activity
20212026
most citedBeyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

565 citations · 607 across the 19 of their papers we have counts for

collaborators

21 papers

cs.CL2026

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…

cs.CL2026

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…

cs.CL2026

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…

cs.CL2026

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…

cs.CL2026★ 1 cited

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…

cs.CL2026

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…

cs.IR2025★ 2 cited

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…

cs.IR2025

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…

cs.CL2024★ 1 cited

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…

cs.IR2024

LLMJudge: LLMs for Relevance Judgments

Hossein A. Rahmani, Emine Yilmaz, Nick Craswell +6

The LLMJudge challenge is organized as part of the LLM4Eval workshop at SIGIR 2024. Test collections are essential for evaluating information retrieval (IR) systems. The evaluation…

cs.IR2024★ 2 cited

Report on the 1st Workshop on Large Language Model for Evaluation in Information Retrieval (LLM4Eval 2024) at SIGIR 2024

Hossein A. Rahmani, Clemencia Siro, Mohammad Aliannejadi +6

The first edition of the workshop on Large Language Model for Evaluation in Information Retrieval (LLM4Eval 2024) took place in July 2024, co-located with the ACM SIGIR Conference…

cs.IR2024★ 3 cited

Rethinking the Evaluation of Dialogue Systems: Effects of User Feedback on Crowdworkers and LLMs

Clemencia Siro, Mohammad Aliannejadi, Maarten de Rijke

In ad-hoc retrieval, evaluation relies heavily on user actions, including implicit feedback. In a conversational setting such signals are usually unavailable due to the nature of t…

cs.CL2024

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…

cs.CL2024★ 2 cited

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…

cs.CL2023

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…

cs.CL2023★ 8 cited

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…

cs.CL2023★ 4 cited

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…

cs.CL2023

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…

cs.CL2022★ 565 cited

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…

cs.IR2022★ 19 cited

Understanding User Satisfaction with Task-oriented Dialogue Systems

Clemencia Siro, Mohammad Aliannejadi, Maarten de Rijke

Dialogue systems are evaluated depending on their type and purpose. Two categories are often distinguished: (1) task-oriented dialogue systems (TDS), which are typically evaluat…

cs.CL2021

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…