A Survey on Natural Language Counterfactual Generation

A Survey on Natural Language Counterfactual Generation

4 July 2024

Papers citing "A Survey on Natural Language Counterfactual Generation"

12 / 12 papers shown

Title
Counterfactual Token Generation in Large Language Models Ivi Chatzi N. C. Benz Eleni Straitouri Stratis Tsirtsis Manuel Gomez Rodriguez LRM 34 3 0 25 Sep 2024
Do Large Language Models Perform the Way People Expect? Measuring the Human Generalization Function Keyon Vafa Ashesh Rambachan S. Mullainathan ELM ALM 13 11 0 03 Jun 2024
LLMs for Generating and Evaluating Counterfactuals: A Comprehensive Study Van Bach Nguyen Paul Youssef Jorg Schlotterer Christin Seifert 37 14 0 26 Apr 2024
Explore Spurious Correlations at the Concept Level in Language Models for Text Classification Yuhang Zhou Paiheng Xu Xiaoyu Liu Bang An Wei Ai Furong Huang LRM 71 20 0 15 Nov 2023
Consistent Multi-Granular Rationale Extraction for Explainable Multi-hop Fact Verification Jiasheng Si Yingjie Zhu Deyu Zhou AAML 24 3 0 16 May 2023
NeuroCounterfactuals: Beyond Minimal-Edit Counterfactuals for Richer Data Augmentation Phillip Howard Gadi Singer Vasudev Lal Yejin Choi Swabha Swayamdipta CML 48 25 0 22 Oct 2022
CORE: A Retrieve-then-Edit Framework for Counterfactual Data Generation Tanay Dixit Bhargavi Paranjape Hannaneh Hajishirzi Luke Zettlemoyer SyDa 133 23 0 10 Oct 2022
CrossAug: A Contrastive Data Augmentation Method for Debiasing Fact Verification Models Minwoo Lee Seungpil Won Juae Kim Hwanhee Lee Cheoneum Park Kyomin Jung 36 29 0 30 Sep 2021
Entity-Based Knowledge Conflicts in Question Answering Shayne Longpre Kartik Perisetla Anthony Chen Nikhil Ramesh Chris DuBois Sameer Singh HILM 241 236 0 10 Sep 2021
Tailor: Generating and Perturbing Text with Semantic Controls Alexis Ross Tongshuang Wu Hao Peng Matthew E. Peters Matt Gardner 134 77 0 15 Jul 2021
Controlling Text Edition by Changing Answers of Specific Questions Lei Sha Patrick Hohenecker Thomas Lukasiewicz 108 7 0 23 May 2021
Linguistically-Informed Transformations (LIT): A Method for Automatically Generating Contrast Sets Chuanrong Li Lin Shengshuo Leo Z. Liu Xinyi Wu Xuhui Zhou Shane Steinert-Threlkeld VLM 128 38 0 16 Oct 2020