3 papers
cs.LG2026
Policy Improvement Reinforcement Learning
Huaiyang Wang, Xiaojie Li, Xiaohan Wang +10
Reinforcement learning has become a central post-training paradigm for improving LLM and agent capabilities. Yet existing RL post-training methods share a common blind spot: they c…
cs.CL2026
WaveFilter: Enhancing the Long-Context Capability of Diffusion LLMs via Wavelet-Guided KV Cache Filtering
Jinnan Yang, Yan Wang, Zhen Bi +5
Diffusion Large Language Models (DLMs) have demonstrated significant advantages across various tasks. However, constrained by their multi-step iterative inference mechanism, their…
cs.LG2026
Adaptive Batch-Wise Sample Scheduling for Direct Preference Optimization
Zixuan Huang, Yikun Ban, Lean Fu +4
Direct Preference Optimization (DPO) has emerged as an effective approach for aligning large language models (LLMs) with human preferences. However, its performance is highly depen…