10 papers
Beyond Isolation: Unlocking Reinforcement Learning Component Synergy for Sample-Efficient Continuous Control
Qi Zhao, Guozheng Ma, Yilun Kong +9
Reinforcement learning systems are significantly more complex than other machine learning paradigms due to inherent properties, causing RL system design to jointly account for many…
Distribution Preference Optimization: A Fine-grained Perspective for LLM Unlearning
Kai Qin, Jiaqi Wu, Jianxiang He +8
As Large Language Models (LLMs) demonstrate remarkable capabilities learned from vast corpora, concerns regarding data privacy and safety are receiving increasing attention. LLM un…
Principled RL for Flow Matching Emerges from the Chunk-level Policy Optimization
Yifu Luo, Haoyuan Sun, Xinhao Hu +12
Recent Progress in post-training flow matching for text-to-image (T2I) generation with Group Relative Policy Optimization (GRPO) has demonstrated strong potential. However, it is h…
Wavelet Fourier Diffuser: Frequency-Aware Diffusion Model for Reinforcement Learning
Yifu Luo, Yongzhe Chang, Xueqian Wang
Diffusion probability models have shown significant promise in offline reinforcement learning by directly modeling trajectory sequences. However, existing approaches primarily focu…
Bridging Perception and Action: A Lightweight Multimodal Meta-Planner Framework for Robust Earth Observation Agents
Jinghui Xu, Boyi Shangguan, Mengke Zhu +10
Autonomous Earth Observation (EO) agents are transitioning from passive perception to complex, multi-step task execution. However, current architectures that integrate planning and…
Co-Evolutionary Multi-Modal Alignment via Structured Adversarial Evolution
Guoxin Shi, Haoyu Wang, Zaihui Yang +2
Adversarial behavior plays a central role in aligning large language models with human values. However, existing alignment methods largely rely on static adversarial settings, whic…