The Open LLM Architecture Lineage
103 open-weight architectures from Raschka's gallery, linked to their closest ancestors by config.json similarity alone and laid out by generation.
Wenhao Chai is a first-year Ph.D. student in Computer Science at Princeton University, advised by Professor Karthik Narasimhan, and student researcher at Google DeepMind. He received his master's degree from University of Washington and bachelor's degree from Zhejiang University.
His research spans a wide range of topics in computer vision and machine learning. He has interned at Pika Labs working with Professor Christopher D. Manning, and Microsoft Research Asia.
He leads MovieChat, one of the first large multimodal models and benchmarks for hour-long video understanding with memory mechanism. He co-leads LiveCodeBench Pro, which has been listed as evaluation benchmarks by frontier models like Google Gemini and Meta Muse Spark. He has organized workshops and competitions at CVPR 2024, CVPR 2025, and CVPR 2026. His work has been featured by MIT Technology Review, and he was named to the AI25 list (AI innovators under 25) by Sequoia China and MIT Technology Review China.
He is currently working on AI for accelerating scientific research.
103 open-weight architectures from Raschka's gallery, linked to their closest ancestors by config.json similarity alone and laid out by generation.
Looping DiT-B/4 under the MeanFlow one-step objective: at equal compute the looped model holds no advantage, and extra denoising steps pay off more than extra loops.
Undergraduate and master's students: if you want to talk about research ideas, career plans, or life in AI/ML, book a slot. I set aside at least 30 minutes every week for these meetings, and I encourage students from underrepresented groups to reach out. Open times are on my calendar.