The Impact of Debiasing on the Performance of Language Models in Downstream Tasks is Underestimated

16 September 2023

Papers citing "The Impact of Debiasing on the Performance of Language Models in Downstream Tasks is Underestimated"

6 / 6 papers shown

Title
Likelihood-based Mitigation of Evaluation Bias in Large Language Models Masanari Ohi Masahiro Kaneko Ryuto Koike Mengsay Loem Naoaki Okazaki 16 4 0 25 Feb 2024
Mitigating Biases of Large Language Models in Stance Detection with Counterfactual Augmented Calibration Ang Li Jingqian Zhao Bin Liang Lin Gui Hui Wang Xi Zeng Xingwei Liang Kam-Fai Wong Ruifeng Xu 30 0 0 22 Feb 2024
The Gaps between Pre-train and Downstream Settings in Bias Evaluation and Debiasing Masahiro Kaneko Danushka Bollegala Timothy Baldwin 19 3 0 16 Jan 2024
Solving NLP Problems through Human-System Collaboration: A Discussion-based Approach Masahiro Kaneko Graham Neubig Naoaki Okazaki 25 6 0 19 May 2023
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 6,927 0 20 Apr 2018