{"total":85,"rows":[{"id":"2408.15240","title":"Generative Verifiers: Reward Modeling as Next-Token Prediction","created":"2024-08-27","cited_by_count":480,"area":"lr"},{"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":"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":"2410.12784","title":"JudgeBench: A Benchmark for Evaluating LLM-based Judges","created":"2024-10-16","cited_by_count":318,"area":null},{"id":"2402.13116","title":"A Survey on Knowledge Distillation of Large Language Models","created":"2024-02-20","cited_by_count":284,"area":"distill"},{"id":"2503.24235","title":"A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?","created":"2025-03-31","cited_by_count":223,"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":"2406.10833","title":"A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discovery","created":"2024-06-16","cited_by_count":96,"area":null},{"id":"2410.09671","title":"OpenR: An Open Source Framework for Advanced Reasoning with Large Language Models","created":"2024-10-12","cited_by_count":94,"area":"lr"},{"id":"2410.15115","title":"On Designing Effective RL Reward at Training Time for LLM Reasoning","created":"2024-10-19","cited_by_count":87,"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":"2312.09241","title":"TinyGSM: achieving >80% on GSM8k with small language models","created":"2023-12-14","cited_by_count":70,"area":"lr"},{"id":"2502.12215","title":"Revisiting the Test-Time Scaling of o1-like Models: Do they Truly Possess Test-Time Scaling Capabilities?","created":"2025-02-17","cited_by_count":70,"area":"lr"},{"id":"2402.05808","title":"Training Large Language Models for Reasoning through Reverse Curriculum Reinforcement Learning","created":"2024-02-08","cited_by_count":65,"area":"lr"},{"id":"2507.12508","title":"MindJourney: Test-Time Scaling with World Models for Spatial Reasoning","created":"2025-07-16","cited_by_count":50,"area":"wm"},{"id":"2407.13301","title":"CoD, Towards an Interpretable Medical Agent using Chain of Diagnosis","created":"2024-07-18","cited_by_count":43,"area":null},{"id":"2406.14024","title":"LLM Critics Help Catch Bugs in Mathematics: Towards a Better Mathematical Verifier with Natural Language Feedback","created":"2024-06-20","cited_by_count":41,"area":"lr"},{"id":"2412.15797","title":"Ensembling Large Language Models with Process Reward-Guided Tree Search for Better Complex Reasoning","created":"2024-12-20","cited_by_count":40,"area":"lr"},{"id":"2505.21496","title":"UI-Genie: A Self-Improving Approach for Iteratively Boosting MLLM-based Mobile GUI Agents","created":"2025-05-27","cited_by_count":34,"area":"agents"},{"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":"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":"2406.05673","title":"Flow of Reasoning: Training LLMs for Divergent Reasoning with Minimal Examples","created":"2024-06-09","cited_by_count":30,"area":"lr"},{"id":"2505.09561","title":"Learning Long-Context Diffusion Policies via Past-Token Prediction","created":"2025-05-14","cited_by_count":30,"area":"diffusion"},{"id":"2502.01633","title":"Adversarial Reasoning at Jailbreaking Time","created":"2025-02-03","cited_by_count":29,"area":"lr"},{"id":"2502.11775","title":"video-SALMONN-o1: Reasoning-enhanced Audio-visual Large Language Model","created":"2025-02-17","cited_by_count":24,"area":"lr"},{"id":"2503.16024","title":"The Lighthouse of Language: Enhancing LLM Agents via Critique-Guided Improvement","created":"2025-03-20","cited_by_count":20,"area":"lr"},{"id":"2505.11595","title":"Stepwise Guided Policy Optimization: Coloring your Incorrect Reasoning in GRPO","created":"2025-05-16","cited_by_count":19,"area":"lr"},{"id":"2403.19346","title":"Large Language Models Struggle with Unreasonability in Math Problems","created":"2024-03-28","cited_by_count":18,"area":"lr"},{"id":"2409.02795","title":"Towards a Unified View of Preference Learning for Large Language Models: A Survey","created":"2024-09-04","cited_by_count":17,"area":"alignment"},{"id":"2502.13550","title":"STaR-SQL: Self-Taught Reasoner for Text-to-SQL","created":"2025-02-19","cited_by_count":17,"area":"lr"},{"id":"2411.11504","title":"Search, Verify and Feedback: Towards Next Generation Post-training Paradigm of Foundation Models via Verifier Engineering","created":"2024-11-18","cited_by_count":16,"area":null},{"id":"2506.07171","title":"RULE: Reinforcement UnLEarning Achieves Forget-Retain Pareto Optimality","created":"2025-06-08","cited_by_count":16,"area":"safety"},{"id":"2508.00890","title":"AgentTTS: Large Language Model Agent for Test-time Compute-optimal Scaling Strategy in Complex Tasks","created":"2025-07-26","cited_by_count":16,"area":"lr"},{"id":"2512.02304","title":"When Does Verification Pay Off? A Closer Look at LLMs as Solution Verifiers","created":"2025-12-02","cited_by_count":15,"area":null},{"id":"2502.14356","title":"Full-Step-DPO: Self-Supervised Preference Optimization with Step-wise Rewards for Mathematical Reasoning","created":"2025-02-20","cited_by_count":14,"area":"lr"},{"id":"2505.02686","title":"Sailing by the Stars: A Survey on Reward Models and Learning Strategies for Learning from Rewards","created":"2025-05-05","cited_by_count":14,"area":"lr"},{"id":"2508.14313","title":"AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning","created":"2025-08-19","cited_by_count":14,"area":"lr"},{"id":"2509.26578","title":"Linking Process to Outcome: Conditional Reward Modeling for LLM Reasoning","created":"2025-09-30","cited_by_count":14,"area":"lr"},{"id":"2505.11227","title":"Is PRM Necessary? Problem-Solving RL Implicitly Induces PRM Capability in LLMs","created":"2025-05-16","cited_by_count":13,"area":"lr"},{"id":"2503.04618","title":"Better Process Supervision with Bi-directional Rewarding Signals","created":"2025-03-06","cited_by_count":12,"area":"lr"},{"id":"2507.03483","title":"BMMR: A Large-Scale Bilingual Multimodal Multi-Discipline Reasoning Dataset","created":"2025-07-04","cited_by_count":12,"area":"lr"},{"id":"2506.03570","title":"FreePRM: Training Process Reward Models Without Ground Truth Process Labels","created":"2025-06-04","cited_by_count":11,"area":"lr"},{"id":"2509.25361","title":"Structural Reward Model: Enhancing Interpretability, Efficiency, and Scalability in Reward Modeling","created":"2025-09-29","cited_by_count":11,"area":"alignment"},{"id":"2503.00845","title":"Rewarding Graph Reasoning Process makes LLMs more Generalized Reasoners","created":"2025-03-02","cited_by_count":10,"area":"lr"},{"id":"2505.13652","title":"Guided Search Strategies in Non-Serializable Environments with Applications to Software Engineering Agents","created":"2025-05-19","cited_by_count":10,"area":"lr"},{"id":"2510.01544","title":"Advancing Reasoning in Diffusion Language Models with Denoising Process Rewards","created":"2025-10-02","cited_by_count":10,"area":"lr"},{"id":"2503.18665","title":"Boosting Virtual Agent Learning and Reasoning: A Step-Wise, Multi-Dimensional, and Generalist Reward Model with Benchmark","created":"2025-03-24","cited_by_count":9,"area":"alignment"},{"id":"2503.23219","title":"Aurelia: Test-time Reasoning Distillation in Audio-Visual LLMs","created":"2025-03-29","cited_by_count":9,"area":"lr"},{"id":"2509.13761","title":"THOR: Tool-Integrated Hierarchical Optimization via RL for Mathematical Reasoning","created":"2025-09-17","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":"2403.02799","title":"DPPA: Pruning Method for Large Language Model to Model Merging","created":"2024-03-05","cited_by_count":7,"area":null},{"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":"2502.14619","title":"Reward Models Identify Consistency, Not Causality","created":"2025-02-20","cited_by_count":6,"area":"alignment"},{"id":"2504.19898","title":"GenCLS++: Pushing the Boundaries of Generative Classification in LLMs Through Comprehensive SFT and RL Studies Across Diverse Datasets","created":"2025-04-28","cited_by_count":6,"area":null},{"id":"2508.05613","title":"Cooper: Co-Optimizing Policy and Reward Models in Reinforcement Learning for Large Language Models","created":"2025-08-07","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":"2606.26080","title":"Neglected Free Lunch from Post-training: Progress Advantage for LLM Agents","created":"2026-06-24","cited_by_count":6,"area":"lr"},{"id":"2412.12583","title":"Process-Supervised Reward Models for Verifying Clinical Note Generation: A Scalable Approach Guided by Domain Expertise","created":"2024-12-17","cited_by_count":5,"area":"alignment"},{"id":"2506.15498","title":"SPARE: Single-Pass Annotation with Reference-Guided Evaluation for Automatic Process Supervision and Reward Modelling","created":"2025-06-18","cited_by_count":4,"area":"lr"},{"id":"2509.24678","title":"Reference-Free Rating of LLM Responses via Latent Information","created":"2025-09-29","cited_by_count":4,"area":null},{"id":"2510.13170","title":"Putting on the Thinking Hats: A Survey on Chain of Thought Fine-tuning from the Perspective of Human Reasoning Mechanism","created":"2025-10-15","cited_by_count":4,"area":"lr"},{"id":"2602.14868","title":"Goldilocks RL: Tuning Task Difficulty to Escape Sparse Rewards for Reasoning","created":"2026-02-16","cited_by_count":4,"area":"lr"},{"id":"2402.11430","title":"EventRL: Enhancing Event Extraction with Outcome Supervision for Large Language Models","created":"2024-02-18","cited_by_count":3,"area":null},{"id":"2403.00800","title":"Brain-Inspired Two-Stage Approach: Enhancing Mathematical Reasoning by Imitating Human Thought Processes","created":"2024-02-23","cited_by_count":3,"area":"lr"},{"id":"2511.22888","title":"Adversarial Training for Process Reward Models","created":"2025-11-28","cited_by_count":3,"area":"lr"},{"id":"2604.16335","title":"Beyond Verifiable Rewards: Rubric-Based GRM for Reinforced Fine-Tuning SWE Agents","created":"2026-03-13","cited_by_count":3,"area":"agents"},{"id":"2604.27955","title":"GUI Agents with Reinforcement Learning: Toward Digital Inhabitants","created":"2026-04-30","cited_by_count":3,"area":"agents"},{"id":"2605.12620","title":"Think Twice, Act Once: Verifier-Guided Action Selection For Embodied Agents","created":"2026-05-12","cited_by_count":3,"area":"lr"},{"id":"2502.11155","title":"Robust Search with Uncertainty-Aware Value Models for Language Model Reasoning","created":"2025-02-16","cited_by_count":2,"area":"lr"},{"id":"2511.00521","title":"Reasoning Planning for Language Models","created":"2025-11-01","cited_by_count":2,"area":"lr"},{"id":"2604.23333","title":"Process Supervision of Confidence Margin for Calibrated LLM Reasoning","created":"2026-04-25","cited_by_count":2,"area":"lr"},{"id":"2412.12609","title":"MultiLingPoT: Enhancing Mathematical Reasoning with Multilingual Program Fine-tuning","created":"2024-12-17","cited_by_count":1,"area":"lr"},{"id":"2505.15444","title":"Single LLM, Multiple Roles: A Unified Retrieval-Augmented Generation Framework Using Role-Specific Token Optimization","created":"2025-05-21","cited_by_count":1,"area":"rag"},{"id":"2508.18212","title":"Better Language Model-Based Judging Reward Modeling through Scaling Comprehension Boundaries","created":"2025-08-25","cited_by_count":1,"area":"alignment"},{"id":"2509.23196","title":"From Harm to Help: Turning Reasoning In-Context Demos into Assets for Reasoning LMs","created":"2025-09-27","cited_by_count":1,"area":"lr"},{"id":"2603.01025","title":"One-Token Verification for Reasoning Correctness Estimation","created":"2026-03-01","cited_by_count":1,"area":"lr"},{"id":"2604.14258","title":"GFT: From Imitation to Reward Fine-Tuning with Unbiased Group Advantages and Dynamic Coefficient Rectification","created":"2026-04-15","cited_by_count":1,"area":null},{"id":"2605.24140","title":"HyperGuide: Hyperbolic Guidance for Efficient Multi-Step Reasoning in Large Language Models","created":"2026-05-22","cited_by_count":1,"area":"lr"},{"id":"2510.25310","title":"Parrot: A Training Pipeline Enhances Both Program CoT and Natural Language CoT for Reasoning","created":"2025-10-29","cited_by_count":0,"area":"lr"},{"id":"2602.05353","title":"AgentXRay: White-Boxing Agentic Systems via Workflow Reconstruction","created":"2026-02-05","cited_by_count":0,"area":"agents"},{"id":"2603.17815","title":"Process Supervision for Chain-of-Thought Reasoning via Monte Carlo Net Information Gain","created":"2026-03-18","cited_by_count":0,"area":"lr"},{"id":"2605.15529","title":"Process Rewards with Learned Reliability","created":"2026-05-15","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":"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"},{"id":"2609.39220","title":"Learning Process Rewards via Reasoning State Propagation","created":"2026-09-30","cited_by_count":0,"area":"lr"}],"next_cursor":null}