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cs.CV2026
Building a Precise Video Language with Human-AI Oversight
Zhiqiu Lin, Chancharik Mitra, Siyuan Cen +13
Video-language models (VLMs) learn to reason about the dynamic visual world through natural language. We introduce a suite of open datasets, benchmarks, and recipes for scalable ov…
cs.CV2026★ 1 cited
TimeBlind: A Spatio-Temporal Compositionality Benchmark for Video LLMs
Baiqi Li, Kangyi Zhao, Ce Zhang +3
Fine-grained spatio-temporal understanding is essential for video reasoning and embodied AI. Yet, while Multimodal Large Language Models (MLLMs) master static semantics, their gras…