ChatGPT to Replace Crowdsourcing of Paraphrases for Intent Classification: Higher Diversity and Comparable Model Robustness

22 May 2023

Papers citing "ChatGPT to Replace Crowdsourcing of Paraphrases for Intent Classification: Higher Diversity and Comparable Model Robustness"

6 / 6 papers shown

Title
A Comprehensive Survey on Data Augmentation Zaitian Wang Pengfei Wang Kunpeng Liu Pengyang Wang Yanjie Fu Chang-Tien Lu Charu Aggarwal Jian Pei Yuanchun Zhou ViT 92 18 0 15 May 2024
ConFit: Improving Resume-Job Matching using Data Augmentation and Contrastive Learning Xiao Yu Jinzhong Zhang Zhou Yu 25 1 0 29 Jan 2024
Keeping Users Engaged During Repeated Administration of the Same Questionnaire: Using Large Language Models to Reliably Diversify Questions Hye Sun Yun Mehdi Arjmand Phillip Raymond Sherlock Michael K Paasche-Orlow James W. Griffith Timothy W. Bickmore 8 0 0 21 Nov 2023
How Far Can We Extract Diverse Perspectives from Large Language Models? Shirley Anugrah Hayati Minhwa Lee Dheeraj Rajagopal Dongyeop Kang 25 10 0 16 Nov 2023
Novelty Controlled Paraphrase Generation with Retrieval Augmented Conditional Prompt Tuning Jishnu Ray Chowdhury Yong Zhuang Shuyi Wang 125 39 0 01 Feb 2022
Toward Learning Human-aligned Cross-domain Robust Models by Countering Misaligned Features Haohan Wang Zeyi Huang Hanlin Zhang Yong Jae Lee Eric P. Xing OOD 115 14 0 05 Nov 2021