activity
20242026
most citedVITA: Towards Open-Source Interactive Omni Multimodal LLM

5 citations · 9 across the 10 of their papers we have counts for

collaborators

12 papers

cs.CV2026

OmniVideo-100K: A Dataset for Audio-Visual Reasoning through Structured Scripts and Evidence Chains

Xinyue Cai, Chaoyou Fu, Yi-Fan Zhang +2

Current automated pipelines for audio-visual Question Answering (QA) generally adopt a ``video-caption-QA'' paradigm. However, these methods typically segment videos into short cli…

cs.CV2026

Video-MME-v2: Towards the Next Stage in Benchmarks for Comprehensive Video Understanding

Chaoyou Fu, Haozhi Yuan, Yuhao Dong +16

With the rapid advancement of video understanding, existing benchmarks are becoming increasingly saturated, exposing a critical discrepancy between inflated leaderboard scores and…

cs.CV2026

Unify-Agent: A Unified Multimodal Agent for World-Grounded Image Synthesis

Shuang Chen, Quanxin Shou, Hangting Chen +16

Unified multimodal models provide a natural and promising architecture for understanding diverse and complex real-world knowledge while generating high-quality images. However, the…

cs.CL2026

PersonaVLM: Long-Term Personalized Multimodal LLMs

Chang Nie, Chaoyou Fu, Yifan Zhang +2

Multimodal Large Language Models (MLLMs) serve as daily assistants for millions. However, their ability to generate responses aligned with individual preferences remains limited. P…

cs.RO2025

VITA-E: Natural Embodied Interaction with Concurrent Seeing, Hearing, Speaking, and Acting

Xiaoyu Liu, Chaoyou Fu, Chi Yan +15

Current Vision-Language-Action (VLA) models are often constrained by a rigid, static interaction paradigm, which lacks the ability to see, hear, speak, and act concurrently as well…

cs.CV2025

VITA-VLA: Efficiently Teaching Vision-Language Models to Act via Action Expert Distillation

Shaoqi Dong, Chaoyou Fu, Haihan Gao +12

Vision-Language Action (VLA) models significantly advance robotic manipulation by leveraging the strong perception capabilities of pretrained vision-language models (VLMs). By inte…

cs.CV2025

OpenGPT-4o-Image: A Comprehensive Dataset for Advanced Image Generation and Editing

Zhihong Chen, Xuehai Bai, Yang Shi +9

The performance of unified multimodal models for image generation and editing is fundamentally constrained by the quality and comprehensiveness of their training data. While existi…

cs.AI2025

RealUnify: Do Unified Models Truly Benefit from Unification? A Comprehensive Benchmark

Yang Shi, Yuhao Dong, Yue Ding +22

The integration of visual understanding and generation into unified multimodal models represents a significant stride toward general-purpose AI. However, a fundamental question rem…

cs.CV2025

MME-VideoOCR: Evaluating OCR-Based Capabilities of Multimodal LLMs in Video Scenarios

Yang Shi, Huanqian Wang, Wulin Xie +20

Multimodal Large Language Models (MLLMs) have achieved considerable accuracy in Optical Character Recognition (OCR) from static images. However, their efficacy in video OCR is sign…

cs.CV2025

VITA-1.5: Towards GPT-4o Level Real-Time Vision and Speech Interaction

Chaoyou Fu, Haojia Lin, Xiong Wang +13

Recent Multimodal Large Language Models (MLLMs) have typically focused on integrating visual and textual modalities, with less emphasis placed on the role of speech in enhancing in…

cs.CV2024★ 4 cited

MME-Survey: A Comprehensive Survey on Evaluation of Multimodal LLMs

Chaoyou Fu, Yi-Fan Zhang, Shukang Yin +9

As a prominent direction of Artificial General Intelligence (AGI), Multimodal Large Language Models (MLLMs) have garnered increased attention from both industry and academia. Build…

cs.CV2024★ 5 cited

VITA: Towards Open-Source Interactive Omni Multimodal LLM

Chaoyou Fu, Haojia Lin, Zuwei Long +16

The remarkable multimodal capabilities and interactive experience of GPT-4o underscore their necessity in practical applications, yet open-source models rarely excel in both areas.…