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Decision-Oriented Recommendation Reranking: An Empirical Study of Jev

Paper recorded by Signals 4 on 2026-09-30 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-30 on arXiv · recorded by Signals 4 on 2026-10-01

Category: cs.CL · 自然语言处理 · first seen 2026-10-01

Abstract

Large language models (LLMs) have shown promise for recommendation reranking, but their use introduces an important tradeoff between recommendation quality and serving efficiency. We investigate whether a decision-oriented model provides a useful alternative when the reranking task is fundamentally a structured choice among predefined candidate items. Specifically, we conduct a controlled empirica

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#14 most recent of 311 cs.CL papers we have recorded · ↑ newer: EvoDuet: Bilevel Co-Evolution of Web Searching and Task Solving for Sc · ↓ older: Provably Tractable NFA-Constrained Language Generation via HMMs
Cite this page: Decision-Oriented Recommendation Reranking: An Empirical Study of Jev: the #14 most recent of 311 cs.CL papers we have recorded (as of 2026-09-30). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/decision-oriented-recommendation-reranking-an-empirical-study-of-jev.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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