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

arXiv: https://arxiv.org/abs/2408.05388 · HTML: https://mlsanity.com/paper/2408.05388/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Aug 2024.

## Built on by (most cited first, 8 of 8)

- [Rankers, Judges, and Assistants: Towards Understanding the Interplay of LLMs in Information Retrieval Evaluation](https://mlsanity.com/paper/2503.19092/) (2025)
- [A Human-AI Comparative Analysis of Prompt Sensitivity in LLM-Based Relevance Judgment](https://mlsanity.com/paper/2504.12408/) (2025)
- [Do RAG Systems Really Suffer From Positional Bias?](https://mlsanity.com/paper/2505.15561/) (2025)
- [Conversational Gold: Evaluating Personalized Conversational Search System using Gold Nuggets](https://mlsanity.com/paper/2503.09902/) (2025)
- [Towards Understanding Bias in Synthetic Data for Evaluation](https://mlsanity.com/paper/2506.10301/) (2025)
- [Redefining Retrieval Evaluation in the Era of LLMs](https://mlsanity.com/paper/2510.21440/) (2025)
- [Evaluating Cost-Accuracy Trade-offs in Multimodal Search Relevance Judgements](https://mlsanity.com/paper/2410.19974/) (2024)
- [Semantic Search Evaluation](https://mlsanity.com/paper/2410.21549/) (2024)

## Abstract (arXiv)

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 2024 in the USA (SIGIR 2024). The aim was to bring information retrieval researchers together around the topic of LLMs for evaluation in information retrieval that gathered attention with the advancement of large language models and generative AI. Given the novelty of the topic, the workshop was focused around multi-sided discussions, namely panels and poster sessions of the accepted proceedings papers.