{"total":26,"rows":[{"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":"2503.11701","title":"A Survey of Direct Preference Optimization","created":"2025-03-12","cited_by_count":36,"area":"alignment"},{"id":"2508.10858","title":"Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation","created":"2025-08-14","cited_by_count":21,"area":"alignment"},{"id":"2503.02832","title":"AlignDistil: Token-Level Language Model Alignment as Adaptive Policy Distillation","created":"2025-03-04","cited_by_count":17,"area":"alignment"},{"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":"2505.19653","title":"Token-Importance Guided Direct Preference Optimization","created":"2025-05-26","cited_by_count":14,"area":"alignment"},{"id":"2410.05102","title":"SparsePO: Controlling Preference Alignment of LLMs via Sparse Token Masks","created":"2024-10-07","cited_by_count":9,"area":"alignment"},{"id":"2502.18293","title":"AMPO: Active Multi-Preference Optimization for Self-play Preference Selection","created":"2025-02-25","cited_by_count":5,"area":"alignment"},{"id":"2502.12678","title":"Multi-Step Alignment as Markov Games: An Optimistic Online Gradient Descent Approach with Convergence Guarantees","created":"2025-02-18","cited_by_count":3,"area":"alignment"},{"id":"2511.06222","title":"SPA: Achieving Consensus in LLM Alignment via Self-Priority Optimization","created":"2025-11-09","cited_by_count":3,"area":"alignment"},{"id":"2601.11865","title":"CTPD: Cross Tokenizer Preference Distillation","created":"2026-01-17","cited_by_count":3,"area":"alignment"},{"id":"2511.23391","title":"Ambiguity Awareness Optimization: Towards Semantic Disambiguation for Direct Preference Optimization","created":"2025-11-28","cited_by_count":2,"area":"alignment"},{"id":"2502.05773","title":"PIPA: Preference Alignment as Prior-Informed Statistical Estimation","created":"2025-02-09","cited_by_count":1,"area":"alignment"},{"id":"2506.09457","title":"Towards Bridging the Reward-Generation Gap in Direct Alignment Algorithms","created":"2025-06-11","cited_by_count":1,"area":"alignment"},{"id":"2602.01068","title":"From Utterance to Vividity: Training Expressive Subtitle Translation LLM via Adaptive Local Preference Optimization","created":"2026-02-01","cited_by_count":1,"area":"alignment"},{"id":"2602.11902","title":"Mitigating Mismatch within Reference-based Preference Optimization","created":"2026-02-12","cited_by_count":1,"area":"alignment"},{"id":"2605.02626","title":"Gradient-Gated DPO: Stabilizing Preference Optimization in Language Models","created":"2026-05-04","cited_by_count":1,"area":"alignment"},{"id":"2509.16965","title":"Preference Distillation via Value based Reinforcement Learning","created":"2025-09-21","cited_by_count":0,"area":"alignment"},{"id":"2510.05799","title":"Data-efficient Targeted Token-level Preference Optimization for LLM-based Text-to-Speech","created":"2025-10-07","cited_by_count":0,"area":"alignment"},{"id":"2605.12288","title":"TokenRatio: Principled Token-Level Preference Optimization via Ratio Matching","created":"2026-05-12","cited_by_count":0,"area":"alignment"},{"id":"2605.21883","title":"Token-weighted Direct Preference Optimization with Attention","created":"2026-05-21","cited_by_count":0,"area":"alignment"},{"id":"2607.18304","title":"TD-DPO: Difference-Aware Preference Optimization for Mitigating Sycophancy in Clinical Autism Intervention Dialogue","created":"2026-07-17","cited_by_count":0,"area":"alignment"},{"id":"2608.09568","title":"Se-DPO: Self-Evolving Token Credit for Direct Preference Optimization","created":"2026-08-10","cited_by_count":0,"area":"alignment"},{"id":"2608.12330","title":"Reliability-Aware Sexism Detection: Combining DPO with Annotator Agreement and Token-Level Confidence Scoring","created":"2026-06-01","cited_by_count":0,"area":"alignment"},{"id":"2610.01323","title":"TRACE: Trajectory Return Attribution and Contrastive Erasure for Multi-Turn Safety","created":"2026-10-01","cited_by_count":0,"area":"alignment"},{"id":"2610.01511","title":"GAW-PO: Preference Optimization with Gradient-Aligned Token Weights","created":"2026-10-01","cited_by_count":0,"area":"alignment"}],"next_cursor":null}