Vision-Language Models (VLMs) have advanced rapidly in static visual understanding, yet remain unreliable when judging how an egocentric task is progressing. Given a task instruction and two visual observations, a model should determine which state is closer to the goal by analyzing task-relevant object configurations...
Xiao-Da Yang, Can Wang, Yu-Xiang Liu et al.· 0 citations
Text-to-image (T2I) models can produce visually compelling images, yet they remain limited on open-world tasks that require complex semantic understanding, multi-step reasoning, and the integration of external world knowledge. Existing efforts introduce agent capabilities into image generation, but they either prescrib...
Jiahao Zhao, Xiao-Min Yu, ZhongXiang Sun et al.· 3 citations
Joint text-to-video-audio generation produces synchronized visual and acoustic content, but the long sampling trajectories and heterogeneous multimodal computation of large models make inference prohibitively expensive. We present TurboT2VA, a distillation and inference framework for accelerating a 19B-parameter joint...
Xiaoda Yang, Yuxiang Liu, Kaiwen Zheng et al.· 0 citations
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