2 papers
cs.CV2026
Are Reasoning Vision-Language Models Robust to Semantic Visual Distractions?
Yizheng Sun, Mochuan Zhan, Yanan Ma +10
Reasoning Vision-Language Models (VLMs) achieve strong performance on complex multimodal tasks, but reliable real-world application requires handling visual inputs that are messier…
cs.CL2025
SelectIT: Selective Instruction Tuning for LLMs via Uncertainty-Aware Self-Reflection
Liangxin Liu, Xuebo Liu, Derek F. Wong +4
Instruction tuning (IT) is crucial to tailoring large language models (LLMs) towards human-centric interactions. Recent advancements have shown that the careful selection of a smal…