AgentVQA benchmarks vision-language models on agentic visual tasks
The best of 22 models scores 58.5% on 1,000 examples drawn from 23 datasets across five agent domains.
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The best of 22 models scores 58.5% on 1,000 examples drawn from 23 datasets across five agent domains.
Jag predicts bounding boxes in one forward pass, specializing a compact multimodal model for faster visual grounding.
GroundAnything, a 4B model, pairs parallel diffusion decoding with precise visual grounding and large inference speedups.
MoE routing signals detect missing visual targets in Qwen and Gemma VLMs and trigger selective review.
AnchorReasoning provides visually grounded reasoning data for long-tail autonomous driving across 416,119 annotated frames.
Study shows visually grounded token embeddings in a small masked LM persist through training and improve object-property knowledge, but escape standard BabyLM benchmarks.
Researchers diagnose conditional visual grounding failures in visuomotor imitation policies and show targeted interventions substantially improve distractor robustness.
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