82 citations · 207 across the 24 of their papers we have counts for
6 papers · 1 filter
Breaking the Memory Barrier: Near Infinite Batch Size Scaling for Contrastive Loss
Zesen Cheng, Hang Zhang, Kehan Li +6
Contrastive loss is a powerful approach for representation learning, where larger batch sizes enhance performance by providing more negative samples to better distinguish between s…
The Curse of Multi-Modalities: Evaluating Hallucinations of Large Multimodal Models across Language, Visual, and Audio
Sicong Leng, Yun Xing, Zesen Cheng +7
Recent advancements in large multimodal models (LMMs) have significantly enhanced performance across diverse tasks, with ongoing efforts to further integrate additional modalities…
Local Action-Guided Motion Diffusion Model for Text-to-Motion Generation
Peng Jin, Hao Li, Zesen Cheng +6
Text-to-motion generation requires not only grounding local actions in language but also seamlessly blending these individual actions to synthesize diverse and realistic global mot…
VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs
Zesen Cheng, Sicong Leng, Hang Zhang +8
In this paper, we present the VideoLLaMA 2, a set of Video Large Language Models (Video-LLMs) designed to enhance spatial-temporal modeling and audio understanding in video and aud…
GraCo: Granularity-Controllable Interactive Segmentation
Yian Zhao, Kehan Li, Zesen Cheng +6
Interactive Segmentation (IS) segments specific objects or parts in the image according to user input. Current IS pipelines fall into two categories: single-granularity output and…
Instance Brownian Bridge as Texts for Open-vocabulary Video Instance Segmentation
Zesen Cheng, Kehan Li, Hao Li +5
Temporally locating objects with arbitrary class texts is the primary pursuit of open-vocabulary Video Instance Segmentation (VIS). Because of the insufficient vocabulary of video…