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20242026
most citedVideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs

11 citations · 17 across the 19 of their papers we have counts for

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5 papers · 1 filter

cs.AI2024

Chain of Ideas: Revolutionizing Research Via Novel Idea Development with LLM Agents

Long Li, Weiwen Xu, Jiayan Guo +11

Effective research ideation is a critical step for scientific research. However, the exponential increase in scientific literature makes it challenging for researchers to stay curr…

cs.CV2024

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…

cs.CV2024

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…

cs.CV2024★ 11 cited

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…

cs.CL2024★ 1 cited

Auto-Arena: Automating LLM Evaluations with Agent Peer Battles and Committee Discussions

Ruochen Zhao, Wenxuan Zhang, Yew Ken Chia +3

As LLMs continuously evolve, there is an urgent need for a reliable evaluation method that delivers trustworthy results promptly. Currently, static benchmarks suffer from inflexibi…