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cs.CV2026
Video-MME-v2: Towards the Next Stage in Benchmarks for Comprehensive Video Understanding
Chaoyou Fu, Haozhi Yuan, Yuhao Dong +16
With the rapid advancement of video understanding, existing benchmarks are becoming increasingly saturated, exposing a critical discrepancy between inflated leaderboard scores and…
cs.CV2026
Youtu-VL: Unleashing Visual Potential via Unified Vision-Language Supervision
Zhixiang Wei, Yi Li, Zhehan Kan +38
Despite the significant advancements represented by Vision-Language Models (VLMs), current architectures often exhibit limitations in retaining fine-grained visual information, lea…
cs.CV2026
Youtu-Parsing: Perception, Structuring and Recognition via High-Parallelism Decoding
Haoyu Cao, Kun Yin, Yunfei Wu +16
This paper presents Youtu-Parsing, an efficient and versatile document parsing model designed for high-performance content extraction. The architecture employs a native Vision Tran…