Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models research paper by Snowflake, 2024

Snowflake · May 8, 2024 · Retrieval and data · 80 citations · 2 upvotes

Open text embedding models from 22M to 334M parameters that led MTEB retrieval for their size at release.

Summarised by hand from the abstract.

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About this paper

Authors: Luke Merrick, Danmei Xu, Gaurav Nuti and 1 more
arXiv: 2405.05374 · PDF
Venue: arXiv.org
Citations: 80, 9 influential · Semantic Scholar
Upvotes: 2 · Hugging Face
Lab: Snowflake · on Companies · on Acquisitions · on Quarterly · on Paydays · on Releases · on TechConf

Changes

Date	What changed
Sep 24, 2026	New paperAdded to the listSep 24, 2026

Sources: each lab's own papers and arXiv, with citation and upvote counts from Semantic Scholar and Hugging Face. One-line summaries are for orientation, not a substitute for the paper. Logos via logo.dev; trademarks belong to their owners.

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