Prépublication
· 2026 arXiv
EN
Streaming Video Large Language Models (VLMs) enable continuous video understanding, yet existing benchmarks focus on low-dynamic scenarios. Under bounded context budgets, models must balance temporal history, spatial resolution, and temporal granularity; spars...
Yuxuan Hu, Weikang Shi et al.
#cs.CV
Prépublication
· 2026 arXiv
EN
Multimodal large language models (MLLMs) struggle with spatial, embodied, physical, and temporal reasoning. We hypothesize that these failures reflect a shared deficit in visual transition reasoning, and test whether this capability can serve as a shared train...
Zheyu Fan, Yue Zhang et al.
#cs.CV
Prépublication
· 2026 arXiv
EN
Generating realistic human-object interactions (HOI) in complex 3D scenes requires two complementary capabilities: reasoning about interaction feasibility in the environment and synthesizing realistic human-object motion. However, supervision for these capabil...
Mingyuan Lei, Yoonchang Sung et al.
#cs.CV
Prépublication
· 2026 arXiv
EN
Skill-augmented agents improve sample efficiency by distilling successful trajectories into reusable strategies. Yet most existing approaches remain text-centric, linearizing spatial layouts and action-state correspondences into language that loses critical ge...
Hongxing Li, Dingming Li et al.
#cs.CV
Prépublication
· 2026 arXiv
EN
Existing spatial reasoning benchmarks mainly test spatial perception: reading off relations already visible in the input. Yet real-world spatial intelligence demands predictive spatial reasoning: constructing a scene from observations, anticipating how an inte...
Hongxing Li, Jinyue Su et al.
#cs.CV
Prépublication
· 2026 arXiv
EN
As we move through the world and carry out everyday tasks, we encounter objects that may become relevant only later. We are capable of recalling where we left something or what was inside a container, even without knowing we would need it later. Here, we study...
Shravan Chaudhari, William Paul et al.
#cs.CV