Reinforcement Learning

ABLE: Personalized Disability Support with Politeness and Empathy Integration EMNLP 2024 Abstract Reward Processes: Leveraging State Abstraction for Consistent Off-Policy Evaluation NeurIPS 2024 A/B Testing and Best-arm Identification for Linear Bandits with Robustness to Non-stationarity AISTATS 2024 ACAMDA: Improving Data Efficiency in Reinforcement Learning through Guided Counterfactual Data Augmentation AAAI 2024 Achieving Õ(1/ε) Sample Complexity for Constrained Markov Decision Process NeurIPS 2024 Achieving Stronger Generation via Simple Contrastive Tuning EMNLP 2024 Achieving Tractable Minimax Optimal Regret in Average Reward MDPs NeurIPS 2024 A Critical Evaluation of AI Feedback for Aligning Large Language Models NeurIPS 2024 ACT: Empowering Decision Transformer with Dynamic Programming via Advantage Conditioning AAAI 2024 Action Gaps and Advantages in Continuous-Time Distributional Reinforcement Learning NeurIPS 2024 Active Reinforcement Learning for Robust Building Control AAAI 2024 Adaptive Q-Aid for Conditional Supervised Learning in Offline Reinforcement Learning NeurIPS 2024 Adaptive Exploration for Data-Efficient General Value Function Evaluations NeurIPS 2024 Adaptive Important Region Selection with Reinforced Hierarchical Search for Dense Object Detection NeurIPS 2024 AdaptiveISP: Learning an Adaptive Image Signal Processor for Object Detection NeurIPS 2024 Adaptive Labeling for Efficient Out-of-distribution Model Evaluation NeurIPS 2024 Advancing Open-Domain Conversational Agents - Designing an Engaging System for Natural Multi-Turn Dialogue EACL 2024 Advancing Process Verification for Large Language Models via Tree-Based Preference Learning EMNLP 2024 Adversarial Environment Design via Regret-Guided Diffusion Models NeurIPS 2024 Adversarially Trained Weighted Actor-Critic for Safe Offline Reinforcement Learning NeurIPS 2024 A Fairness-Driven Method for Learning Human-Compatible Negotiation Strategies EMNLP 2024 A General Theoretical Paradigm to Understand Learning from Human Preferences AISTATS 2024 Agent-Pro: Learning to Evolve via Policy-Level Reflection and Optimization ACL 2024 AGR: Reinforced Causal Agent-Guided Self-explaining Rationalization ACL 2024 AI-Olympics: Exploring the Generalization of Agents through Open Competitions IJCAI 2024