3 citations · 10 across the 18 of their papers we have counts for
6 papers · 1 filter
JudgeBlender: Ensembling Judgments for Automatic Relevance Assessment
Hossein A. Rahmani, Emine Yilmaz, Nick Craswell +1
The effective training and evaluation of retrieval systems require a substantial amount of relevance judgments, which are traditionally collected from human assessors -- a process…
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…
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…
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…
Understanding the Role of User Profile in the Personalization of Large Language Models
Bin Wu, Zhengyan Shi, Hossein A. Rahmani +2
Utilizing user profiles to personalize Large Language Models (LLMs) has been shown to enhance the performance on a wide range of tasks. However, the precise role of user profiles a…
Synthetic Test Collections for Retrieval Evaluation
Hossein A. Rahmani, Nick Craswell, Emine Yilmaz +2
Test collections play a vital role in evaluation of information retrieval (IR) systems. Obtaining a diverse set of user queries for test collection construction can be challenging,…