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Sarcasm hinders Turkish hate speech detection in LLMs and fine-tuned models

A new research paper introduces SarcasTraps, a dataset designed to evaluate how sarcasm impacts the detection of hate speech in Turkish. The study found that sarcasm significantly challenges both fine-tuned models like BERTurk and XLM-RoBERTa, as well as large language models such as GPT-4.1 and Llama 3.3 70B Instruct, leading to reduced recall or precision when identifying sarcastic hate speech. AI

IMPACT Highlights challenges in AI's ability to understand nuanced language like sarcasm for safety applications.

RANK_REASON Research paper introducing a new dataset and evaluation of models on that dataset. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Sarcasm hinders Turkish hate speech detection in LLMs and fine-tuned models

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Research paper introducing a new dataset and evaluation of models on that dataset. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Niyazi Ahmet Metin, Dilara Kek\"ull\"uo\u{g}lu ·

    SarcasTraps: Effect of Sarcasm on Turkish Hate Speech Detection

    arXiv:2610.16957v1 Announce Type: cross Abstract: Standard hate speech detection datasets often emphasize explicit harmful language, but directed harm can also be expressed indirectly, without clearly hateful wording. Sarcasm is one such form of indirect expression, as it can con…