Versioned Late Materialization for Ultra-Long Sequence Training in Recommendation Systems at Scale
2026-04-29T08:52:24Z•c55086269c72091f5410c3fc7344e6e73942cf5fd6f12ff16aa3dfea3896448a
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
This record may overlap with other records. Its enrichment can be incomplete or wrong, and machine assistance was used. Validate consequential decisions against the linked source and your own environment.