activity
20242026
collaborators

5 papers

cs.IR2026

LLM-based relevance assessment still can't replace human relevance assessment

Charles L. A. Clarke, Laura Dietz

The use of large language models (LLMs) for relevance assessment in information retrieval has gained significant attention, with recent studies suggesting that LLM-based judgments…

cs.IR2025

LLM-Evaluation Tropes: Perspectives on the Validity of LLM-Evaluations

Laura Dietz, Oleg Zendel, Peter Bailey +6

Large Language Models (LLMs) are increasingly used to evaluate information retrieval (IR) systems, generating relevance judgments traditionally made by human assessors. Recent empi…

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.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…