Beyond Centralization: User-Controlled Federated Recommendations in Practice
arXiv 2605.12527•f13e719dfe7a3eb06c0cd264cfe587070d7f7a91a98c6a525d6a086ed070f988
GEOLLM-agentsMLPRAGXRootDcontextual-retrievalconversational-recommendersdynamic-content-expirationecosystem-influenceembeddingsenterprise-governancefederated-learninggenerative-recommendationimage-retrievalinformation-retrievalmodel-distillationmultilingual-embeddingsopen-sourceprivacy-preservingprofile-generationrecommender-systemsreproducibilitytheorem-proving-retrievaluser-simulationweb-manipulation
Paper metadata
- arXiv ID
- 2605.12527
- Version
- Not specified by this published record
- Category
- Computer Science — Information Retrieval (cs.IR)
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Evidence and limitations
- Source ID
- arxiv_cs_ir
- Record identifier
- f13e719dfe7a3eb06c0cd264cfe587070d7f7a91a98c6a525d6a086ed070f988
- Enrichment time
- 2026-05-14T08:52:18Z
- AI-assisted enrichment
- Yes
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