conftrace_

policy optimization

771 papers

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Also known as

POLO PO

Co-occurring keywords · papers mentioning both

reinforcement learning (237) markov decision process (81) offline reinforcement learning (69) large language model (56) model-based reinforcement learning (53) sample efficiency (44) deep reinforcement learning (43) safe reinforcement learning (40) continuous control (39) value function (37)

Papers

Learning with Linear Function Approximations in Mean-Field Control JMLR 2025 Leveraging Constraint Violation Signals for Action Constrained Reinforcement Learning AAAI 2025 LLMSR@XLLM25: A Language Model-Based Pipeline for Structured Reasoning Data Construction ACL 2025 MAPoRL: Multi-Agent Post-Co-Training for Collaborative Large Language Models with Reinforcement Learning ACL 2025 MDCure: A Scalable Pipeline for Multi-Document Instruction-Following ACL 2025 Mitigating Reward Over-Optimization in RLHF via Behavior-Supported Regularization ICLR 2025 Narrowing the Gap between Adversarial and Stochastic MDPs via Policy Optimization AISTATS 2025 Near-optimal Regret Using Policy Optimization in Online MDPs with Aggregate Bandit Feedback ICML 2025 Neurosymbolic World Models for Sequential Decision Making ICML 2025 Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization AAAI 2025 Offline Reinforcement Learning for LLM Multi-step Reasoning ACL 2025 Online Reinforcement Learning in Non-Stationary Context-Driven Environments ICLR 2025 OpenWebVoyager: Building Multimodal Web Agents via Iterative Real-World Exploration, Feedback and Optimization ACL 2025 Optimal Strong Regret and Violation in Constrained MDPs via Policy Optimization ICLR 2025 Optimizing Heat Alert Issuance with Reinforcement Learning AAAI 2025 Optimizing the Battery-Swapping Problem in Urban E-Bike Systems with Reinforcement Learning IJCAI 2025 Optimizing Vital Sign Monitoring in Resource-Constrained Maternal Care: An RL-Based Restless Bandit Approach AAAI 2025 ORSO: Accelerating Reward Design via Online Reward Selection and Policy Optimization ICLR 2025 Policy Optimization for CMDPs with Bandit Feedback: Learning Stochastic and Adversarial Constraints ICML 2025 Private Federated Learning using Preference-Optimized Synthetic Data ICML 2025 R1-VL: Learning to Reason with Multimodal Large Language Models via Step-wise Group Relative Policy Optimization ICCV 2025 RAISE: Reinforced Adaptive Instruction Selection For Large Language Models EMNLP 2025 RAVEN: Robust Advertisement Video Violation Temporal Grounding via Reinforcement Reasoning ACL 2025 RED: Unleashing Token-Level Rewards from Holistic Feedback via Reward Redistribution EMNLP 2025 ReFLAIR: Enhancing Multimodal Reasoning via Structured Reflection and Reward-Guided Learning EMNLP 2025