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cs.CL2026
Faster but Different: Diagnosing and Controlling Content Drift in Accelerated Multimodal Diffusion Language Models
Yaoxuan Dou, Yang Shu
Training-free acceleration makes diffusion-based multimodal large language models (dMLLMs) more deployable, but it may silently change generated content. We study this serving-time…
cs.CL2026
Localizing Prompt Ambiguity in Large Language Models with Probe-Targeted Attribution
Govind Ramesh, Yao Dou, Wei Xu
Prompt ambiguity is a common source of failure in large language models, but is difficult to localize because it is a latent property of the prompt, while existing attribution meth…
cs.CL2026
Gavel: Agent Meets Checklist for Evaluating LLMs on Long-Context Legal Summarization
Yao Dou, Benjamin Mamut, Wei Xu
Large language models (LLMs) now support contexts of up to 1M tokens, but their strengths and weaknesses on complex long-context tasks remain unclear. To study this, we focus on mu…