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20242026
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cs.CV2026

Small Vision-Language Models are Smart Compressors for Long Video Understanding

Junjie Fei, Jun Chen, Zechun Liu +13

Adapting Multimodal Large Language Models (MLLMs) for hour-long videos is bottlenecked by context limits. Dense visual streams saturate token budgets and exacerbate the lost-in-the…

cs.CV2025

WikiAutoGen: Towards Multi-Modal Wikipedia-Style Article Generation

Zhongyu Yang, Jun Chen, Dannong Xu +5

Knowledge discovery and collection are intelligence-intensive tasks that traditionally require significant human effort to ensure high-quality outputs. Recent research has explored…

cs.CV2025

Kestrel: 3D Multimodal LLM for Part-Aware Grounded Description

Mahmoud Ahmed, Junjie Fei, Jian Ding +2

In this paper, we introduce Part-Aware Point Grounded Description (PaPGD), a challenging task aimed at advancing 3D multimodal learning for fine-grained, part-aware segmentation gr…

cs.CV2025

MAGNET: A Multi-agent Framework for Finding Audio-Visual Needles by Reasoning over Multi-Video Haystacks

Sanjoy Chowdhury, Mohamed Elmoghany, Yohan Abeysinghe +5

Large multimodal models (LMMs) have shown remarkable progress in audio-visual understanding, yet they struggle with real-world scenarios that require complex reasoning across exten…

cs.CV2024

Document Haystacks: Vision-Language Reasoning Over Piles of 1000+ Documents

Jun Chen, Dannong Xu, Junjie Fei +2

Large multimodal models (LMMs) have achieved impressive progress in vision-language understanding, yet they face limitations in real-world applications requiring complex reasoning…