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Optimizing What Matters: AUC-Driven Learning for Robust Neural Retrieval research paper by ServiceNow, 2025

ServiceNow · Sep 30, 2025 · Retrieval and data · 4 upvotes · unverified 12 months ago

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What it shows

A new training objective, MW loss, is introduced to improve retriever calibration and ranking quality by directly optimizing the Area under the ROC Curve (AUC), outperforming Contrastive Loss in retrieval-augmented generation tasks.

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

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About this paper
Authors
Nima Sheikholeslami, Erfan Hosseini, Patrice Bechard and 2 more
arXiv
2510.00137 · PDF
Citations
Not counted yet · Semantic Scholar
Upvotes
4 · Hugging Face
Lab
ServiceNow · on Companies · on Acquisitions · on Quarterly · on Paydays · on TechConf

Changes

What changed
New paperFound by the weekly scan, unverifiedSep 26, 2026today

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