3 papers
cs.CV2026
Are VLMs Seeing or Just Saying? Uncovering the Illusion of Visual Re-examination
Chufan Shi, Cheng Yang, Yaokang Wu +4
Vision-Language Models (VLMs) often produce self-reflective statements like "let me check the figure again" during reasoning. Do such statements trigger genuine visual re-examinati…
cs.CL2026
From Reasoning to Pixels: Benchmarking the Alignment Gap in Unified Multimodal Models
Cheng Yang, Chufan Shi, Bo Shui +7
Unified multimodal models (UMMs) aim to integrate multimodal understanding and generation within a unified architecture, yet it remains unclear to what extent their representations…
cs.AI2026
From Abstract to Contextual: What LLMs Still Cannot Do in Mathematics
Bowen Cao, Dongdong Zhang, Yixia Li +8
Large language models now solve many benchmark math problems at near-expert levels, yet this progress has not fully translated into reliable performance in real-world applications.…