Publications (14)
Generative AI Act II: Test Time Scaling Drives Cognition Engineering
Shijie Xia, Yiwei Qin, Xuefeng Li +11
The first generation of Large Language Models - what might be called "Act I" of generative AI (2020-2023) - achieved remarkable success through massive parameter and data scaling,…
Rethinking RL Scaling for Vision Language Models: A Transparent, From-Scratch Framework and Comprehensive Evaluation Scheme
Yan Ma, Steffi Chern, Xuyang Shen +2
Reinforcement learning (RL) has recently shown strong potential in improving the reasoning capabilities of large language models and is now being actively extended to vision-langua…
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…
BeHonest: Benchmarking Honesty in Large Language Models
Steffi Chern, Zhulin Hu, Yuqing Yang +5
Previous works on Large Language Models (LLMs) have mainly focused on evaluating their helpfulness or harmlessness. However, honesty, another crucial alignment criterion, has recei…
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…
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…