2 papers
cs.CV2026
Reflect to Inform: Boosting Multimodal Reasoning via Information-Gain-Driven Verification
Shuai Lv, Chang Liu, Feng Tang +5
Multimodal Large Language Models (MLLMs) achieve strong multimodal reasoning performance, yet we identify a recurring failure mode in long-form generation: as outputs grow longer,…
cs.CV2025
FCoT-VL:Advancing Text-oriented Large Vision-Language Models with Efficient Visual Token Compression
Jianjian Li, Junquan Fan, Feng Tang +6
The rapid success of Vision Large Language Models (VLLMs) often depends on the high-resolution images with abundant visual tokens, which hinders training and deployment efficiency.…