preference learning

PaTaRM: Bridging Pairwise and Pointwise Signals via Preference-Aware Task-Adaptive Reward Modeling ACL 2026 P-Check: Advancing Personalized Reward Model via Learning to Generate Dynamic Checklist ACL 2026 PIRA: Preference-Oriented Instruction-Tuned Reward Models with Dual Aggregation EACL 2026 PosterReward: Unlocking Accurate Evaluation for High-Quality Graphic Design Generation CVPR 2026 Provably Efficient Multi-Objective Bandit Algorithms Under Preference-Centric Customization AAAI 2026 Provably Efficient Personalized Multi-Objective Bandits with Proactive Conversational Queries UAI 2026 RankList – a Listwise Preference Learning Framework for Predicting Subjective Preferences AAAI 2026 Reducing the Scope of Language Models AAAI 2026 Rethinking Direct Preference Optimization in Diffusion Models AAAI 2026 Socratic-Geo: Synthetic Data Generation and Cross-Modal Geometric Reasoning via Multi-Agent Interaction CVPR 2026 SoliReward: Mitigating Susceptibility to Reward Hacking and Annotation Noise in Video Generation Reward Models CVPR 2026 TEAR: Temporal-aware Automated Red-teaming for Text-to-Video Models CVPR 2026 TEMPLE: Incentivizing Temporal Understanding of Video Large Language Models via Progressive Pre-SFT Alignment AAAI 2026 Twin-T & TwintVQA: A Reliable Structure-Detail Separating VLM and a Comprehensive Benchmark for Chart and Table Tasks CVPR 2026 UCPO: A Universal Constrained Combinatorial Optimization Method via Preference Optimization AAAI 2026 Uncertainty-Aware Exploratory Direct Preference Optimization for Multimodal Large Language Models CVPR 2026 VaccineRAG: Boosting Multimodal Large Language Models’ Immunity to Harmful RAG Samples AAAI 2026 VQ-Insight: Teaching VLMs for AI-Generated Video Quality Understanding via Progressive Visual Reinforcement Learning AAAI 2026 2D-DPO: Scaling Direct Preference Optimization with 2-Dimensional Supervision NAACL 2025 3D-Properties: Identifying Challenges in DPO and Charting a Path Forward ICLR 2025 ACECODER: Acing Coder RL via Automated Test-Case Synthesis ACL 2025 A Comprehensive Survey on Learning from Rewards for Large Language Models: Reward Models and Learning Strategies EMNLP 2025 Advancing LLM Reasoning Generalists with Preference Trees ICLR 2025 Agentic Reward Modeling: Integrating Human Preferences with Verifiable Correctness Signals for Reliable Reward Systems ACL 2025 Aligning Language Models Using Follow-up Likelihood as Reward Signal AAAI 2025