3 papers
cs.CV2026
Long Grounded Thoughts: Synthesizing Visual Problems and Reasoning Chains at Scale
David Acuna, Chao-Han Huck Yang, Yuntian Deng +6
Despite rapid progress, multimodal reasoning still lacks a systematic approach to synthesize large-scale vision-centric datasets beyond visual math. We introduce a framework able t…
cs.CV2025
Can Large Vision-Language Models Correct Semantic Grounding Errors By Themselves?
Yuan-Hong Liao, Rafid Mahmood, Sanja Fidler +1
Enhancing semantic grounding abilities in Vision-Language Models (VLMs) often involves collecting domain-specific training data, refining the network architectures, or modifying th…
cs.CV2025
LongPerceptualThoughts: Distilling System-2 Reasoning for System-1 Perception
Yuan-Hong Liao, Sven Elflein, Liu He +4
Recent reasoning models through test-time scaling have demonstrated that long chain-of-thoughts can unlock substantial performance boosts in hard reasoning tasks such as math and c…