{"total":148,"rows":[{"id":"2504.02495","title":"Inference-Time Scaling for Generalist Reward Modeling","created":"2025-04-03","cited_by_count":239,"area":"lr"},{"id":"2509.08827","title":"A Survey of Reinforcement Learning for Large Reasoning Models","created":"2025-09-10","cited_by_count":180,"area":"lr"},{"id":"2504.16891","title":"AIMO-2 Winning Solution: Building State-of-the-Art Mathematical Reasoning Models with OpenMathReasoning dataset","created":"2025-04-23","cited_by_count":174,"area":"lr"},{"id":"2506.01937","title":"RewardBench 2: Advancing Reward Model Evaluation","created":"2025-06-02","cited_by_count":150,"area":"alignment"},{"id":"2504.16828","title":"Process Reward Models That Think","created":"2025-04-23","cited_by_count":118,"area":"lr"},{"id":"2504.09037","title":"A Survey of Frontiers in LLM Reasoning: Inference Scaling, Learning to Reason, and Agentic Systems","created":"2025-04-12","cited_by_count":111,"area":"lr"},{"id":"2501.04682","title":"Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Thought","created":"2025-01-08","cited_by_count":109,"area":"lr"},{"id":"2504.00891","title":"GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning","created":"2025-04-01","cited_by_count":97,"area":"lr"},{"id":"2506.18254","title":"RLPR: Extrapolating RLVR to General Domains without Verifiers","created":"2025-06-23","cited_by_count":85,"area":"lr"},{"id":"2502.12118","title":"Scaling Test-Time Compute Without Verification or RL is Suboptimal","created":"2025-02-17","cited_by_count":84,"area":"lr"},{"id":"2503.09501","title":"ReMA: Learning to Meta-think for LLMs with Multi-Agent Reinforcement Learning","created":"2025-03-12","cited_by_count":79,"area":"lr"},{"id":"2505.10320","title":"J1: Incentivizing Thinking in LLM-as-a-Judge via Reinforcement Learning","created":"2025-05-15","cited_by_count":75,"area":"lr"},{"id":"2411.16646","title":"Self-Generated Critiques Boost Reward Modeling for Language Models","created":"2024-11-25","cited_by_count":71,"area":"lr"},{"id":"2502.19613","title":"Self-rewarding correction for mathematical reasoning","created":"2025-02-26","cited_by_count":70,"area":"lr"},{"id":"2502.20379","title":"Multi-Agent Verification: Scaling Test-Time Compute with Multiple Verifiers","created":"2025-02-27","cited_by_count":62,"area":"lr"},{"id":"2503.14286","title":"Tapered Off-Policy REINFORCE: Stable and efficient reinforcement learning for LLMs","created":"2025-03-18","cited_by_count":61,"area":null},{"id":"2412.20993","title":"Efficiently Scaling LLM Reasoning with Certaindex","created":"2024-12-30","cited_by_count":58,"area":"lr"},{"id":"2602.01511","title":"Alternating Reinforcement Learning for Rubric-Based Reward Modeling in Non-Verifiable LLM Post-Training","created":"2026-02-02","cited_by_count":54,"area":"alignment"},{"id":"2504.12328","title":"A Comprehensive Survey of Reward Models: Taxonomy, Applications, Challenges, and Future","created":"2025-04-12","cited_by_count":53,"area":"alignment"},{"id":"2411.04109","title":"Self-Consistency Preference Optimization","created":"2024-11-06","cited_by_count":50,"area":"lr"},{"id":"2505.14674","title":"Reward Reasoning Model","created":"2025-05-20","cited_by_count":47,"area":"lr"},{"id":"2509.19199","title":"Agentic Reinforcement Learning with Implicit Step Rewards","created":"2025-09-23","cited_by_count":47,"area":"agents"},{"id":"2504.01005","title":"When To Solve, When To Verify: Compute-Optimal Problem Solving and Generative Verification for LLM Reasoning","created":"2025-04-01","cited_by_count":42,"area":"lr"},{"id":"2507.00769","title":"LitBench: A Benchmark and Dataset for Reliable Evaluation of Creative Writing","created":"2025-07-01","cited_by_count":42,"area":"alignment"},{"id":"2505.15277","title":"Web-Shepherd: Advancing PRMs for Reinforcing Web Agents","created":"2025-05-21","cited_by_count":41,"area":"agents"},{"id":"2412.02980","title":"Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models","created":"2024-12-04","cited_by_count":35,"area":"synth"},{"id":"2509.00676","title":"LLaVA-Critic-R1: Your Critic Model is Secretly a Strong Policy Model","created":"2025-08-31","cited_by_count":35,"area":"mllm"},{"id":"2505.22453","title":"First SFT, Second RL, Third UPT: Continual Improving Multi-Modal LLM Reasoning via Unsupervised Post-Training","created":"2025-05-28","cited_by_count":34,"area":"lr"},{"id":"2506.23235","title":"Generalist Reward Models: Found Inside Large Language Models","created":"2025-06-29","cited_by_count":34,"area":"alignment"},{"id":"2505.15431","title":"Hunyuan-TurboS: Advancing Large Language Models through Mamba-Transformer Synergy and Adaptive Chain-of-Thought","created":"2025-05-21","cited_by_count":29,"area":"lr"},{"id":"2506.03637","title":"RewardAnything: Generalizable Principle-Following Reward Models","created":"2025-06-04","cited_by_count":28,"area":"alignment"},{"id":"2506.10406","title":"PAG: Multi-Turn Reinforced LLM Self-Correction with Policy as Generative Verifier","created":"2025-06-12","cited_by_count":28,"area":null},{"id":"2503.04104","title":"LLMs Can Generate a Better Answer by Aggregating Their Own Responses","created":"2025-03-06","cited_by_count":27,"area":null},{"id":"2602.14069","title":"Open Rubric System: Scaling Reinforcement Learning with Pairwise Adaptive Rubric","created":"2026-02-15","cited_by_count":27,"area":"alignment"},{"id":"2503.22230","title":"Exploring Data Scaling Trends and Effects in Reinforcement Learning from Human Feedback","created":"2025-03-28","cited_by_count":26,"area":"alignment"},{"id":"2504.10337","title":"Heimdall: test-time scaling on the generative verification","created":"2025-04-14","cited_by_count":26,"area":"lr"},{"id":"2508.02298","title":"CAPO: Towards Enhancing LLM Reasoning through Generative Credit Assignment","created":"2025-08-04","cited_by_count":26,"area":"lr"},{"id":"2506.14175","title":"GRAM: A Generative Foundation Reward Model for Reward Generalization","created":"2025-06-17","cited_by_count":25,"area":"alignment"},{"id":"2507.09075","title":"OpenCodeReasoning-II: A Simple Test Time Scaling Approach via Self-Critique","created":"2025-07-11","cited_by_count":25,"area":"lr"},{"id":"2510.13744","title":"Hard2Verify: A Step-Level Verification Benchmark for Open-Ended Frontier Math","created":"2025-10-15","cited_by_count":22,"area":"lr"},{"id":"2602.07594","title":"Learning to Self-Verify Makes Language Models Better Reasoners","created":"2026-02-07","cited_by_count":21,"area":"lr"},{"id":"2502.12501","title":"Crowd Comparative Reasoning: Unlocking Comprehensive Evaluations for LLM-as-a-Judge","created":"2025-02-18","cited_by_count":19,"area":"lr"},{"id":"2509.10704","title":"Maestro: Self-Improving Text-to-Image Generation via Agent Orchestration","created":"2025-09-12","cited_by_count":19,"area":"agents"},{"id":"2509.17995","title":"Variation in Verification: Understanding Verification Dynamics in Large Language Models","created":"2025-09-22","cited_by_count":19,"area":null},{"id":"2601.07408","title":"Outcome-Grounded Advantage Reshaping for Fine-Grained Credit Assignment in Mathematical Reasoning","created":"2026-01-12","cited_by_count":19,"area":"lr"},{"id":"2505.22338","title":"Text2Grad: Reinforcement Learning from Natural Language Feedback","created":"2025-05-28","cited_by_count":18,"area":"alignment"},{"id":"2509.22638","title":"Language Models Can Learn from Verbal Feedback Without Scalar Rewards","created":"2025-09-26","cited_by_count":18,"area":null},{"id":"2502.01619","title":"Learning to Generate Unit Tests for Automated Debugging","created":"2025-02-03","cited_by_count":17,"area":null},{"id":"2506.01369","title":"Incentivizing LLMs to Self-Verify Their Answers","created":"2025-06-02","cited_by_count":17,"area":"lr"},{"id":"2505.16265","title":"Think-RM: Enabling Long-Horizon Reasoning in Generative Reward Models","created":"2025-05-22","cited_by_count":16,"area":"lr"},{"id":"2507.17849","title":"Dynamic and Generalizable Process Reward Modeling","created":"2025-07-23","cited_by_count":16,"area":"lr"},{"id":"2505.02666","title":"A Survey on Progress in LLM Alignment from the Perspective of Reward Design","created":"2025-05-05","cited_by_count":15,"area":"alignment"},{"id":"2507.05197","title":"Pre-Trained Policy Discriminators are General Reward Models","created":"2025-07-07","cited_by_count":15,"area":"alignment"},{"id":"2505.04842","title":"Putting the Value Back in RL: Better Test-Time Scaling by Unifying LLM Reasoners With Verifiers","created":"2025-05-07","cited_by_count":14,"area":"lr"},{"id":"2509.01684","title":"Reinforcement Learning for Machine Learning Engineering Agents","created":"2025-09-01","cited_by_count":14,"area":"lr"},{"id":"2602.12268","title":"CM2: Reinforcement Learning with Checklist Rewards for Multi-Turn and Multi-Step Agentic Tool Use","created":"2026-02-12","cited_by_count":14,"area":"agents"},{"id":"2604.11626","title":"RationalRewards: Reasoning Rewards Scale Visual Generation Both Training and Test Time","created":"2026-04-13","cited_by_count":14,"area":"alignment"},{"id":"2504.04718","title":"T1: Tool-integrated Verification for Test-time Compute Scaling in Small Language Models","created":"2025-04-07","cited_by_count":13,"area":"lr"},{"id":"2505.18531","title":"Generative RLHF-V: Learning Principles from Multi-modal Human Preference","created":"2025-05-24","cited_by_count":13,"area":"mllm"},{"id":"2506.14234","title":"Xolver: Multi-Agent Reasoning with Holistic Experience Learning Just Like an Olympiad Team","created":"2025-06-17","cited_by_count":13,"area":"lr"},{"id":"2510.20369","title":"Ask a Strong LLM Judge when Your Reward Model is Uncertain","created":"2025-10-23","cited_by_count":13,"area":"alignment"},{"id":"2603.12246","title":"Examining Reasoning LLMs-as-Judges in Non-Verifiable LLM Post-Training","created":"2026-03-12","cited_by_count":13,"area":"lr"},{"id":"2501.19383","title":"Decoding-based Regression","created":"2025-01-31","cited_by_count":12,"area":null},{"id":"2509.00084","title":"Learning to Refine: Self-Refinement of Parallel Reasoning in LLMs","created":"2025-08-27","cited_by_count":12,"area":"lr"},{"id":"2510.11892","title":"R-WoM: Retrieval-augmented World Model For Computer-use Agents","created":"2025-10-13","cited_by_count":12,"area":"wm"},{"id":"2603.04304","title":"$V_1$: Unifying Generation and Self-Verification for Parallel Reasoners","created":"2026-03-04","cited_by_count":12,"area":"lr"},{"id":"2505.16142","title":"RLKD: Distilling LLMs' Reasoning via Reinforcement Learning","created":"2025-05-22","cited_by_count":11,"area":"lr"},{"id":"2507.23317","title":"Good Learners Think Their Thinking: Generative PRM Makes Large Reasoning Model More Efficient Math Learner","created":"2025-07-31","cited_by_count":11,"area":"lr"},{"id":"2601.07349","title":"Reward Modeling from Natural Language Human Feedback","created":"2026-01-12","cited_by_count":11,"area":"alignment"},{"id":"2603.14473","title":"AI Can Learn Scientific Taste","created":"2026-03-15","cited_by_count":11,"area":null},{"id":"2604.10701","title":"Bringing Value Models Back: Generative Critics for Value Modeling in LLM Reinforcement Learning","created":"2026-04-12","cited_by_count":11,"area":null},{"id":"2510.14232","title":"Scaling Test-Time Compute to Achieve IOI Gold Medal with Open-Weight Models","created":"2025-10-16","cited_by_count":10,"area":"lr"},{"id":"2505.13346","title":"J4R: Learning to Judge with Equivalent Initial State Group Relative Policy Optimization","created":"2025-05-19","cited_by_count":9,"area":"lr"},{"id":"2506.16712","title":"ReasonGRM: Enhancing Generative Reward Models through Large Reasoning Models","created":"2025-06-20","cited_by_count":9,"area":"lr"},{"id":"2503.01642","title":"Graph-Augmented Reasoning: Evolving Step-by-Step Knowledge Graph Retrieval for LLM Reasoning","created":"2025-03-03","cited_by_count":8,"area":"lr"},{"id":"2508.18255","title":"Hermes 4 Technical Report","created":"2025-08-25","cited_by_count":8,"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":"2512.00920","title":"Reward Auditor: Inference on Reward Modeling Suitability in Real-World Perturbed Scenarios","created":"2025-11-30","cited_by_count":8,"area":"alignment"},{"id":"2507.13158","title":"Inverse Reinforcement Learning Meets Large Language Model Post-Training: Basics, Advances, and Opportunities","created":"2025-07-17","cited_by_count":7,"area":"alignment"},{"id":"2507.15024","title":"RefCritic: Training Long Chain-of-Thought Critic Models with Refinement Feedback","created":"2025-07-20","cited_by_count":7,"area":"lr"},{"id":"2509.21871","title":"Unlocking the Essence of Beauty: Advanced Aesthetic Reasoning with Relative-Absolute Policy Optimization","created":"2025-09-26","cited_by_count":7,"area":"lr"},{"id":"2510.13291","title":"Higher Satisfaction, Lower Cost: A Technical Report on How LLMs Revolutionize Meituan's Intelligent Interaction Systems","created":"2025-10-15","cited_by_count":7,"area":null},{"id":"2510.22543","title":"FAPO: Flawed-Aware Policy Optimization for Efficient and Reliable Reasoning","created":"2025-10-26","cited_by_count":7,"area":"lr"},{"id":"2510.23596","title":"Think Twice: Branch-and-Rethink Reasoning Reward Model","created":"2025-10-27","cited_by_count":7,"area":"lr"},{"id":"2601.21872","title":"WebArbiter: A Principle-Guided Reasoning Process Reward Model for Web Agents","created":"2026-01-29","cited_by_count":7,"area":"lr"},{"id":"2602.09305","title":"Reward Modeling for Reinforcement Learning-Based LLM Reasoning: Design, Challenges, and Evaluation","created":"2026-02-10","cited_by_count":7,"area":"lr"},{"id":"2505.18601","title":"Flex-Judge: Text-Only Reasoning Unleashes Zero-Shot Multimodal Evaluators","created":"2025-05-24","cited_by_count":6,"area":"lr"},{"id":"2511.15137","title":"From Solving to Verifying: A Unified Objective for Robust Reasoning in LLMs","created":"2025-11-19","cited_by_count":6,"area":"lr"},{"id":"2512.01457","title":"Zero-Overhead Introspection for Adaptive Test-Time Compute","created":"2025-12-01","cited_by_count":6,"area":"lr"},{"id":"2601.17717","title":"A Survey on Evaluating Quality and Trustworthiness in LLM-Generated Data","created":"2026-01-25","cited_by_count":6,"area":"synth"},{"id":"2604.10072","title":"Reason Only When Needed: Efficient Generative Reward Modeling via Model-Internal Uncertainty","created":"2026-04-11","cited_by_count":6,"area":"lr"},{"id":"2411.14251","title":"Natural Language Reinforcement Learning","created":"2024-11-21","cited_by_count":5,"area":"lr"},{"id":"2503.04793","title":"Sentence-level Reward Model can Generalize Better for Aligning LLM from Human Preference","created":"2025-03-01","cited_by_count":5,"area":"alignment"},{"id":"2508.02618","title":"Alleviating Attention Hacking in Discriminative Reward Modeling through Interaction Distillation","created":"2025-08-04","cited_by_count":5,"area":"alignment"},{"id":"2509.22099","title":"S2J: Bridging the Gap Between Solving and Judging Ability in Generative Reward Models","created":"2025-09-26","cited_by_count":5,"area":"alignment"},{"id":"2510.17793","title":"Foundational Automatic Evaluators: Scaling Multi-Task Generative Evaluator Training for Reasoning-Centric Domains","created":"2025-10-20","cited_by_count":5,"area":null},{"id":"2603.25108","title":"MSRL: Scaling Generative Multimodal Reward Modeling via Multi-Stage Reinforcement Learning","created":"2026-03-26","cited_by_count":5,"area":"alignment"},{"id":"2605.20745","title":"The Hidden Signal of Verifier Strictness: Controlling and Improving Step-Wise Verification via Selective Latent Steering","created":"2026-05-20","cited_by_count":5,"area":null},{"id":"2605.29156","title":"RUBRIC-ARROW: Alternating Pointwise Rubric Reward Modeling for LLM Post-training in Non-verifiable Domains","created":"2026-05-27","cited_by_count":5,"area":"alignment"},{"id":"2607.06065","title":"SWE-Review: Closing the Loop on Issue Resolution with Agentic Code Review","created":"2026-07-07","cited_by_count":5,"area":"agents"}],"next_cursor":"100"}