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Improving JEV Entailment Reranking with Span Readouts and Selective Adaptation

Paper recorded by Signals 4 on 2026-10-26 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-26 on arXiv · recorded by Signals 4 on 2026-10-27

Category: cs.CL · 自然语言处理 · first seen 2026-10-27

Abstract

JEV decision models pair a language model backbone with a lightweight scoring head to select among natural-language options. Direct selection compares candidate answers within one request, whereas entailment reranking evaluates each candidate in a separate natural language inference (NLI) request over fixed relation options. We examine whether the readout and adaptation choices used for direct sel

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#145 most recent of 660 cs.CL papers we have recorded · ↑ newer: Evaluating DeepSeek V4.1 Flash-1017 for loss of control and harmful ma · ↓ older: Offline Language-Based Support System for Tactical Decision-Making in
Cite this page: Improving JEV Entailment Reranking with Span Readouts and Selective Adaptation: the #145 most recent of 660 cs.CL papers we have recorded (as of 2026-10-26). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/improving-jev-entailment-reranking-with-span-readouts-and-selective-adaptation.html
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