2 papers
cs.AI2026
Are Benchmarks Reliable? Toward Structural Diagnosis via Item-Level Capability Boundaries
Haiquan Hu, Yuzhu Liang, Weicheng Tang +4
Evaluating large language models (LLMs) relies heavily on benchmark scores, yet aggregate metrics can obscure whether individual items serve their intended measurement purpose. BSD…
cs.LG2025
Diffusion Models for Reinforcement Learning: Foundations, Taxonomy, and Development
Changfu Xu, Jianxiong Guo, Yuzhu Liang +7
Diffusion Models (DMs), as a leading class of generative models, offer key advantages for reinforcement learning (RL), including multi-modal expressiveness, stable training, and tr…