565 citations · 607 across the 19 of their papers we have counts for
15 papers · 1 filter
When More Metadata Misleads: Probing Field-Level Grounding in LLM-Generated Museum Descriptions
Clemencia Siro, Laura Hollink
Metadata-conditioned generation is often framed as a data-to-text task in which additional input fields should improve grounding. Museum description generation challenges this assu…
Prompting Strategy Effects Depend on the Judge: A Multilingual Study of LLM-as-a-Judge Robustness
Asal Mehrabi, Mohammad Aliannejadi, Clemencia Siro
LLM-as-a-Judge evaluation is increasingly applied to multilingual tasks, yet prompting strategies such as Chain-of-Thought and Role Conditioning are recommended based solely on Eng…
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…
AGENT-CQ: Automatic Generation and Evaluation of Clarifying Questions for Conversational Search with LLMs
Clemencia Siro, Yifei Yuan, Mohammad Aliannejadi +1
Generating diverse and effective clarifying questions is crucial for improving query understanding and retrieval performance in open-domain conversational search (CS) systems. We p…
Context Does Matter: Implications for Crowdsourced Evaluation Labels in Task-Oriented Dialogue Systems
Clemencia Siro, Mohammad Aliannejadi, Maarten de Rijke
Crowdsourced labels play a crucial role in evaluating task-oriented dialogue systems (TDSs). Obtaining high-quality and consistent ground-truth labels from annotators presents chal…
Asking Multimodal Clarifying Questions in Mixed-Initiative Conversational Search
Yifei Yuan, Clemencia Siro, Mohammad Aliannejadi +2
In mixed-initiative conversational search systems, clarifying questions are used to help users who struggle to express their intentions in a single query. These questions aim to un…
AfriMTE and AfriCOMET: Enhancing COMET to Embrace Under-resourced African Languages
Jiayi Wang, David Ifeoluwa Adelani, Sweta Agrawal +55
Despite the recent progress on scaling multilingual machine translation (MT) to several under-resourced African languages, accurately measuring this progress remains challenging, s…
AfriQA: Cross-lingual Open-Retrieval Question Answering for African Languages
Odunayo Ogundepo, Tajuddeen R. Gwadabe, Clara E. Rivera +49
African languages have far less in-language content available digitally, making it challenging for question answering systems to satisfy the information needs of users. Cross-lingu…
MasakhaNEWS: News Topic Classification for African languages
David Ifeoluwa Adelani, Marek Masiak, Israel Abebe Azime +62
African languages are severely under-represented in NLP research due to lack of datasets covering several NLP tasks. While there are individual language specific datasets that are…
Evaluating the Robustness of Machine Reading Comprehension Models to Low Resource Entity Renaming
Clemencia Siro, Tunde Oluwaseyi Ajayi
Question answering (QA) models have shown compelling results in the task of Machine Reading Comprehension (MRC). Recently these systems have proved to perform better than humans on…
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao +448
Language models demonstrate both quantitative improvement and new qualitative capabilities with increasing scale. Despite their potentially transformative impact, these new capabil…
MasakhaNER: Named Entity Recognition for African Languages
David Ifeoluwa Adelani, Jade Abbott, Graham Neubig +58
We take a step towards addressing the under-representation of the African continent in NLP research by creating the first large publicly available high-quality dataset for named en…