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Look Before You Leap: Factual Decoding with Internal Attribution Signals

Paper recorded by Signals 4 on 2026-09-14 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-14 on arXiv · recorded by Signals 4 on 2026-09-15

Category: cs.CL · 自然语言处理 · first seen 2026-09-15

Abstract

Hallucination remains a critical challenge in large language models (LLMs), where early factual errors compound through autoregressive generation in a snowballing effect that neither post-hoc correction nor weight-level intervention can effectively preempt. We propose DescaPE (DEcoding Signal Control Against Path Error-snowballing), a decoding framework that leverages internal model signals to sup

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#46 most recent of 186 cs.CL papers we have recorded · ↑ newer: Sequential Adapter Stacking for Cross-Lingual Low-Resource ASR · ↓ older: Merging the Knowledge of LLMs for Automatic Speech Recognition
Cite this page: Look Before You Leap: Factual Decoding with Internal Attribution Signals: the #46 most recent of 186 cs.CL papers we have recorded (as of 2026-09-14). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/look-before-you-leap-factual-decoding-with-internal-attribution-signals.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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