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It Takes Two to Match: Co-Evolving Generative Retriever with Reinforcement Learning research paper by Apple, 2026

Apple · Sep 1, 2026 · Retrieval and data · 1 citations · 65 upvotes · unverified

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What it shows

CoGR trains LLMs to generate compact keywords for both queries and items, enabling direct inverted-index retrieval optimized via co-evolving reinforcement learning.

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

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About this paper
Authors
Runpeng Dai, Kaili Huang, Changsung Kang and 1 more
arXiv
2609.00638 · PDF
Citations
1, 0 influential · Semantic Scholar
Upvotes
65 · Hugging Face
Lab
Apple · on Companies · on Quarterly · on Paydays · on TechConf

Changes

What changed
Influential citationsfirst count: 0Sep 25, 2026
Citationsfirst count: 1Sep 25, 2026
New paperFound by the weekly scan, unverifiedSep 25, 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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