A research paper co-authored by Dobot, the Institute of Computing Technology of the Chinese Academy of Sciences, the Nanjing College of the University of Chinese Academy of Sciences, the Nanjing Information High-Speed Rail Research Institute, and two other CAS-affiliated schools has been accepted for publication at the Findings of EMNLP 2026, the top-tier international conference on computational linguistics and natural language processing, which will take place in Budapest from 24–29 October. The study, titled “Meta-Learning Where to Allocate Experts: Task-Conditioned Layer-Wise Compression for MoEs,” proposes a novel compression method for mixture-of-experts models, marking a collaborative research achievement among the Chinese academic and industrial partners.
Dobot, CAS institutes' MoE paper accepted by EMNLP 2026
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