5 papers · 1 filter
SyncRA: Learning Temporal Correspondence in Omni-Modal Models
Zelong Xu, Yan Li, Wenhe Hu +1
Recent omni-modal models demonstrate strong perception of audio and visual inputs, yet often struggle to connect what they hear with what they see at the same moment. This weakness…
Moment-Video: Diagnosing Temporal Fidelity of Video MLLMs on Momentary Visual Events
Xiaolin Liu, Yilun Zhu, Xiangyu Zhao +9
Video multimodal large language models (MLLMs) have made rapid progress in general and long-form video understanding, yet their ability to capture and use brief, answer-critical vi…
EvoTok: A Unified Image Tokenizer via Residual Latent Evolution for Visual Understanding and Generation
Yan Li, Ning Liao, Xiangyu Zhao +5
The development of unified multimodal large language models (MLLMs) is fundamentally challenged by the granularity gap between visual understanding and generation: understanding re…
UniWeTok: An Unified Binary Tokenizer with Codebook Size for Unified Multimodal Large Language Model
Shaobin Zhuang, Yuang Ai, Jiaming Han +12
Unified Multimodal Large Language Models (MLLMs) require a visual representation that simultaneously supports high-fidelity reconstruction, complex semantic extraction, and generat…
VirtueBench: Evaluating Trustworthiness under Uncertainty in Long Video Understanding
Xueqing Yu, Bohan Li, Yan Li +1
Recent Vision-Language Models (VLMs) have made remarkable progress in multimodal understanding tasks, yet their evaluation on long video understanding remains unreliable. Due to li…