Versioned Late Materialization for Ultra-Long Sequence Training in Recommendation Systems at Scale

2026-04-29T08:52:24Zc55086269c72091f5410c3fc7344e6e73942cf5fd6f12ff16aa3dfea3896448a
access-controladversarial-robustnessauditabilitycompliancedata-leakagedata-privacydataset-governanceembeddingshipaamembership-inferencemodel-inversionpiipoisoningragrecommender-systemsreverse-image-searchtraining-data-leakagevector-databaseweb-scraping

What happened

This batch contains research on large-scale recommender/IR engineering and evaluation, with several items raising privacy and ML-security considerations. Notable items: a production-grade health-system semantic search that indexes 166M clinical notes (HIPAA governance claimed) using embeddings and a vector DB; GeoSearch which integrates web-scale reverse image search and web scraping; a "versioned late materialization" system that explicitly addresses Online-to-Offline (O2O) consistency and leakage prevention for ultra-long user interaction histories; and multiple generative/RAG and grounding/

Why it matters

A reviewed impact interpretation has not been published for this record.

Evidence and limitations

Source ID
arxiv_cs_ir
Record identifier
c55086269c72091f5410c3fc7344e6e73942cf5fd6f12ff16aa3dfea3896448a
Enrichment time
2026-04-29T08:52:24Z
AI-assisted enrichment
Yes

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