Copertina

Salience-Invariant Consistent Policy Learning for Generalization in Visual Reinforcement Learning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Sun, Jingbo, Tu, Songjun, Zhang, Qichao, Chen, Ke, Zhao, Dongbin
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Saliency-Guided Representation with Consistency Policy Learning for Visual Unsupervised Reinforcement Learning
di: Sun, Jingbo, et al.
Pubblicazione: (2026)

Online Preference-based Reinforcement Learning with Self-augmented Feedback from Large Language Model
di: Tu, Songjun, et al.
Pubblicazione: (2024)

In-Dataset Trajectory Return Regularization for Offline Preference-based Reinforcement Learning
di: Tu, Songjun, et al.
Pubblicazione: (2024)

AutoSearch: Adaptive Search Depth for Efficient Agentic RAG via Reinforcement Learning
di: Sun, Jingbo, et al.
Pubblicazione: (2026)

Learning When to Think: Shaping Adaptive Reasoning in R1-Style Models via Multi-Stage RL
di: Tu, Songjun, et al.
Pubblicazione: (2025)

SRFT: A Single-Stage Method with Supervised and Reinforcement Fine-Tuning for Reasoning
di: Fu, Yuqian, et al.
Pubblicazione: (2025)

Generalizing Consistency Policy to Visual RL with Prioritized Proximal Experience Regularization
di: Li, Haoran, et al.
Pubblicazione: (2024)

RLAE: Reinforcement Learning-Assisted Ensemble for LLMs
di: Fu, Yuqian, et al.
Pubblicazione: (2025)

Dynamic Dual-Granularity Skill Bank for Agentic RL
di: Tu, Songjun, et al.
Pubblicazione: (2026)

Perception-Consistency Multimodal Large Language Models Reasoning via Caption-Regularized Policy Optimization
di: Tu, Songjun, et al.
Pubblicazione: (2025)

Learning Future Representation with Synthetic Observations for Sample-efficient Reinforcement Learning
di: Liu, Xin, et al.
Pubblicazione: (2024)

Discretizing Continuous Action Space with Unimodal Probability Distributions for On-Policy Reinforcement Learning
di: Zhu, Yuanyang, et al.
Pubblicazione: (2024)

ConRFT: A Reinforced Fine-tuning Method for VLA Models via Consistency Policy
di: Chen, Yuhui, et al.
Pubblicazione: (2025)

LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions
di: Sun, Chuanneng, et al.
Pubblicazione: (2024)

SAFE-RL: Saliency-Aware Counterfactual Explainer for Deep Reinforcement Learning Policies
di: Samadi, Amir, et al.
Pubblicazione: (2024)

Cross-domain Random Pre-training with Prototypes for Reinforcement Learning
di: Liu, Xin, et al.
Pubblicazione: (2023)

Thinking with Constructions: A Benchmark and Policy Optimization for Visual-Text Interleaved Geometric Reasoning
di: Zhao, Haokun, et al.
Pubblicazione: (2026)

TeViR: Text-to-Video Reward with Diffusion Models for Efficient Reinforcement Learning
di: Chen, Yuhui, et al.
Pubblicazione: (2025)

World4RL: Diffusion World Models for Policy Refinement with Reinforcement Learning for Robotic Manipulation
di: Jiang, Zhennan, et al.
Pubblicazione: (2025)

One LR Doesn't Fit All: Heavy-Tail Guided Layerwise Learning Rates for LLMs
di: He, Di, et al.
Pubblicazione: (2026)

A Hierarchical Deep Reinforcement Learning Framework for 6-DOF UCAV Air-to-Air Combat
di: Chai, Jiajun, et al.
Pubblicazione: (2022)

TrajMoE: Scene-Adaptive Trajectory Planning with Mixture of Experts and Reinforcement Learning
di: Xing, Zebin, et al.
Pubblicazione: (2025)

Offline Reinforcement Learning with Generative Trajectory Policies
di: Feng, Xinsong, et al.
Pubblicazione: (2025)

On Generating Explanations for Reinforcement Learning Policies: An Empirical Study
di: Yuasa, Mikihisa, et al.
Pubblicazione: (2023)

Pessimistic Auxiliary Policy for Offline Reinforcement Learning
di: Zhang, Fan, et al.
Pubblicazione: (2026)

Preferred-Action-Optimized Diffusion Policies for Offline Reinforcement Learning
di: Zhang, Tianle, et al.
Pubblicazione: (2024)

LAMARL: LLM-Aided Multi-Agent Reinforcement Learning for Cooperative Policy Generation
di: Zhu, Guobin, et al.
Pubblicazione: (2025)

WebRenderBench: Enhancing Web Interface Generation through Layout-Style Consistency and Reinforcement Learning
di: Lai, Peichao, et al.
Pubblicazione: (2025)

FM3Q: Factorized Multi-Agent MiniMax Q-Learning for Two-Team Zero-Sum Markov Game
di: Hu, Guangzheng, et al.
Pubblicazione: (2024)

Revisiting Generative Policies: A Simpler Reinforcement Learning Algorithmic Perspective
di: Zhang, Jinouwen, et al.
Pubblicazione: (2024)

Learning by Doing: An Online Causal Reinforcement Learning Framework with Causal-Aware Policy
di: Cai, Ruichu, et al.
Pubblicazione: (2024)

Integrating Saliency Ranking and Reinforcement Learning for Enhanced Object Detection
di: Bartolo, Matthias, et al.
Pubblicazione: (2024)

LLM-Driven Policy Diffusion: Enhancing Generalization in Offline Reinforcement Learning
di: Zhang, Hanping, et al.
Pubblicazione: (2025)

Reinforcement Learning Policy as Macro Regulator Rather than Macro Placer
di: Xue, Ke, et al.
Pubblicazione: (2024)

Large Language Model as a Policy Teacher for Training Reinforcement Learning Agents
di: Zhou, Zihao, et al.
Pubblicazione: (2023)

Behavior-Consistent Deep Reinforcement Learning
di: Hussing, Marcel, et al.
Pubblicazione: (2026)

Policy Expansion for Bridging Offline-to-Online Reinforcement Learning
di: Zhang, Haichao, et al.
Pubblicazione: (2023)

Forward Learning for Gradient-based Black-box Saliency Map Generation
di: Zhang, Zeliang, et al.
Pubblicazione: (2024)

Test-driven Reinforcement Learning in Continuous Control
di: Yu, Zhao, et al.
Pubblicazione: (2025)

Physics-Regulated Deep Reinforcement Learning: Invariant Embeddings
di: Cao, Hongpeng, et al.
Pubblicazione: (2023)