activity
20232025
most citedVideoLLaMA 3: Frontier Multimodal Foundation Models for Image and Video Understanding

5 citations · 8 across the 11 of their papers we have counts for

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Showing 2025Show all

7 papers · 1 filter

cs.CL2025

AR-Med: Automated Relevance Enhancement in Medical Search via LLM-Driven Information Augmentation

Chuyue Wang, Jie Feng, Yuxi Wu +4

Accurate and reliable search on online healthcare platforms is critical for user safety and service efficacy. Traditional methods, however, often fail to comprehend complex and nua…

cs.HC2025

Plug-and-Play Clarifier: A Zero-Shot Multimodal Framework for Egocentric Intent Disambiguation

Sicheng Yang, Yukai Huang, Weitong Cai +6

The performance of egocentric AI agents is fundamentally limited by multimodal intent ambiguity. This challenge arises from a combination of underspecified language, imperfect visu…

cs.AI2025

From Five Dimensions to Many: Large Language Models as Precise and Interpretable Psychological Profilers

Yi-Fei Liu, Yi-Long Lu, Di He +1

Psychological constructs within individuals are widely believed to be interconnected. We investigated whether and how Large Language Models (LLMs) can model the correlational struc…

cs.AR2025

Improving the Serving Performance of Multi-LoRA Large Language Models via Efficient LoRA and KV Cache Management

Hang Zhang, Jiuchen Shi, Yixiao Wang +3

Multiple Low-Rank Adapters (Multi-LoRAs) are gaining popularity for task-specific Large Language Model (LLM) applications. For multi-LoRA serving, caching hot KV caches and LoRA ad…

cs.CV2025★ 5 cited

VideoLLaMA 3: Frontier Multimodal Foundation Models for Image and Video Understanding

Boqiang Zhang, Kehan Li, Zesen Cheng +12

In this paper, we propose VideoLLaMA3, a more advanced multimodal foundation model for image and video understanding. The core design philosophy of VideoLLaMA3 is vision-centric. T…

cs.CV2025

2.5 Years in Class: A Multimodal Textbook for Vision-Language Pretraining

Wenqi Zhang, Hang Zhang, Xin Li +6

Compared to image-text pair data, interleaved corpora enable Vision-Language Models (VLMs) to understand the world more naturally like humans. However, such existing datasets are c…

cs.CV2025

VideoRefer Suite: Advancing Spatial-Temporal Object Understanding with Video LLM

Yuqian Yuan, Hang Zhang, Wentong Li +9

Video Large Language Models (Video LLMs) have recently exhibited remarkable capabilities in general video understanding. However, they mainly focus on holistic comprehension and st…