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LLM Targeted Underperformance Disproportionately Impacts Vulnerable
  Users

LLM Targeted Underperformance Disproportionately Impacts Vulnerable Users

25 June 2024
Elinor Poole-Dayan
Deb Roy
Jad Kabbara
ArXiv (abs)PDFHTML

Papers citing "LLM Targeted Underperformance Disproportionately Impacts Vulnerable Users"

5 / 5 papers shown
Title
Unequal Opportunities: Examining the Bias in Geographical Recommendations by Large Language Models
Unequal Opportunities: Examining the Bias in Geographical Recommendations by Large Language Models
Shiran Dudy
Thulasi Tholeti
R. Ramachandranpillai
Muhammad Ali
Toby Jia-Jun Li
Ricardo Baeza-Yates
107
1
0
16 Mar 2025
Personal LLM Agents: Insights and Survey about the Capability,
  Efficiency and Security
Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security
Yuanchun Li
Hao Wen
Weijun Wang
Xiangyu Li
Yizhen Yuan
...
Zhijun Li
Peng Li
Yang Liu
Yaqiong Zhang
Yunxin Liu
LLMAG
86
189
0
10 Jan 2024
Towards Understanding Sycophancy in Language Models
Towards Understanding Sycophancy in Language Models
Mrinank Sharma
Meg Tong
Tomasz Korbak
David Duvenaud
Amanda Askell
...
Oliver Rausch
Nicholas Schiefer
Da Yan
Miranda Zhang
Ethan Perez
354
244
0
20 Oct 2023
Training language models to follow instructions with human feedback
Training language models to follow instructions with human feedback
Long Ouyang
Jeff Wu
Xu Jiang
Diogo Almeida
Carroll L. Wainwright
...
Amanda Askell
Peter Welinder
Paul Christiano
Jan Leike
Ryan J. Lowe
OSLMALM
888
13,207
0
04 Mar 2022
Red Teaming Language Models with Language Models
Red Teaming Language Models with Language Models
Ethan Perez
Saffron Huang
Francis Song
Trevor Cai
Roman Ring
John Aslanides
Amelia Glaese
Nat McAleese
G. Irving
AAML
183
668
0
07 Feb 2022
1