Junxiong Wang

I obtained my PhD in Computer Science from Cornell University, where I worked at the intersection of systems and large language models, with a focus on linear models and their hybrid variants. I lead multiple research projects at Together AI, including adaptive speculative decoding, inference time training, and efficient RL rollouts. If you would like to see my CV, please feel free to contact me by email.

Recent Publications

• Woojeong Kim, Junxiong Wang, Jing Nathan Yan, Mohamed S. Abdelfattah, Alexander M. Rush
  Overfill: Two-Stage Models for Efficient Language Model Decoding
  Conference on Language Modeling (CoLM), 2025
  
  
• Daniele Paliotta*, Junxiong Wang*, Matteo Pagliardini*, Kevin Y Li*, Aviv Bick, J Zico Kolter, Albert Gu, François Fleuret, Tri Dao
  Thinking Slow, Fast: Scaling Inference Compute with Distilled Reasoners
  A shorter version at ICLR 2024, Workshop on Reasoning and Planning for Large Language Models
  In submission
  
  
• Junxiong Wang*, Daniele Paliotta*, Avner May, Alexander M. Rush, Tri Dao
  The Mamba in the Llama: Distilling and Accelerating Hybrid Models
  Models, Video, Code, Blog
  Neural Information Processing Systems (NeurIPS), 2024
  A shorter version at ICML 2024, 2nd Workshop on Efficient Systems for Foundation Models (ES-FoMo)
  
  
• Junxiong Wang, Tushaar Gangavarapu, Jing Nathan Yan, Alexander M. Rush
  MambaByte: Token-free Selective State Space Model
  Models, Video
  Conference on Language Modeling (CoLM), 2024
  
  

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