Signals 4 · free daily AI digest

Predictable Failure in Multi-Hop Retrieval: Score-Distributional Confidence Scoring and Abstention

Paper recorded by Signals 4 on 2026-09-18 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-18 on arXiv · recorded by Signals 4 on 2026-09-21

Category: cs.LG · 机器学习 · first seen 2026-09-21

Abstract

Multi-hop retrieval failures are not uniformly distributed across queries: they cluster in structurally predictable subpopulations. We prove two results formalizing this structure. First (CWAR Reducibility): confident-failure reduction is achievable if and only if retrieval features carry mutual information about success, a condition satisfied by LLM-judge pipelines but substantially weaker in den

Read on arXiv →

#2 most recent of 235 cs.LG papers we have recorded · ↑ newer: BrainWideBench: Benchmarking large-scale pretraining and across-animal · ↓ older: Benchmarking World Models for Continual Learning on Compositional Task
Cite this page: Predictable Failure in Multi-Hop Retrieval: Score-Distributional Confidence Scoring and Abstention: the #2 most recent of 235 cs.LG papers we have recorded (as of 2026-09-18). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/predictable-failure-in-multi-hop-retrieval-score-distributional-confidence-scori.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
Related: More cs.LG papers · arXiv signals · All papers · Today in AI
Get 4 AI signals a day by email — free.
Subscribe free → See all plans →
Get 4 AI signals a day by email — free
All models · All repos · By company · Daily editions