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Recognizing Is Not Reversing: A Controlled Inversion Test of Fact-Preserving News Framing

Paper recorded by Signals 4 on 2026-09-10 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-10 on arXiv · recorded by Signals 4 on 2026-09-11

Category: cs.AI · 人工智能 · first seen 2026-09-11

Abstract

Large language models (LLMs) are increasingly used to analyze and rewrite news, yet current framing studies mainly evaluate generation, detection, or whether rewritten text appears more neutral. They do not directly show whether a model can undo a known framing transformation while keeping the facts fixed. We introduce a controlled inversion test over three established textual realizations of fram

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#119 most recent of 300 cs.AI papers we have recorded · ↑ newer: Beyond Word Error Rate: A Switch Aware Evaluation of ASR and Audio Lan · ↓ older: A Unified Per-Token Gating Family for On-Policy Distillation: FKL/RKL
Cite this page: Recognizing Is Not Reversing: A Controlled Inversion Test of Fact-Preserving News Framing: the #119 most recent of 300 cs.AI papers we have recorded (as of 2026-09-10). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/recognizing-is-not-reversing-a-controlled-inversion-test-of-fact-preserving-news.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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