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Researchers break 1.58-bit barrier for ternary LLM compression

Paper on ternary LLM compression published on arXiv

1 Sep 16 12:00 AM · 11d ago · 1 article · 1 source · development 1 of 2

Evangelos Georganas, Alexander Heinecke, and Pradeep Dubey post a preprint describing a method to achieve sub-1.585-bit storage for ternary models, improving over the conventional 1.625 bits per weight using five-trit packing.

“Ternary Large Language Models (LLM) store every weight as one of three symbols {−1,0,+1}, so the cost of a ternary model is conventionally referenced to the information-theoretic log₂3 ≈ 1.585 bits per weight.”

Evangelos Georganas, Alexander Heinecke, Pradeep Dubey, Paper authors · rss ↗

Evangelos Georganas Researcher, paper authorAlexander Heinecke Researcher, paper authorPradeep Dubey Researcher, paper author

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1Paper on ternary LLM compression…2Paper surfaces on Hacker News frontpage
Sep 16Sep 17Sep 18Sep 19Sep 20Sep 21Sep 22Sep 23Sep 24Sep 25yesterdaynow · 7:57 PM ET

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