Ranked List Truncation for Large Language Model-based Re-Ranking-Reference-Cited by-同舟云学术

Ranked List Truncation for Large Language Model-based Re-Ranking

Published:2024-07-10 Issue: Volume: Page:141-151
ISSN:
Container-title:Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval
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Author:

Meng Chuan¹^ORCID,Arabzadeh Negar²^ORCID,Askari Arian³^ORCID,Aliannejadi Mohammad⁴^ORCID,de Rijke Maarten¹^ORCID

Affiliation:

1. University of Amsterdam, Amsterdam, Netherlands

2. University of Waterloo, Waterloo, Canada

3. Leiden University, Leiden, Netherlands

4. University of Amsterdam, Amstedam, Netherlands

Funder

Dutch Research Council (NWO)

European UnionðÄôs Horizon Europe research and innovation program

Dutch Research Council (NWO), DPG Media, RTL, and the Dutch Ministry of Economic Affairs and Climate Policy (EZK)

Netherlands Organisation for Scientific Research

China Scholarship Council (CSC)

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3626772.3657864

Reference67 articles.

1. Zahra Abbasiantaeb, Chuan Meng, David Rau, Antonis Krasakis, Hossein A Rahmani, and Mohammad Aliannejadi. 2023. LLM-based Retrieval and Generation Pipelines for TREC Interactive Knowledge Assistance Track (iKAT) 2023. In TREC.

2. Negar Arabzadeh, Chuan Meng, Mohammad Aliannejadi, and Ebrahim Bagheri. 2024. Query Performance Prediction: From Fundamentals to Advanced Techniques. In ECIR. Springer, 381--388.

3. Avi Arampatzis Jaap Kamps and Stephen Robertson. 2009. Where to Stop Reading a Ranked List? Threshold Optimization using Truncated Score Distributions. In SIGIR. 524--531.

4. Nima Asadi and Jimmy Lin. 2013. Effectiveness/Efficiency Tradeoffs for Candidate Generation in Multi-Stage Retrieval Architectures. In SIGIR. 997--1000.

5. Arian Askari, Roxana Petcu, Chuan Meng, Mohammad Aliannejadi, Amin Abolghasemi, Evangelos Kanoulas, and Suzan Verberne. 2024. Self-seeding and Multi-intent Self-instructing LLMs for Generating Intent-aware Information-Seeking dialogs. arXiv preprint arXiv:2402.11633 (2024).

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1. Query Performance Prediction for Conversational Search and Beyond;Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval;2024-07-10