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LLM-based Detection of Manipulative Political Narratives

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arXiv:2605. 14354v1 Announce Type: new Abstract: We present a new computational framework for detecting and structuring manipulative political narratives.

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Authors: Sinclair Schneider, Florian Steuber, Gabi Dreo Rodosek
Released: 2026-05-15 (3mo ago)
Topic: Related to current project
Relation to my work: Read next because LLM-based Detection of Manipulative Political Narratives overlaps with clean result "LoRA persona trained on <A> alone emits <B> at 23.5% when a co-trained partner learns <A>...<B>, vs 0% control on Qwen2.5-7B-Instruct (MODERATE confidence)", clean result "Leakage rate is a usable signal for recovering trigger-shaped phrases on Gaperon-1125-1B without knowing the hidden trigger itself (MODERATE confidence)", clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)". Matching terms: text, good, model. Source: arxiv cs.CL (NLP).
arXiv: 2605.14354

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