How Are LLMs Mitigating Stereotyping Harms? Learning from Search Engine Studies

16 July 2024

Papers citing "How Are LLMs Mitigating Stereotyping Harms? Learning from Search Engine Studies"

8 / 8 papers shown

Title
Personalisation or Prejudice? Addressing Geographic Bias in Hate Speech Detection using Debias Tuning in Large Language Models Paloma Piot Patricia Martín-Rodilla Javier Parapar 36 0 0 04 May 2025
Speak Out of Turn: Safety Vulnerability of Large Language Models in Multi-turn Dialogue Zhenhong Zhou Jiuyang Xiang Haopeng Chen Quan Liu Zherui Li Sen Su 21 6 0 27 Feb 2024
"I'm sorry to hear that": Finding New Biases in Language Models with a Holistic Descriptor Dataset Eric Michael Smith Melissa Hall Melanie Kambadur Eleonora Presani Adina Williams 53 128 0 18 May 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
BBQ: A Hand-Built Bias Benchmark for Question Answering Alicia Parrish Angelica Chen Nikita Nangia Vishakh Padmakumar Jason Phang Jana Thompson Phu Mon Htut Sam Bowman 200 235 0 15 Oct 2021
Stepmothers are mean and academics are pretentious: What do pretrained language models learn about you? Rochelle Choenni Ekaterina Shutova R. Rooij 69 18 0 21 Sep 2021
Disembodied Machine Learning: On the Illusion of Objectivity in NLP Zeerak Talat Smarika Lulz Joachim Bingel Isabelle Augenstein 77 47 0 28 Jan 2021
The Woman Worked as a Babysitter: On Biases in Language Generation Emily Sheng Kai-Wei Chang Premkumar Natarajan Nanyun Peng 190 607 0 03 Sep 2019