C2-Routing cuts VLM visual tokens by routing crop or compress
With a 1,024-token cap already applied, the method reports 36.53% fewer FLOPs and a 0.77% mean relative score drop.
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Stories tagged #vqa
Rethinking LLM-Guided Visual Question Answering: Does Deeper Knowledge Integration Really Help?
Study finds shallow LLM guidance beats deep fusion for knowledge-based VQA under scarce data.
STARS: From Spatiotemporal Dynamics to Social Representations in Human-Robot Interaction
SocialNav-SUB benchmarks whether vision-language models understand social robot navigation scenes.
Don't Send What You Don't Need: Question-Guided Token Pruning as a Privacy Defense for Vision-Language Models
QPriv-VL prunes privacy-sensitive visual tokens in federated/split VQA, cutting membership-inference success on VQA-RAD from 0.99 to 0.76-0.79 using ~40% of tokens.