2 citations · 4 across the 9 of their papers we have counts for
10 papers
VidaForge: Open Research Infrastructure for Video Pretraining Data Recipes
Yan Ma, Jiadi Su, Zhulin Hu +4
Video foundation models increasingly rely on large-scale pretraining data, yet the end-to-end data pipelines behind them remain largely closed and difficult to inspect or reuse. Re…
Speed by Simplicity: A Single-Stream Architecture for Fast Audio-Video Generative Foundation Model
SII-GAIR, Sand. ai, : +43
We present daVinci-MagiHuman, an open-source audio-video generative foundation model for human-centric generation. daVinci-MagiHuman jointly generates synchronized video and audio…
LiveTalk: Real-Time Multimodal Interactive Video Diffusion via Improved On-Policy Distillation
Ethan Chern, Zhulin Hu, Bohao Tang +4
Real-time video generation via diffusion is essential for building general-purpose multimodal interactive AI systems. However, the simultaneous denoising of all video frames with b…
Mantis: A Versatile Vision-Language-Action Model with Disentangled Visual Foresight
Yi Yang, Xueqi Li, Yiyang Chen +7
Recent advances in Vision-Language-Action (VLA) models demonstrate that visual signals can effectively complement sparse action supervisions. However, letting VLA directly predict…
Visual Programmability: A Guide for Code-as-Thought in Chart Understanding
Bohao Tang, Yan Ma, Fei Zhang +6
Chart understanding presents a critical test to the reasoning capabilities of Vision-Language Models (VLMs). Prior approaches face critical limitations: some rely on external tools…
Interaction as Intelligence: Deep Research With Human-AI Partnership
Lyumanshan Ye, Xiaojie Cai, Xinkai Wang +23
This paper introduces "Interaction as Intelligence" research series, presenting a reconceptualization of human-AI relationships in deep research tasks. Traditional approaches treat…
Thinking with Generated Images
Ethan Chern, Zhulin Hu, Steffi Chern +5
We present Thinking with Generated Images, a novel paradigm that fundamentally transforms how large multimodal models (LMMs) engage with visual reasoning by enabling them to native…
PC Agent: While You Sleep, AI Works -- A Cognitive Journey into Digital World
Yanheng He, Jiahe Jin, Shijie Xia +5
Imagine a world where AI can handle your work while you sleep - organizing your research materials, drafting a report, or creating a presentation you need for tomorrow. However, wh…
ANOLE: An Open, Autoregressive, Native Large Multimodal Models for Interleaved Image-Text Generation
Ethan Chern, Jiadi Su, Yan Ma +1
Previous open-source large multimodal models (LMMs) have faced several limitations: (1) they often lack native integration, requiring adapters to align visual representations with…
OlympicArena: Benchmarking Multi-discipline Cognitive Reasoning for Superintelligent AI
Zhen Huang, Zengzhi Wang, Shijie Xia +25
The evolution of Artificial Intelligence (AI) has been significantly accelerated by advancements in Large Language Models (LLMs) and Large Multimodal Models (LMMs), gradually showc…