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Counterfactual samples constructing and training for commonsense statements estimation

delete2025-12-18
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PRE
AI
C
Chong Liu
Z
Zaiwen Feng
Z
Zhenyun Deng
刘琳 (Lin Liu)
J
Jiuyong Li
R
Ruifang Zhai
D
Debo Cheng
L
Li Qin
DOI:10.1016/j.ipm.2025.104563delete
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Abstract

Abstract

En 中文
• Introduces CCSG, a novel framework enhancing PE models with counterfactual reasoning. • Leverages SCMs to analyze and mitigate commonsense biases in language model predictions. • Achieves state-of-the-art results on 9 datasets, outperforming GPT-4 and VERA benchmarks.

Journal

I
Information Processing and Management
IF:
6.9
Papers:
5.2K
Citations:
1.4W

Organization

H
Huazhong Agricultural University
Scholars:
3.2W
Papers: 1.8W
Citations: 3.5W
U
university of cambridge
Scholars:
6.8K
Papers: 3.2K
Citations: 3
H
Hainan University
Scholars:
2.0W
Papers: 1.2W
Citations: 1.9W
U
University of South Australia
Scholars:
9.0K
Papers: 1.1W
Citations: 1.6W
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