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Beyond Performance: Quantifying and Mitigating Label Bias in LLMs

Beyond Performance: Quantifying and Mitigating Label Bias in LLMs

4 May 2024
Philipp Benz
Maitreya Patel
ArXivPDFHTML

Papers citing "Beyond Performance: Quantifying and Mitigating Label Bias in LLMs"

15 / 15 papers shown
Title
Through the LLM Looking Glass: A Socratic Self-Assessment of Donkeys, Elephants, and Markets
Through the LLM Looking Glass: A Socratic Self-Assessment of Donkeys, Elephants, and Markets
Molly Kennedy
Ayyoob Imani
Timo Spinde
Hinrich Schütze
45
1
0
20 Mar 2025
Towards AI-assisted Academic Writing
Towards AI-assisted Academic Writing
Daniel J. Liebling
Malcolm Kane
Madeleine Grunde-Mclaughlin
Ian J. Lang
Subhashini Venugopalan
Michael P. Brenner
60
0
0
17 Mar 2025
DOVE: A Large-Scale Multi-Dimensional Predictions Dataset Towards Meaningful LLM Evaluation
Eliya Habba
Ofir Arviv
Itay Itzhak
Yotam Perlitz
Elron Bandel
Leshem Choshen
Michal Shmueli-Scheuer
Gabriel Stanovsky
74
2
0
03 Mar 2025
Aligning Black-box Language Models with Human Judgments
Aligning Black-box Language Models with Human Judgments
Gerrit J. J. van den Burg
Gen Suzuki
Wei Liu
Murat Sensoy
ALM
82
0
0
07 Feb 2025
Improving Model Evaluation using SMART Filtering of Benchmark Datasets
Improving Model Evaluation using SMART Filtering of Benchmark Datasets
Vipul Gupta
Candace Ross
David Pantoja
R. Passonneau
Megan Ung
Adina Williams
76
1
0
26 Oct 2024
Mitigating Selection Bias with Node Pruning and Auxiliary Options
Mitigating Selection Bias with Node Pruning and Auxiliary Options
Hyeong Kyu Choi
Weijie Xu
Chi Xue
Stephanie Eckman
Chandan K. Reddy
29
1
0
27 Sep 2024
Self-Recognition in Language Models
Self-Recognition in Language Models
Tim R. Davidson
Viacheslav Surkov
V. Veselovsky
Giuseppe Russo
Robert West
Çağlar Gülçehre
PILM
248
2
0
09 Jul 2024
Generative Calibration for In-context Learning
Generative Calibration for In-context Learning
Zhongtao Jiang
Yuanzhe Zhang
Cao Liu
Jun Zhao
Kang Liu
167
17
0
16 Oct 2023
Calibrating Factual Knowledge in Pretrained Language Models
Calibrating Factual Knowledge in Pretrained Language Models
Qingxiu Dong
Damai Dai
Yifan Song
Jingjing Xu
Zhifang Sui
Lei Li
KELM
238
82
0
07 Oct 2022
On the Relation between Sensitivity and Accuracy in In-context Learning
On the Relation between Sensitivity and Accuracy in In-context Learning
Yanda Chen
Chen Zhao
Zhou Yu
Kathleen McKeown
He He
182
77
0
16 Sep 2022
Prototypical Calibration for Few-shot Learning of Language Models
Prototypical Calibration for Few-shot Learning of Language Models
Zhixiong Han
Y. Hao
Li Dong
Yutao Sun
Furu Wei
178
52
0
20 May 2022
Fantastically Ordered Prompts and Where to Find Them: Overcoming
  Few-Shot Prompt Order Sensitivity
Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity
Yao Lu
Max Bartolo
Alastair Moore
Sebastian Riedel
Pontus Stenetorp
AILaw
LRM
279
1,124
0
18 Apr 2021
What Makes Good In-Context Examples for GPT-$3$?
What Makes Good In-Context Examples for GPT-333?
Jiachang Liu
Dinghan Shen
Yizhe Zhang
Bill Dolan
Lawrence Carin
Weizhu Chen
AAML
RALM
275
1,312
0
17 Jan 2021
RobustBench: a standardized adversarial robustness benchmark
RobustBench: a standardized adversarial robustness benchmark
Francesco Croce
Maksym Andriushchenko
Vikash Sehwag
Edoardo Debenedetti
Nicolas Flammarion
M. Chiang
Prateek Mittal
Matthias Hein
VLM
231
677
0
19 Oct 2020
A Survey on Bias and Fairness in Machine Learning
A Survey on Bias and Fairness in Machine Learning
Ninareh Mehrabi
Fred Morstatter
N. Saxena
Kristina Lerman
Aram Galstyan
SyDa
FaML
323
4,212
0
23 Aug 2019
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