ADEPT: A DEbiasing PrompT Framework

ADEPT: A DEbiasing PrompT Framework

10 November 2022

Heng Ji

Papers citing "ADEPT: A DEbiasing PrompT Framework"

10 / 10 papers shown

Title
Investigating and Mitigating Stereotype-aware Unfairness in LLM-based Recommendations Zihuai Zhao Wenqi Fan Yao Wu Qing Li 75 1 0 05 Apr 2025
No Free Lunch: Retrieval-Augmented Generation Undermines Fairness in LLMs, Even for Vigilant Users Mengxuan Hu Hongyi Wu Zihan Guan Ronghang Zhu Dongliang Guo Daiqing Qi Sheng Li SILM 33 3 0 10 Oct 2024
Collapsed Language Models Promote Fairness Jingxuan Xu Wuyang Chen Linyi Li Yao Zhao Yunchao Wei 39 0 0 06 Oct 2024
A Survey on Fairness in Large Language Models Yingji Li Mengnan Du Rui Song Xin Wang Ying Wang ALM 37 59 0 20 Aug 2023
P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks Xiao Liu Kaixuan Ji Yicheng Fu Weng Lam Tam Zhengxiao Du Zhilin Yang Jie Tang VLM 236 805 0 14 Oct 2021
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 280 3,843 0 18 Apr 2021
Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP Timo Schick Sahana Udupa Hinrich Schütze 257 374 0 28 Feb 2021
Debiasing Pre-trained Contextualised Embeddings Masahiro Kaneko Danushka Bollegala 210 138 0 23 Jan 2021
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 294 6,943 0 20 Apr 2018
Efficient Estimation of Word Representations in Vector Space Tomáš Mikolov Kai Chen G. Corrado J. Dean 3DV 228 31,244 0 16 Jan 2013