Kimi Linear: An Expressive, Efficient Attention Architecture
Kimi Linear is a new attention architecture designed to improve the efficiency and expressiveness of large language models. The paper, authored by the Kimi team, explores advancements in sequence processing for AI applications.
Why it matters
Improving attention mechanisms is essential for reducing the computational cost and latency of training and running large-scale AI models.
Focus to learn more arXiv-issued DOI via DataCite Submission history From: Yulun Du [ view email ] [v1] Thu, 30 Oct 2025 16:59:43 UTC (645 KB) [v2] Sat, 1 Nov 2025 12:05:18 UTC (691 KB) Full-text links: Access Paper: View a PDF of the paper titled Kimi Linear: An Expressive, Efficient Attention Architecture, by Kimi Team: Yu Zhang and 58 other authors View PDF TeX Source view license Current browse context: cs.CL < prev | next > new | recent | 2025-10 Change to browse by: cs cs.LG References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps?
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