{"total":58,"rows":[{"id":"2504.12501","title":"Reinforcement Learning from Human Feedback","created":"2025-04-16","cited_by_count":58,"area":"alignment"},{"id":"2506.07468","title":"Chasing Moving Targets with Online Self-Play Reinforcement Learning for Safer Language Models","created":"2025-06-09","cited_by_count":39,"area":"alignment"},{"id":"2504.19599","title":"GVPO: Group Variance Policy Optimization for Large Language Model Post-Training","created":"2025-04-28","cited_by_count":32,"area":"alignment"},{"id":"2601.03555","title":"SCRIBE: Structured Mid-Level Supervision for Tool-Using Language Models","created":"2026-01-07","cited_by_count":21,"area":"alignment"},{"id":"2505.11080","title":"BLEUBERI: BLEU is a surprisingly effective reward for instruction following","created":"2025-05-16","cited_by_count":17,"area":"alignment"},{"id":"2605.09959","title":"G-Zero: Self-Play for Open-Ended Generation from Zero Data","created":"2026-05-11","cited_by_count":17,"area":"alignment"},{"id":"2511.16955","title":"Neighbor GRPO: Contrastive ODE Policy Optimization Aligns Flow Models","created":"2025-11-21","cited_by_count":16,"area":"alignment"},{"id":"2507.19672","title":"Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges","created":"2025-07-25","cited_by_count":15,"area":"alignment"},{"id":"2510.01555","title":"Rethinking KL Regularization in RLHF: From Value Estimation to Gradient Optimization","created":"2025-10-02","cited_by_count":14,"area":"alignment"},{"id":"2506.01183","title":"Doubly Robust Alignment for Large Language Models","created":"2025-06-01","cited_by_count":12,"area":"alignment"},{"id":"2511.20256","title":"The Image as Its Own Reward: Reinforcement Learning with Adversarial Reward for Image Generation","created":"2025-11-25","cited_by_count":12,"area":"alignment"},{"id":"2506.15068","title":"Semantically-Aware Rewards for Open-Ended R1 Training in Free-Form Generation","created":"2025-06-18","cited_by_count":11,"area":"alignment"},{"id":"2506.10054","title":"Uni-DPO: A Unified Paradigm for Dynamic Preference Optimization of LLMs","created":"2025-06-11","cited_by_count":9,"area":"alignment"},{"id":"2509.15110","title":"TDRM: Smooth Reward Models with Temporal Difference for LLM RL and Inference","created":"2025-09-18","cited_by_count":8,"area":"alignment"},{"id":"2512.20806","title":"Safety Alignment of LMs via Non-cooperative Games","created":"2025-12-23","cited_by_count":8,"area":"alignment"},{"id":"2602.18037","title":"Gradient Regularization Mitigates Reward Hacking in Reinforcement Learning from Human Feedback and Verifiable Rewards","created":"2026-02-20","cited_by_count":8,"area":"alignment"},{"id":"2601.07182","title":"PRPO: Aligning Process Reward with Outcome Reward in Policy Optimization","created":"2026-01-12","cited_by_count":7,"area":"alignment"},{"id":"2601.18533","title":"From Verifiable Dot to Reward Chain: Harnessing Verifiable Reference-based Rewards for Reinforcement Learning of Open-ended Generation","created":"2026-01-26","cited_by_count":6,"area":"alignment"},{"id":"2601.03525","title":"Beyond Binary: Turning Partial Success into Dense Verifiable Rewards for Reinforcement Learning in Code Generation","created":"2026-01-07","cited_by_count":5,"area":"alignment"},{"id":"2508.18569","title":"The Mind's Eye: A Multi-Faceted Reward Framework for Guiding Visual Metaphor Generation","created":"2025-08-26","cited_by_count":4,"area":"alignment"},{"id":"2602.14012","title":"From SFT to RL: Demystifying the Post-Training Pipeline for LLM-based Vulnerability Detection","created":"2026-02-15","cited_by_count":4,"area":"alignment"},{"id":"2604.02507","title":"Reinforcement Learning from Human Feedback: A Statistical Perspective","created":"2026-04-02","cited_by_count":4,"area":"alignment"},{"id":"2606.32032","title":"Reinforcement Learning with Metacognitive Feedback Elicits Faithful Uncertainty Expression in LLMs","created":"2026-06-30","cited_by_count":4,"area":"alignment"},{"id":"2509.26601","title":"MENLO: From Preferences to Proficiency -- Evaluating and Modeling Native-like Quality Across 47 Languages","created":"2025-09-30","cited_by_count":3,"area":"alignment"},{"id":"2511.17879","title":"Generative Adversarial Post-Training Mitigates Reward Hacking in Live Human-AI Music Interaction","created":"2025-11-22","cited_by_count":3,"area":"alignment"},{"id":"2601.22801","title":"Clipping-Free Policy Optimization for Large Language Models","created":"2026-01-30","cited_by_count":3,"area":"alignment"},{"id":"2602.08813","title":"Robust Policy Optimization to Prevent Catastrophic Forgetting","created":"2026-02-09","cited_by_count":3,"area":"alignment"},{"id":"2606.07705","title":"SAW: Stage-Aware Dynamic Weighting for Multi-Objective Reinforcement Learning in Large Language Models","created":"2026-06-05","cited_by_count":3,"area":"alignment"},{"id":"2507.17107","title":"Reinforcement Learning Fine-Tunes a Sparse Subnetwork in Large Language Models","created":"2025-07-23","cited_by_count":2,"area":"alignment"},{"id":"2511.09864","title":"Uncertainty-Guided Checkpoint Selection for Reinforcement Finetuning of Large Language Models","created":"2025-11-13","cited_by_count":2,"area":"alignment"},{"id":"2601.04411","title":"Rate or Fate? RLV$^\\varepsilon$R: Reinforcement Learning with Verifiable Noisy Rewards","created":"2026-01-07","cited_by_count":1,"area":"alignment"},{"id":"2601.20585","title":"Ranking-aware Reinforcement Learning for Ordinal Ranking","created":"2026-01-28","cited_by_count":1,"area":"alignment"},{"id":"2602.07333","title":"High Fidelity Textual User Representation over Heterogeneous Sources via Reinforcement Learning","created":"2026-02-07","cited_by_count":1,"area":"alignment"},{"id":"2604.02986","title":"Mitigating Reward Hacking in RLHF via Advantage Sign Robustness","created":"2026-04-03","cited_by_count":1,"area":"alignment"},{"id":"2605.29275","title":"Prompt-Level Reward Specifications for Open-Ended Post-Training","created":"2026-05-28","cited_by_count":1,"area":"alignment"},{"id":"2509.01720","title":"Succeed or Learn Slowly: Sample Efficient Off-Policy Reinforcement Learning for Mobile App Control","created":"2025-09-01","cited_by_count":0,"area":"alignment"},{"id":"2602.00857","title":"Unifying Adversarial Robustness and Training Across Text Scoring Models","created":"2026-01-31","cited_by_count":0,"area":"alignment"},{"id":"2602.06239","title":"Provably avoiding over-optimization in Direct Preference Optimization without knowing the data distribution","created":"2026-02-05","cited_by_count":0,"area":"alignment"},{"id":"2602.08600","title":"Beyond Scalar Scores: Reinforcement Learning for Error-Aware Quality Estimation of Machine Translation","created":"2026-02-09","cited_by_count":0,"area":"alignment"},{"id":"2603.04974","title":"VRM: Teaching Reward Models to Understand Authentic Human Preferences","created":"2026-03-05","cited_by_count":0,"area":"alignment"},{"id":"2606.10528","title":"Representation-Aware Advantage Estimation: Your Reward Model Provides More Than A Scalar Output","created":"2026-06-09","cited_by_count":0,"area":"alignment"},{"id":"2606.27291","title":"Designing Reward Signals for Portable Query Generation: A Case Study in Industrial Semantic Job Search","created":"2026-06-25","cited_by_count":0,"area":"alignment"},{"id":"2607.13430","title":"Exploring Post-Training Alignment of Small Language Models for Biomedical Data-to-Text Generation: A Case Study of Medication Leaflet","created":"2026-07-15","cited_by_count":0,"area":"alignment"},{"id":"2607.25970","title":"Reinforcement Learning for Code Optimization","created":"2026-07-28","cited_by_count":0,"area":"alignment"},{"id":"2609.02170","title":"DMRL: Document-Mediated Reinforcement Learning for Skill Optimization in Advertising Recommendation","created":"2026-09-02","cited_by_count":0,"area":"alignment"},{"id":"2609.04824","title":"Generating Constructive Feedback on Stories via Reinforcement Learning","created":"2026-09-04","cited_by_count":0,"area":"alignment"},{"id":"2609.12607","title":"Direct Preference Density Alignment for Conversational Audio Equalization","created":"2026-09-11","cited_by_count":0,"area":"alignment"},{"id":"2609.14648","title":"Optimizing Sparse Outcomes Through Dense Behavioral Signals via Value-Guided Preference Distillation","created":"2026-09-13","cited_by_count":0,"area":"alignment"},{"id":"2609.23665","title":"Which Constraints Are Missing? Ask the Verifier: Graded Rewards for Constraint-Following Music Generation","created":"2026-09-20","cited_by_count":0,"area":"alignment"},{"id":"2609.29421","title":"Rufus-Air: An Open LLM Post-Training Recipe","created":"2026-09-24","cited_by_count":0,"area":"alignment"},{"id":"2609.34374","title":"ABC-Align: Prediction-Powered Alignment with Adaptive Bias Control","created":"2026-09-28","cited_by_count":0,"area":"alignment"},{"id":"2609.34718","title":"Quality Determines Direction, Length Shapes Magnitude: Length Control for Open-Ended Reinforcement Learning","created":"2026-09-28","cited_by_count":0,"area":"alignment"},{"id":"2609.34929","title":"Sample What You Say: Aligning Language Models to Sample the Distributions They State","created":"2026-09-28","cited_by_count":0,"area":"alignment"},{"id":"2609.36652","title":"RankBuffer: Efficient Ranking-Based Rewards for Open-Ended Generation","created":"2026-09-29","cited_by_count":0,"area":"alignment"},{"id":"2610.02824","title":"MetaRubric: Learning to Reward for Rubric-Based Reinforcement Learning","created":"2026-10-02","cited_by_count":0,"area":"alignment"},{"id":"2610.03185","title":"Gains and Collapse in On-Policy Distillation:A Reinforcement Learning Perspective","created":"2026-10-02","cited_by_count":0,"area":"alignment"},{"id":"2610.17733","title":"CoCA: Criterion-Aware Credit Assignment for Rubric-Based Reinforcement Learning","created":"2026-10-13","cited_by_count":0,"area":"alignment"},{"id":"2610.18415","title":"Do Factuality Methods Make LLMs More Factual? Reproducibility and Fair Comparison","created":"2026-10-13","cited_by_count":0,"area":"alignment"}],"next_cursor":null}