activity
20242026
most citedMulti-Perspective Stance Detection

12 citations · 19 across the 7 of their papers we have counts for

collaborators

8 papers

cs.CL2026

From Plausible to Actionable: A Position on LLM Self-Explanations

Elize Herrewijnen, Benedetta Muscato, Gizem Gezici +1

Large Language Models (LLMs) can generate natural language explanations that rationalize their own decisions, a phenomenon commonly referred to as self-explanations. Such explanati…

cs.CL2026

Disagreeing Rationales: Rethinking Classification and Explainability Evaluation in Hate Speech Detection

Benedetta Muscato, Beiduo Chen, Gizem Gezici +2

Human disagreement is ubiquitous and well-known in labeling. However, variation in explanations, captured through token-level human rationales, remains far less explored. At the sa…

cs.CL2025

Perspectives in Play: A Multi-Perspective Approach for More Inclusive NLP Systems

Benedetta Muscato, Lucia Passaro, Gizem Gezici +1

In the realm of Natural Language Processing (NLP), common approaches for handling human disagreement consist of aggregating annotators' viewpoints to establish a single ground trut…

cs.IR2025★ 2 cited

Hybrid Retrieval for Hallucination Mitigation in Large Language Models: A Comparative Analysis

Chandana Sree Mala, Gizem Gezici, Fosca Giannotti

Large Language Models (LLMs) excel in language comprehension and generation but are prone to hallucinations, producing factually incorrect or unsupported outputs. Retrieval Augment…

cs.CL2025

Embracing Diversity: A Multi-Perspective Approach with Soft Labels

Benedetta Muscato, Praveen Bushipaka, Gizem Gezici +3

Prior studies show that adopting the annotation diversity shaped by different backgrounds and life experiences and incorporating them into the model learning, i.e. multi-perspectiv…

cs.CL2024★ 12 cited

Multi-Perspective Stance Detection

Benedetta Muscato, Praveen Bushipaka, Gizem Gezici +2

Subjective NLP tasks usually rely on human annotations provided by multiple annotators, whose judgments may vary due to their diverse backgrounds and life experiences. Traditional…