Unifying Bias and Unfairness in Information Retrieval: A Survey of
Challenges and Opportunities with Large Language Models

Unifying Bias and Unfairness in Information Retrieval: A Survey of Challenges and Opportunities with Large Language Models

17 April 2024

Liang Pang

Jun Xu

Papers citing "Unifying Bias and Unfairness in Information Retrieval: A Survey of Challenges and Opportunities with Large Language Models"

6 / 6 papers shown

Title
Unbiased Evaluation of Large Language Models from a Causal Perspective Meilin Chen Jian Tian Liang Ma Di Xie Weijie Chen Jiang Zhu ALM ELM 52 0 0 10 Feb 2025
Can Large Language Models Be an Alternative to Human Evaluations? Cheng-Han Chiang Hung-yi Lee ALM LM&MA 206 559 0 03 May 2023
Self-Consistency Improves Chain of Thought Reasoning in Language Models Xuezhi Wang Jason W. Wei Dale Schuurmans Quoc Le Ed H. Chi Sharan Narang Aakanksha Chowdhery Denny Zhou ReLM BDL LRM AI4CE 297 3,163 0 21 Mar 2022
Multitask Prompted Training Enables Zero-Shot Task Generalization Victor Sanh Albert Webson Colin Raffel Stephen H. Bach Lintang Sutawika ... T. Bers Stella Biderman Leo Gao Thomas Wolf Alexander M. Rush LRM 203 1,651 0 15 Oct 2021
Low Frequency Names Exhibit Bias and Overfitting in Contextualizing Language Models Robert Wolfe Aylin Caliskan 82 51 0 01 Oct 2021
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 286 4,143 0 23 Aug 2019