Poster · Atlanta

MoBiQuant: Mixture-of-Bits Quantization for Token-Adaptive Any-Precision LLM

Name: MoBiQuant: Mixture-of-Bits Quantization for Token-Adaptive Any-Precision LLM
Start: 2026-12-09T16:30:00-05:00
End: 2026-12-09T19:30:00-05:00
Location: Hall C1, Georgia World Congress Center

When: Wed 9 Dec 2026, 16:30–19:30 EST
Where: Hall C1, Georgia World Congress Center
Session: Atlanta Poster Session 2
Authors: Dongwei Wang, Jinhee Kim, Seokho Han, Denis Gudovskiy, Yohei Nakata, Tomoyuki Okuno, KhayTze Peong, Kang E Jeon, Jong Hwan Ko, Yiran Chen, Huanrui Yang
Organisations: University of Arizona, Duke University, Sungkyunkwan University, Panasonic AI Lab, Panasonic Holdings Corp, Panasonic Holdings Corporation, Daegu Gyeongbuk Institute of Science and Technology
QRS classification: Language models, Efficient and distributed ML systems

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