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20242026
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cs.IR2025

Demographically-Inspired Query Variants Using an LLM

Marwah Alaofi, Nicola Ferro, Paul Thomas +2

This study proposes a method to diversify queries in existing test collections to reflect some of the diversity of search engine users, aligning with an earlier vision of an 'ideal…

cs.IR2025

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

SynDL: A Large-Scale Synthetic Test Collection for Passage Retrieval

Hossein A. Rahmani, Xi Wang, Emine Yilmaz +3

Large-scale test collections play a crucial role in Information Retrieval (IR) research. However, according to the Cranfield paradigm and the research into publicly available datas…

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

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…