Reinforcement Learning

A Safe Exploration Approach to Constrained Markov Decision Processes AISTATS 2025 ASP-Driven Emergency Planning for Norm Violations in Reinforcement Learning AAAI 2025 A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning AISTATS 2025 Best Possible Q-Learning UAI 2025 Beyond Correctness: Confidence-Aware Reward Modeling for Enhancing Large Language Model Reasoning EMNLP 2025 Beyond-Expert Performance with Limited Demonstrations: Efficient Imitation Learning with Double Exploration ICLR 2025 Boosting Policy and Process Reward Models with Monte Carlo Tree Search in Open-Domain QA ACL 2025 Breaking Barriers: A Paradigm Shift in Technology Accessibility for Individuals with Physical Disabilities AAAI 2025 Bridging Adaptivity and Safety: Learning Agile Collision-Free Locomotion Across Varied Physics L4DC 2025 Bridging Distributionally Robust Learning and Offline RL: An Approach to Mitigate Distribution Shift and Partial Data Coverage L4DC 2025 Can Reinforcement Learning Solve Asymmetric Combinatorial-Continuous Zero-Sum Games? ICLR 2025 CarPlanner: Consistent Auto-regressive Trajectory Planning for Large-Scale Reinforcement Learning in Autonomous Driving CVPR 2025 Causal Eligibility Traces for Confounding Robust Off-Policy Evaluation UAI 2025 CEAES: Bidirectional Reinforcement Learning Optimization for Consistent and Explainable Essay Assessment ACL 2025 Computationally Efficient RL under Linear Bellman Completeness for Deterministic Dynamics ICLR 2025 Computing Circuits Optimization via Model-Based Circuit Genetic Evolution ICLR 2025 Conflict-Averse Gradient Aggregation for Constrained Multi-Objective Reinforcement Learning ICLR 2025 Constraint-Conditioned Actor-Critic for Offline Safe Reinforcement Learning ICLR 2025 Convert Language Model into a Value-based Strategic Planner ACL 2025 Corruption-Robust Variance-aware Algorithms for Generalized Linear Bandits under Heavy-tailed Rewards UAI 2025 CPO: Addressing Reward Ambiguity in Role-playing Dialogue via Comparative Policy Optimization EMNLP 2025 CTD4 – a Deep Continuous Distributional Actor-Critic Agent with a Kalman Fusion of Multiple Critics AAAI 2025 Data-Driven Upper Confidence Bounds with Near-Optimal Regret for Heavy-Tailed Bandits AISTATS 2025 Deep Implicit Imitation Reinforcement Learning in Heterogeneous Action Settings AAAI 2025 DeepLTL: Learning to Efficiently Satisfy Complex LTL Specifications for Multi-Task RL ICLR 2025