Papers by Lucia Siciliani

2 papers
From Detection to Explanation: Effective Learning Strategies for LLMs in Online Abusive Language Research (2025.coling-main)

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Challenge: Abusive language detection requires commonsense reasoning, world knowledge and linguistic nuances that evolve over time.
Approach: They propose a knowledge-guided version of Llama-2 instruction fine-tuned for multi-class abusive language detection and explanation generation that mitigates bias and generates explanations that are relevant to the text and coherent with human reasoning.
Outcome: The proposed model mitigates bias and generates explanations that are relevant to the text and coherent with human reasoning, with an average 48.76% better alignment with human judgment.
XL-LEXEME: WiC Pretrained Model for Cross-Lingual LEXical sEMantic changE (2023.acl-short)

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Challenge: Existing approaches to the Word in Context task use cross-encoders, which prevent the possibility of deriving comparable word embeddings.
Approach: They propose a Lexical Semantic Change Detection model that extends SBERT, highlighting the target word in the sentence.
Outcome: The proposed model outperforms the state-of-the-art on the multilingual benchmarks for SemEval-2020 Task 1 - Lexical Semantic Change (LSC) Detection and the RuShiftEval shared task.

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