preference learning

Teaching Your Models to Understand Code via Focal Preference Alignment EMNLP 2025 Thinking Before Running! Efficient Code Generation with Thorough Exploration and Optimal Refinement ACL 2025 Token-Level Accept or Reject: A Micro Alignment Approach for Large Language Models IJCAI 2025 Towards Reward Fairness in RLHF: From a Resource Allocation Perspective ACL 2025 Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization ICLR 2025 Towards Uncertainty Unification: A Case Study for Preference Learning RSS 2025 Transferring Textual Preferences to Vision-Language Understanding through Model Merging ACL 2025 Tuning Less, Prompting More: In-Context Preference Learning Pipeline for Natural Language Transformation EMNLP 2025 Uncertainty-Aware Iterative Preference Optimization for Enhanced LLM Reasoning ACL 2025 Understanding Reference Policies in Direct Preference Optimization NAACL 2025 UniCBE: An Uniformity-driven Comparing Based Evaluation Framework with Unified Multi-Objective Optimization ICLR 2025 Unintentional Unalignment: Likelihood Displacement in Direct Preference Optimization ICLR 2025 Verifiable by Design: Aligning Language Models to Quote from Pre-Training Data NAACL 2025 VideoComp: Advancing Fine-Grained Compositional and Temporal Alignment in Video-Text Models CVPR 2025 VisionArena: 230k Real World User-VLM Conversations with Preference Labels CVPR 2025 VLP: Vision-Language Preference Learning for Embodied Manipulation EMNLP 2025 VPO: Aligning Text-to-Video Generation Models with Prompt Optimization ICCV 2025 When Personalization Meets Reality: A Multi-Faceted Analysis of Personalized Preference Learning EMNLP 2025 World Modeling Makes a Better Planner: Dual Preference Optimization for Embodied Task Planning ACL 2025 “Yes, My LoRD.” Guiding Language Model Extraction with Locality Reinforced Distillation ACL 2025 Advancing Process Verification for Large Language Models via Tree-Based Preference Learning EMNLP 2024 Advancing Tool-Augmented Large Language Models: Integrating Insights from Errors in Inference Trees NeurIPS 2024 A General Theoretical Paradigm to Understand Learning from Human Preferences AISTATS 2024 A Graph Theoretic Approach for Preference Learning with Feature Information UAI 2024 A Grounded Preference Model for LLM Alignment ACL 2024