collaborators

9 papers

cs.CV2026

HSD: Training-Free Acceleration for Document Parsing Vision-Language Models with Hierarchical Speculative Decoding

Wenhui Liao, Hongliang Li, Pengyu Xie +15

Document parsing is a fundamental task in multimodal understanding, supporting a wide range of downstream applications such as information extraction and intelligent document analy…

cs.CV2025

Is Sora a World Simulator? A Comprehensive Survey on General World Models and Beyond

Zheng Zhu, Xiaofeng Wang, Wangbo Zhao +15

General world models represent a crucial pathway toward achieving Artificial General Intelligence (AGI), serving as the cornerstone for various applications ranging from virtual en…

cs.CV2025

Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Zhe Chen, Weiyun Wang, Yue Cao +39

We introduce InternVL 2.5, an advanced multimodal large language model (MLLM) series that builds upon InternVL 2.0, maintaining its core model architecture while introducing signif…

cs.CV2025

InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency

Weiyun Wang, Zhangwei Gao, Lixin Gu +72

We introduce InternVL 3.5, a new family of open-source multimodal models that significantly advances versatility, reasoning capability, and inference efficiency along the InternVL…

cs.CV2025

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

InternSpatial: A Comprehensive Dataset for Spatial Reasoning in Vision-Language Models

Nianchen Deng, Lixin Gu, Shenglong Ye +17

Recent benchmarks and datasets have been proposed to improve spatial reasoning in vision-language models (VLMs), yet existing open resources remain limited in scale, visual diversi…