Chaoyou Fu

R1-Reward: Training Multimodal Reward Model Through Stable Reinforcement Learning

Thyme: Think Beyond Images

VITA-E: A Dual-Model Framework for Real-Time, Interruptible, and Concurrent Human-Robot Interaction

BaseReward: A Strong Baseline for Multimodal Reward Model

Human-MME: A Holistic Evaluation Benchmark for Human-Centric Multimodal Large Language Models

MME-Unify: A Comprehensive Benchmark for Unified Multimodal Understanding and Generation Models

MME-Reasoning: A Comprehensive Benchmark for Logical Reasoning in MLLMs

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

CUARewardBench: Benchmark for Evaluating Reward Models on Computer-using Agent Trajectories

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

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

MME-CC: A Challenging Multi-Modal Evaluation Benchmark of Cognitive Capacity

HumanVideo-MME: Benchmarking MLLMs for Human-Centric Video Understanding

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

Video-RAG: Visually-aligned Retrieval-Augmented Long Video Comprehension

MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans?

Learning Interleaved Image-Text Comprehension in Vision-Language Large Models

VITA-Audio: Fast Interleaved Audio-Text Token Generation for Efficient Large Speech-Language Model

Zooming from Context to Cue: Hierarchical Preference Optimization for Multi-Image MLLMs

MM-RLHF: The Next Step Forward in Multimodal LLM Alignment

MME-CoT: Benchmarking Chain-of-Thought in Large Multimodal Models for Reasoning Quality, Robustness, and Efficiency

MME-FINANCE: A Multimodal Finance Benchmark for Expert-level Understanding and Reasoning

Freeze-Omni: A Smart and Low Latency Speech-to-speech Dialogue Model with Frozen LLM