13 papers
LLM Safety Alignment in Low-Resource Languages: A Systematic Literature Review
Valdini Douglace Lemofouet, Blessing Ngozi Uzor, Paula Chikaodinaka Anyanwu +9
Large Language Models (LLMs) have achieved substantial progress in safety alignment, yet their safety guarantees remain significantly weaker in low-resource and multilingual settin…
SemEval-2026 Task 9: Detecting Multilingual, Multicultural and Multievent Online Polarization
Usman Naseem, Robert Geislinger, Juan Ren +31
We present SemEval-2026 Task 9, a shared task on online polarization detection, covering 22 languages and comprising over 110K annotated instances. Each data instance is multi-labe…
Do Images Clarify? A Study on the Effect of Images on Clarifying Questions in Conversational Search
Clemencia Siro, Zahra Abbasiantaeb, Yifei Yuan +2
Conversational search systems increasingly employ clarifying questions to refine user queries and improve the search experience. Previous studies have demonstrated the usefulness o…
Learning to Judge: LLMs Designing and Applying Evaluation Rubrics
Clemencia Siro, Pourya Aliannejadi, Mohammad Aliannejadi
Large language models (LLMs) are increasingly used as evaluators for natural language generation, applying human-defined rubrics to assess system outputs. However, human rubrics ar…
Judging the Judges: A Collection of LLM-Generated Relevance Judgements
Hossein A. Rahmani, Clemencia Siro, Mohammad Aliannejadi +6
Using Large Language Models (LLMs) for relevance assessments offers promising opportunities to improve Information Retrieval (IR), Natural Language Processing (NLP), and related fi…
Multi-Turn Multi-Modal Question Clarification for Enhanced Conversational Understanding
Kimia Ramezan, Alireza Amiri Bavandpour, Yifei Yuan +2
Conversational query clarification enables users to refine their search queries through interactive dialogue, improving search effectiveness. Traditional approaches rely on text-ba…