2019-12-05","cited_by_count":45},{"id":"2509.26626","title":"Recursive Self-Aggregation Unlocks Deep Thinking in Large Language Models","created":"2025-09-30","cited_by_count":35},{"id":"2006.05879","title":"Planning in Markov Decision Processes with Gap-Dependent Sample Complexity","created":"2020-06-10","cited_by_count":34},{"id":"2302.03201","title":"Near-Minimax-Optimal Risk-Sensitive Reinforcement Learning with CVaR","created":"2023-02-07","cited_by_count":32},{"id":"2202.01511","title":"Challenging Common Assumptions in Convex Reinforcement Learning","created":"2022-02-03","cited_by_count":30},{"id":"2210.05650","title":"Regret Bounds for Risk-Sensitive Reinforcement Learning","created":"2022-10-11","cited_by_count":26},{"id":"2605.22763","title":"Advancing Mathematics Research with AI-Driven Formal Proof Search","created":"2026-05-21","cited_by_count":23},{"id":"1806.01492","title":"Near-Optimal Time and Sample Complexities for Solving Discounted Markov Decision Process with a Generative Model","created":"2018-06-05","cited_by_count":22},{"id":"2105.14016","title":"Sample-Efficient Reinforcement Learning for Linearly-Parameterized MDPs with a Generative Model","created":"2021-05-28","cited_by_count":18},{"id":"2510.23393","title":"The Best of N Worlds: Aligning Reinforcement Learning with Best-of-N Sampling via max@k Optimisation","created":"2025-10-27","cited_by_count":16},{"id":"1508.02933","title":"No Regret Bound for Extreme Bandits","created":"2015-08-12","cited_by_count":9},{"id":"2606.06468","title":"Goedel-Architect: Streamlining Formal Theorem Proving with Blueprint Generation and Refinement","created":"2026-06-04","cited_by_count":9},{"id":"1707.08820","title":"Max K-armed bandit: On the ExtremeHunter algorithm and beyond","created":"2017-07-27","cited_by_count":8},{"id":"2309.17262","title":"Estimation and Inference in Distributional Reinforcement Learning","created":"2023-09-29","cited_by_count":8},{"id":"2311.13589","title":"Risk-sensitive Markov Decision Process and Learning under General Utility Functions","created":"2023-11-22","cited_by_count":7},{"id":"2402.07598","title":"Near-Minimax-Optimal Distributional Reinforcement Learning with a Generative Model","created":"2024-02-12","cited_by_count":7},{"id":"2210.00991","title":"Policy Gradient for Reinforcement Learning with General Utilities","created":"2022-10-03","cited_by_count":6},{"id":"2605.20854","title":"Regret Analysis of Retry-Based Bandits","created":"2026-05-20","cited_by_count":4},{"id":"2606.13473","title":"MaxProof: Scaling Mathematical Proof with Generative-Verifier RL and Population-Level Test-Time Scaling","created":"2026-06-11","cited_by_count":4},{"id":"2203.10883","title":"Efficient Algorithms for Extreme Bandits","created":"2022-03-21","cited_by_count":2},{"id":"2604.24545","title":"Extreme bandits","created":"2026-04-27","cited_by_count":2},{"id":"2512.14617","title":"Model-Based Reinforcement Learning in Discrete-Action Non-Markovian Reward Decision Processes","created":"2025-12-16","cited_by_count":1},{"id":"2602.04397","title":"Optimal Rates for Feasible Payoff Set Estimation in Games","created":"2026-02-04","cited_by_count":1}],"next_cursor":null}