RankGraph-2: Lifecycle Co-Design for Billion-Node Graph Learning in Recommendation
arXiv 2606.18379•f799da114d7afa471b30e19b0b2f19c273b10bd9352cde84d9ba555ea4d01c5b
AutoML for recommender systemsLensKit-AutoMLM-head rescalingMeta deploymentQuerit-RerankerRankGraph-2SAERecSHIFTSPLADEdense retrievalgraph learninginformation retrievalinterpretable intentslabel-efficient adaptation','model merging','Hugging Face modellanguage bias mitigationmultilingual IRpersonalized PageRankpopularity bias correctionrecommender systemsrerankerresidual quantizationsparse autoencodersparse retrievalsubsamplingtraining stability
Paper metadata
- arXiv ID
- 2606.18379
- 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
- f799da114d7afa471b30e19b0b2f19c273b10bd9352cde84d9ba555ea4d01c5b
- Enrichment time
- 2026-06-18T08:52:20Z
- AI-assisted enrichment
- Yes
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