"reinforcement learning" Papers
300 papers found • Page 5 of 6
Conference
AdaNAT: Exploring Adaptive Policy for Token-Based Image Generation
Zanlin Ni, Yulin Wang, Renping Zhou et al.
Adapt2Reward: Adapting Video-Language Models to Generalizable Robotic Rewards via Failure Prompts
Yanting Yang, Minghao Chen, Qibo Qiu et al.
A Hierarchical Adaptive Multi-Task Reinforcement Learning Framework for Multiplier Circuit Design
Zhihai Wang, Jie Wang, Dongsheng Zuo et al.
AlignSAM: Aligning Segment Anything Model to Open Context via Reinforcement Learning
Duojun Huang, Xinyu Xiong, Jie Ma et al.
A Neural-Guided Dynamic Symbolic Network for Exploring Mathematical Expressions from Data
Wenqiang Li, Weijun Li, Lina Yu et al.
An Improved Finite-time Analysis of Temporal Difference Learning with Deep Neural Networks
Zhifa Ke, Zaiwen Wen, Junyu Zhang
An Information Theoretic Approach to Interaction-Grounded Learning
Xiaoyan Hu, Farzan Farnia, Ho-fung Leung
Augmenting Decision with Hypothesis in Reinforcement Learning
Nguyen Minh Quang, Hady Lauw
Boosting Reinforcement Learning with Strongly Delayed Feedback Through Auxiliary Short Delays
Qingyuan Wu, Simon Zhan, Yixuan Wang et al.
Building Minimal and Reusable Causal State Abstractions for Reinforcement Learning
Zizhao Wang, Caroline Wang, Xuesu Xiao et al.
Code as Reward: Empowering Reinforcement Learning with VLMs
David Venuto, Mohammad Sami Nur Islam, Martin Klissarov et al.
ConsistentEE: A Consistent and Hardness-Guided Early Exiting Method for Accelerating Language Models Inference
Ziqian Zeng, Yihuai Hong, Hongliang Dai et al.
Cross-Domain Policy Adaptation by Capturing Representation Mismatch
Jiafei Lyu, Chenjia Bai, Jing-Wen Yang et al.
Dealing With Unbounded Gradients in Stochastic Saddle-point Optimization
Gergely Neu, Nneka Okolo
DGPO: Discovering Multiple Strategies with Diversity-Guided Policy Optimization
Wenze Chen, Shiyu Huang, Yuan Chiang et al.
DiffAIL: Diffusion Adversarial Imitation Learning
Bingzheng Wang, Guoqiang Wu, Teng Pang et al.
Discerning Temporal Difference Learning
Jianfei Ma
DISCRET: Synthesizing Faithful Explanations For Treatment Effect Estimation
Yinjun Wu, Mayank Keoliya, Kan Chen et al.
Dynamic Knowledge Injection for AIXI Agents
Samuel Yang-Zhao, Kee Siong Ng, Marcus Hutter
Efficient Policy Evaluation with Offline Data Informed Behavior Policy Design
Shuze Liu, Shangtong Zhang
Efficient World Models with Context-Aware Tokenization
Vincent Micheli, Eloi Alonso, François Fleuret
EfficientZero V2: Mastering Discrete and Continuous Control with Limited Data
Shengjie Wang, Shaohuai Liu, Weirui Ye et al.
Episodic Return Decomposition by Difference of Implicitly Assigned Sub-trajectory Reward
Haoxin Lin, Hongqiu Wu, Jiaji Zhang et al.
EvoRainbow: Combining Improvements in Evolutionary Reinforcement Learning for Policy Search
Pengyi Li, Yan Zheng, Hongyao Tang et al.
Explore 3D Dance Generation via Reward Model from Automatically-Ranked Demonstrations
Zilin Wang, Haolin Zhuang, Lu Li et al.
Fair Resource Allocation in Multi-Task Learning
Hao Ban, Kaiyi Ji
Feedback Efficient Online Fine-Tuning of Diffusion Models
Masatoshi Uehara, Yulai Zhao, Kevin Black et al.
Fine-tuning Reinforcement Learning Models is Secretly a Forgetting Mitigation Problem
Maciej Wołczyk, Bartłomiej Cupiał, Mateusz Ostaszewski et al.
Finite Time Logarithmic Regret Bounds for Self-Tuning Regulation
Rahul Singh, Akshay Mete, Avik Kar et al.
Fourier Controller Networks for Real-Time Decision-Making in Embodied Learning
Hengkai Tan, LIU SONGMING, Kai Ma et al.
FuRL: Visual-Language Models as Fuzzy Rewards for Reinforcement Learning
Yuwei Fu, Haichao Zhang, di wu et al.
Hieros: Hierarchical Imagination on Structured State Space Sequence World Models
Paul Mattes, Rainer Schlosser, Ralf Herbrich
Implicit Bias of Policy Gradient in Linear Quadratic Control: Extrapolation to Unseen Initial States
Noam Razin, Yotam Alexander, Edo Cohen-Karlik et al.
Improving Token-Based World Models with Parallel Observation Prediction
Lior Cohen, Kaixin Wang, Bingyi Kang et al.
Iterative Regularized Policy Optimization with Imperfect Demonstrations
Xudong Gong, Feng Dawei, Kele Xu et al.
Knowledge-aware Reinforced Language Models for Protein Directed Evolution
Yuhao Wang, Qiang Zhang, Ming Qin et al.
Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game
Zelai Xu, Chao Yu, Fei Fang et al.
Large-scale Reinforcement Learning for Diffusion Models
Yinan Zhang, Eric Tzeng, Yilun Du et al.
Learning Causal Dynamics Models in Object-Oriented Environments
Zhongwei Yu, Jingqing Ruan, Dengpeng Xing
Learning Diverse Risk Preferences in Population-Based Self-Play
Yuhua Jiang, Qihan Liu, Xiaoteng Ma et al.
Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making
Vivek Myers, Chongyi Zheng, Anca Dragan et al.
Learning the Target Network in Function Space
Kavosh Asadi, Yao Liu, Shoham Sabach et al.
Learning to Stabilize Online Reinforcement Learning in Unbounded State Spaces
Brahma Pavse, Matthew Zurek, Yudong Chen et al.
Learning Uncertainty-Aware Temporally-Extended Actions
Joongkyu Lee, Seung Joon Park, Yunhao Tang et al.
Linguistic Calibration of Long-Form Generations
Neil Band, Xuechen Li, Tengyu Ma et al.
LLM-Empowered State Representation for Reinforcement Learning
Boyuan Wang, Yun Qu, Yuhang Jiang et al.
Mixtures of Experts Unlock Parameter Scaling for Deep RL
Johan Obando Ceron, Ghada Sokar, Timon Willi et al.
Multimodal Label Relevance Ranking via Reinforcement Learning
Taian Guo, Taolin Zhang, Haoqian Wu et al.
Near-Optimal Regret in Linear MDPs with Aggregate Bandit Feedback
Asaf Cassel, Haipeng Luo, Aviv Rosenberg et al.
No-Regret Reinforcement Learning in Smooth MDPs
Davide Maran, Alberto Maria Metelli, Matteo Papini et al.