DQI: Measuring Data Quality in NLP

2 May 2020

Papers citing "DQI: Measuring Data Quality in NLP"

8 / 8 papers shown

Title
Measuring Diversity in Synthetic Datasets Yuchang Zhu Huizhe Zhang Bingzhe Wu Jintang Li Zibin Zheng Peilin Zhao Liang Chen Yatao Bian 95 0 0 12 Feb 2025
Unleashing the Power of Data Tsunami: A Comprehensive Survey on Data Assessment and Selection for Instruction Tuning of Language Models Yulei Qin Yuncheng Yang Pengcheng Guo Gang Li Hang Shao Yuchen Shi Zihan Xu Yun Gu Ke Li Xing Sun ALM 88 11 0 31 Dec 2024
ShortcutLens: A Visual Analytics Approach for Exploring Shortcuts in Natural Language Understanding Dataset Zhihua Jin Xingbo Wang Furui Cheng Chunhui Sun Qun Liu Huamin Qu 32 9 0 17 Aug 2022
To Find Waldo You Need Contextual Cues: Debiasing Who's Waldo Yiran Luo Pratyay Banerjee Tejas Gokhale Yezhou Yang Chitta Baral 14 4 0 30 Mar 2022
Are We Modeling the Task or the Annotator? An Investigation of Annotator Bias in Natural Language Understanding Datasets Mor Geva Yoav Goldberg Jonathan Berant 235 319 0 21 Aug 2019
Language GANs Falling Short Massimo Caccia Lucas Page-Caccia W. Fedus Hugo Larochelle Joelle Pineau Laurent Charlin 117 214 0 06 Nov 2018
Hypothesis Only Baselines in Natural Language Inference Adam Poliak Jason Naradowsky Aparajita Haldar Rachel Rudinger Benjamin Van Durme 187 576 0 02 May 2018
Split and Rephrase: Better Evaluation and a Stronger Baseline Roee Aharoni Yoav Goldberg MoE 215 45 0 02 May 2018