activity
20212026
most citedInternVideo: General Video Foundation Models via Generative and Discriminative Learning

93 citations · 236 across the 26 of their papers we have counts for

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Showing 2025Show all

7 papers · 1 filter

cs.CV2025

ExpVid: A Benchmark for Experiment Video Understanding & Reasoning

Yicheng Xu, Yue Wu, Jiashuo Yu +9

Multimodal Large Language Models (MLLMs) hold promise for accelerating scientific discovery by interpreting complex experimental procedures. However, their true capabilities are po…

cs.LG2025

Intern-S1: A Scientific Multimodal Foundation Model

Lei Bai, Zhongrui Cai, Yuhang Cao +173

In recent years, a plethora of open-source foundation models have emerged, achieving remarkable progress in some widely attended fields, with performance being quite close to that…

cs.CV2025

VRBench: A Benchmark for Multi-Step Reasoning in Long Narrative Videos

Jiashuo Yu, Yue Wu, Meng Chu +14

We present VRBench, the first long narrative video benchmark crafted for evaluating large models' multi-step reasoning capabilities, addressing limitations in existing evaluations…

cs.CV2025

VEU-Bench: Towards Comprehensive Understanding of Video Editing

Bozheng Li, Yongliang Wu, Yi Lu +7

Widely shared videos on the internet are often edited. Recently, although Video Large Language Models (Vid-LLMs) have made great progress in general video understanding tasks, thei…

cs.RO2025

A Comprehensive LLM-powered Framework for Driving Intelligence Evaluation

Shanhe You, Xuewen Luo, Xinhe Liang +3

Evaluation methods for autonomous driving are crucial for algorithm optimization. However, due to the complexity of driving intelligence, there is currently no comprehensive evalua…

cs.CV2025★ 1 cited

InternVideo2.5: Empowering Video MLLMs with Long and Rich Context Modeling

Yi Wang, Xinhao Li, Ziang Yan +13

This paper aims to improve the performance of video multimodal large language models (MLLM) via long and rich context (LRC) modeling. As a result, we develop a new version of Inter…

cs.CV2025

VideoChat-Flash: Hierarchical Compression for Long-Context Video Modeling

Xinhao Li, Yi Wang, Jiashuo Yu +10

Long-context video modeling is critical for multimodal large language models (MLLMs), enabling them to process movies, online video streams, and so on. Despite its advances, handli…