AI RESEARCH
Spatial-Conditioned Reasoning in Long-Egocentric Videos
arXiv CS.CV
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ArXi:2601.18100v2 Announce Type: replace Long-horizon egocentric video presents significant challenges for visual navigation due to viewpoint drift and the absence of persistent geometric context. Although recent vision-language models perform well on image and short-video reasoning, their spatial reasoning capability in long egocentric sequences remains limited. In this work, we study how explicit spatial signals influence VLM-based video understanding without modifying model architectures or inference procedures. We.