Video understanding benchmarks have long centered on single-camera settings, where modern multi-modal language models achieve strong performance across image and video tasks. Yet, the real world runs on multi-camera networks: autonomous vehicles, security systems, and robots all gather data across many simultaneous vie...
Sahil Shah, S. Sharan, Harsh Goel et al.· 1 citation
Vision-language navigation agents are often evaluated on their ability to follow route-like instructions toward a fixed goal. Yet, real navigation instructions often depend on observed states of the environment: if a condition holds, then follow one path, otherwise take another. Such instructions require an agent to ev...
Seoyoung Lee, N. Bhatt, Pranay Samineni et al.· 0 citations
VSeek is introduced, an agentic framework that transforms long-video question answering (LVQA) from a passive, single-pass perception task into a multi-turn retrieval process and proposes a novel neuro-symbolic approach that bridges open-ended natural language with discrete visual verification.
Harsh Goel, S. Sharan, Sahil Shah et al.· arXiv.org· 1 citation
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