Papers by Berk Atıl

2 papers
♪ Something Just Like TRuST ♪ *: Toxicity Recognition of Span and Target (2026.findings-acl)

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Challenge: Toxic language is pervasive online, and because LLMs are trained on web data, it generates such content.
Approach: They propose a large-scale dataset that synthesizes toxicity definitions and an annotation scheme . they use a rigorous human annotation process to evaluate the diversity of the annotations .
Outcome: The proposed model outperforms existing models on three tasks and is not reliable.
Self-Explaining Hate Speech Detection with Moral Rationales (2026.findings-acl)

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Challenge: Existing models for hate speech detection are opaque and rely on surface-level cues. Existing approaches often encode biases originating from training data and annotation processes.
Approach: They propose a framework that integrates moral rationale supervision into training . they propose SMRA for self-explaining hate speech detection .
Outcome: The proposed framework improves performance across binary hate speech detection and multi-label moral sentiment classification.

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