1 citations · 1 across the 24 of their papers we have counts for
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EACO: Enhancing Alignment in Multimodal LLMs via Critical Observation
Yongxin Wang, Meng Cao, Haokun Lin +5
Multimodal large language models (MLLMs) have achieved remarkable progress on various visual question answering and reasoning tasks leveraging instruction fine-tuning specific data…
PhysGame: Uncovering Physical Commonsense Violations in Gameplay Videos
Meng Cao, Haoran Tang, Haoze Zhao +7
Recent advancements in video-based large language models (Video LLMs) have witnessed the emergence of diverse capabilities to reason and interpret dynamic visual content. Among the…
Continual LLaVA: Continual Instruction Tuning in Large Vision-Language Models
Meng Cao, Yuyang Liu, Yingfei Liu +6
Instruction tuning constitutes a prevalent technique for tailoring Large Vision Language Models (LVLMs) to meet individual task requirements. To date, most of the existing approach…
MUSE: Mamba is Efficient Multi-scale Learner for Text-video Retrieval
Haoran Tang, Meng Cao, Jinfa Huang +4
Text-Video Retrieval (TVR) aims to align and associate relevant video content with corresponding natural language queries. Most existing TVR methods are based on large-scale pre-tr…
RAP: Efficient Text-Video Retrieval with Sparse-and-Correlated Adapter
Meng Cao, Haoran Tang, Jinfa Huang +7
Text-Video Retrieval (TVR) aims to align relevant video content with natural language queries. To date, most state-of-the-art TVR methods learn image-to-video transfer learning bas…