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

collaborators

27 papers

cs.AI2026

Intern-S2-Mobius: Foundation Model with Decoupled Knowledge and Reasoning

Kai Chen, Jifeng Ding, Ning Ding +44

We introduce Mobius-v0, an architecture that comprises a globally shared Memory (FFN) that stores knowledge vectors and multiple Reasoners (Self-Attn) that iteratively achieve comp…

cs.LG2026

Intern-S2-Preview: Scientific Agentic Foundation Model

Lei Bai, Jiaqi Cao, Chiyu Chen +121

Scientific discovery increasingly requires AI systems that can reason over scientific evidence of heterogeneous modalities, interact with scientific tools and environments, and sus…

cs.CV2026

InternVideo3: Agentify Foundation Models with Multimodal Contextual Reasoning

Ziang Yan, Sheng Xia, Jiashuo Yu +10

Recent progress in foundation models has shifted toward agentic behavior involving multi-step reasoning and tool use. However, open-source efforts largely focus on text-dominant se…

cs.SD2026

JenBridge: Adaptive Long-Form Video Soundtracking across Scene Transitions

Jiashuo Yu, Yao Yao, Boyu Chen +1

We address the challenge of generating high-fidelity, long-form soundtracks that remain coherent across scene transitions. Existing AI music systems are mainly designed for short,…

cs.LG2026

Intern-S1-Pro: Scientific Multimodal Foundation Model at Trillion Scale

Yicheng Zou, Dongsheng Zhu, Lin Zhu +174

We introduce Intern-S1-Pro, the first one-trillion-parameter scientific multimodal foundation model. Scaling to this unprecedented size, the model delivers a comprehensive enhancem…

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…

cs.CV2024

VBench++: Comprehensive and Versatile Benchmark Suite for Video Generative Models

Ziqi Huang, Fan Zhang, Xiaojie Xu +14

Video generation has witnessed significant advancements, yet evaluating these models remains a challenge. A comprehensive evaluation benchmark for video generation is indispensable…

cs.CV2024★ 1 cited

OmniCorpus: A Unified Multimodal Corpus of 10 Billion-Level Images Interleaved with Text

Qingyun Li, Zhe Chen, Weiyun Wang +37

Image-text interleaved data, consisting of multiple images and texts arranged in a natural document format, aligns with the presentation paradigm of internet data and closely resem…

cs.CV2024★ 16 cited

InternVideo2: Scaling Foundation Models for Multimodal Video Understanding

Yi Wang, Kunchang Li, Xinhao Li +17

We introduce InternVideo2, a new family of video foundation models (ViFM) that achieve the state-of-the-art results in video recognition, video-text tasks, and video-centric dialog…

cs.CV2023★ 4 cited

VBench: Comprehensive Benchmark Suite for Video Generative Models

Ziqi Huang, Yinan He, Jiashuo Yu +13

Video generation has witnessed significant advancements, yet evaluating these models remains a challenge. A comprehensive evaluation benchmark for video generation is indispensable…

cs.CV2023★ 12 cited

SEINE: Short-to-Long Video Diffusion Model for Generative Transition and Prediction

Xinyuan Chen, Yaohui Wang, Lingjun Zhang +7

Recently video generation has achieved substantial progress with realistic results. Nevertheless, existing AI-generated videos are usually very short clips ("shot-level") depicting…

cs.CV2023★ 34 cited

LAVIE: High-Quality Video Generation with Cascaded Latent Diffusion Models

Yaohui Wang, Xinyuan Chen, Xin Ma +17

This work aims to learn a high-quality text-to-video (T2V) generative model by leveraging a pre-trained text-to-image (T2I) model as a basis. It is a highly desirable yet challengi…

cs.CV2023★ 32 cited

InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation

Yi Wang, Yinan He, Yizhuo Li +13

This paper introduces InternVid, a large-scale video-centric multimodal dataset that enables learning powerful and transferable video-text representations for multimodal understand…

cs.CV2023★ 14 cited

InternGPT: Solving Vision-Centric Tasks by Interacting with ChatGPT Beyond Language

Zhaoyang Liu, Yinan He, Wenhai Wang +17

We present an interactive visual framework named InternGPT, or iGPT for short. The framework integrates chatbots that have planning and reasoning capabilities, such as ChatGPT, wit…

cs.SD2023★ 3 cited

Long-Term Rhythmic Video Soundtracker

Jiashuo Yu, Yaohui Wang, Xinyuan Chen +2

We consider the problem of generating musical soundtracks in sync with rhythmic visual cues. Most existing works rely on pre-defined music representations, leading to the incompete…

cs.CV2022★ 93 cited

InternVideo: General Video Foundation Models via Generative and Discriminative Learning

Yi Wang, Kunchang Li, Yizhuo Li +14

The foundation models have recently shown excellent performance on a variety of downstream tasks in computer vision. However, most existing vision foundation models simply focus on…

cs.CV2022★ 14 cited

InternVideo-Ego4D: A Pack of Champion Solutions to Ego4D Challenges

Guo Chen, Sen Xing, Zhe Chen +18

In this report, we present our champion solutions to five tracks at Ego4D challenge. We leverage our developed InternVideo, a video foundation model, for five Ego4D tasks, includin…

cs.CV2022★ 1 cited

Modality-Aware Contrastive Instance Learning with Self-Distillation for Weakly-Supervised Audio-Visual Violence Detection

Jiashuo Yu, Jinyu Liu, Ying Cheng +2

Weakly-supervised audio-visual violence detection aims to distinguish snippets containing multimodal violence events with video-level labels. Many prior works perform audio-visual…