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FastContext: Training Efficient Repository Explorer for Coding Agents research paper by Microsoft, 2026

Microsoft · Inference and efficiency · Jun 12, 2026 · 5 citations · 94 upvotes · unverified

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What it shows

FastContext separates repository exploration from code solving in LLM agents using specialized exploration models that reduce token consumption and improve resolution rates.

By Shaoqiu Zhang, Maoquan Wang, Yuling Shi and 5 more · arXiv 2606.14066 · PDF

UnverifiedHugging Face's summary; not yet checked by hand.

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About this paper
Venue
arXiv.org
Citations
5, 1 influential · Semantic Scholar
Upvotes
94 · Hugging Face
Lab
Microsoft · on Companies · on Acquisitions · on Quarterly · on Paydays · on Releases · on TechConf

Changes

CitationsNov 2, 2026Citations rose from 4 to 5.
CitationsOct 12, 2026Influential citations rose from 0 to 1.
CitationsOct 12, 2026Citations rose from 3 to 4.
CitationsSep 25, 2026A first count of 0 influential citations.
CitationsSep 25, 2026A first count of 3 citations.
New paperSep 25, 2026Found by the weekly Hugging Face scan; not yet checked by hand.