Multimodal perception forms the foundation of multimodal intelligence. In particular, spatial perception and multimodal long-context understanding are two pivotal tasks that underpin embodied AI and m
EvidenceConnect synthesizes training data to strengthen visual evidence connection, improving spatial perception and multimodal reasoning across diverse tasks.
Multimodal perception forms the foundation of multimodal intelligence. In particular, spatial perception and multimodal long-context understanding are two pivotal tasks that underpin embodied AI and multimodal agents. However, synthesizing targeted, high-quality training data for these tasks remains difficult and costly. Our key insight is that these tasks share an underlying capability, which we call connecting evidence: identifying relevant visual facts, binding them to the correct entities, recovering their relations, and composing them into an answer. Crucially, targeted training data are far easier to synthesize for this capability than for these tasks themselves. To strengthen this…
Summary and abstract excerpt via Hugging Face Papers ↗ · arXiv.
Zooming without Zooming v2: From Seeing Details to Connecting Evidence for Generalizable Multimodal Perception was first seen on Hugging Face · Daily papers on Oct 28, 2026. Since then it has appeared in 23 checks on 3 different days. Its best position was #6 of 30, reached on Oct 30, 05:28 UTC. It dropped off the list after Oct 30, 05:28 UTC.
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Not at the moment. It was last on the list on Oct 30, 05:28 UTC, after 3 days of trending.
#6 on Hugging Face · Daily papers, on Oct 30, 05:28 UTC. Trendoday checks this list every 120 minutes.
It was first seen on Oct 28, 2026 and has been on the list on 3 days (23 checks) since.