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End-to-End Self-Debiasing Framework for Robust NLU Training

End-to-End Self-Debiasing Framework for Robust NLU Training

5 September 2021
Abbas Ghaddar
Philippe Langlais
Mehdi Rezagholizadeh
Ahmad Rashid
    UQCV
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Papers citing "End-to-End Self-Debiasing Framework for Robust NLU Training"

22 / 22 papers shown
Title
EqualizeIR: Mitigating Linguistic Biases in Retrieval Models
EqualizeIR: Mitigating Linguistic Biases in Retrieval Models
Jiali Cheng
Hadi Amiri
23
1
0
22 Mar 2025
Towards Robust Extractive Question Answering Models: Rethinking the
  Training Methodology
Towards Robust Extractive Question Answering Models: Rethinking the Training Methodology
Son Quoc Tran
Matt Kretchmar
OOD
19
0
0
29 Sep 2024
LLMs Are Biased Towards Output Formats! Systematically Evaluating and Mitigating Output Format Bias of LLMs
LLMs Are Biased Towards Output Formats! Systematically Evaluating and Mitigating Output Format Bias of LLMs
Do Xuan Long
Hai Nguyen Ngoc
Tiviatis Sim
Hieu Dao
Shafiq R. Joty
Kenji Kawaguchi
Nancy F. Chen
Min-Yen Kan
29
7
0
16 Aug 2024
Not Eliminate but Aggregate: Post-Hoc Control over Mixture-of-Experts to
  Address Shortcut Shifts in Natural Language Understanding
Not Eliminate but Aggregate: Post-Hoc Control over Mixture-of-Experts to Address Shortcut Shifts in Natural Language Understanding
Ukyo Honda
Tatsushi Oka
Peinan Zhang
Masato Mita
36
1
0
17 Jun 2024
Explanation based Bias Decoupling Regularization for Natural Language
  Inference
Explanation based Bias Decoupling Regularization for Natural Language Inference
Jianxiang Zang
Hui Liu
16
0
0
20 Apr 2024
Self-Supervised Position Debiasing for Large Language Models
Self-Supervised Position Debiasing for Large Language Models
Zhongkun Liu
Zheng Chen
Mengqi Zhang
Zhaochun Ren
Pengjie Ren
Zhumin Chen
34
1
0
02 Jan 2024
Improving Bias Mitigation through Bias Experts in Natural Language
  Understanding
Improving Bias Mitigation through Bias Experts in Natural Language Understanding
Eojin Jeon
Mingyu Lee
Juhyeong Park
Yeachan Kim
Wing-Lam Mok
SangKeun Lee
11
2
0
06 Dec 2023
A Simple yet Effective Self-Debiasing Framework for Transformer Models
A Simple yet Effective Self-Debiasing Framework for Transformer Models
Xiaoyue Wang
Lijie Wang
Xin Liu
Suhang Wu
Jinsong Su
Huasen Wu
31
3
0
02 Jun 2023
Robust Natural Language Understanding with Residual Attention Debiasing
Robust Natural Language Understanding with Residual Attention Debiasing
Fei Wang
James Y. Huang
Tianyi Yan
Wenxuan Zhou
Muhao Chen
29
10
0
28 May 2023
From Shortcuts to Triggers: Backdoor Defense with Denoised PoE
From Shortcuts to Triggers: Backdoor Defense with Denoised PoE
Qin Liu
Fei Wang
Chaowei Xiao
Muhao Chen
AAML
24
21
0
24 May 2023
DialogVCS: Robust Natural Language Understanding in Dialogue System
  Upgrade
DialogVCS: Robust Natural Language Understanding in Dialogue System Upgrade
Zefan Cai
Xin Zheng
Tianyu Liu
Xu Wang
H. Meng
Jiaqi Han
Gang Yuan
Binghuai Lin
Baobao Chang
Yunbo Cao
14
4
0
24 May 2023
Improving Classifier Robustness through Active Generation of Pairwise
  Counterfactuals
Improving Classifier Robustness through Active Generation of Pairwise Counterfactuals
Ananth Balashankar
Xuezhi Wang
Yao Qin
Ben Packer
Nithum Thain
Jilin Chen
Ed H. Chi
Alex Beutel
15
0
0
22 May 2023
Guide the Learner: Controlling Product of Experts Debiasing Method Based
  on Token Attribution Similarities
Guide the Learner: Controlling Product of Experts Debiasing Method Based on Token Attribution Similarities
Ali Modarressi
Hossein Amirkhani
Mohammad Taher Pilehvar
6
2
0
06 Feb 2023
Feature-Level Debiased Natural Language Understanding
Feature-Level Debiased Natural Language Understanding
Yougang Lyu
Piji Li
Yechang Yang
Maarten de Rijke
Pengjie Ren
Yukun Zhao
Dawei Yin
Z. Ren
23
10
0
11 Dec 2022
A Win-win Deal: Towards Sparse and Robust Pre-trained Language Models
A Win-win Deal: Towards Sparse and Robust Pre-trained Language Models
Yuanxin Liu
Fandong Meng
Zheng Lin
JiangNan Li
Peng Fu
Yanan Cao
Weiping Wang
Jie Zhou
28
4
0
11 Oct 2022
A Survey on Measuring and Mitigating Reasoning Shortcuts in Machine
  Reading Comprehension
A Survey on Measuring and Mitigating Reasoning Shortcuts in Machine Reading Comprehension
Xanh Ho
Johannes Mario Meissner
Saku Sugawara
Akiko Aizawa
OffRL
30
4
0
05 Sep 2022
Generating Data to Mitigate Spurious Correlations in Natural Language
  Inference Datasets
Generating Data to Mitigate Spurious Correlations in Natural Language Inference Datasets
Yuxiang Wu
Matt Gardner
Pontus Stenetorp
Pradeep Dasigi
19
67
0
24 Mar 2022
RAIL-KD: RAndom Intermediate Layer Mapping for Knowledge Distillation
RAIL-KD: RAndom Intermediate Layer Mapping for Knowledge Distillation
Md. Akmal Haidar
Nithin Anchuri
Mehdi Rezagholizadeh
Abbas Ghaddar
Philippe Langlais
Pascal Poupart
27
22
0
21 Sep 2021
Knowledge Distillation with Noisy Labels for Natural Language
  Understanding
Knowledge Distillation with Noisy Labels for Natural Language Understanding
Shivendra Bhardwaj
Abbas Ghaddar
Ahmad Rashid
Khalil Bibi
Cheng-huan Li
A. Ghodsi
Philippe Langlais
Mehdi Rezagholizadeh
19
1
0
21 Sep 2021
How to Select One Among All? An Extensive Empirical Study Towards the
  Robustness of Knowledge Distillation in Natural Language Understanding
How to Select One Among All? An Extensive Empirical Study Towards the Robustness of Knowledge Distillation in Natural Language Understanding
Tianda Li
Ahmad Rashid
A. Jafari
Pranav Sharma
A. Ghodsi
Mehdi Rezagholizadeh
AAML
17
5
0
13 Sep 2021
Towards Zero-Shot Knowledge Distillation for Natural Language Processing
Towards Zero-Shot Knowledge Distillation for Natural Language Processing
Ahmad Rashid
Vasileios Lioutas
Abbas Ghaddar
Mehdi Rezagholizadeh
8
27
0
31 Dec 2020
Hypothesis Only Baselines in Natural Language Inference
Hypothesis Only Baselines in Natural Language Inference
Adam Poliak
Jason Naradowsky
Aparajita Haldar
Rachel Rudinger
Benjamin Van Durme
187
576
0
02 May 2018
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