arXiv — NLP / Computation & Language · · 3 min read

Unreliable Narrator Framing as a Cost-effective Mechanism for Satire Explanation of Australian and American Satirical News

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Computer Science > Computation and Language

arXiv:2610.12863 (cs)
[Submitted on 9 Oct 2026]

Title:Unreliable Narrator Framing as a Cost-effective Mechanism for Satire Explanation of Australian and American Satirical News

View a PDF of the paper titled Unreliable Narrator Framing as a Cost-effective Mechanism for Satire Explanation of Australian and American Satirical News, by Kanay Gupta and 2 other authors
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Abstract:Satirical news is a unique form of misinformation: it is intended to be humorous by the original publication source but can be misinterpreted. Explanation of satirical news articles is challenging because recent and local context needs to be incorporated. This is a pilot study that explores explanation generation for satirical news articles from Australia and compares them alongside those from USA. The paper demonstrates that framing explanations on unreliable narrator theory on open-weights models can be a feasible, cost-effective alternative to frontier models. We find that models identify the satirical tropes more accurately on the American source than the Australian one. This work results in a novel dataset and an evaluation benchmark for satirical explanation.
Comments: 4 content pages + references, appendix; ACL Stylesheet; Under review
Subjects: Computation and Language (cs.CL)
Cite as: arXiv:2610.12863 [cs.CL]
  (or arXiv:2610.12863v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2610.12863
arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Aditya Joshi [view email]
[v1] Fri, 9 Oct 2026 01:41:47 UTC (37 KB)
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