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Past works that investigate out-of-domain performance of QA systems have mainly focused on general domains (e.g.
Huggingface’s transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, R’emi Louf, Morgan Funtowicz, and Jamie Brew. 2019 · 1910
Earlier work this paper cites.
Learning question classifiers
Xin Li and Dan Roth. 2002 · 2002
Earlier work this paper cites.
Question classification using support vector machines
Dell Zhang and Wee Sun Lee. 2003 · 2003
Earlier work this paper cites.
Subdomain sensitive statistical parsing using raw corpora
Barbara Plank and Khalil Sima’an. 2008 · 2008
Earlier work this paper cites.
What to do about non-standard (or non-canonical) language in NLP
Barbara Plank. 2016 · 2016
Earlier work this paper cites.
SQuAD: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
Earlier work this paper cites.
Reading Wikipedia to answer open-domain questions
Danqi Chen, Adam Fisch, Jason Weston, and Antoine Bordes. 2017 · 2017
Earlier work this paper cites.
NewsQA: A machine comprehension dataset
Adam Trischler, Tong Wang, Xingdi Yuan, Justin Harris, Alessandro Sordoni, Philip Bachman, and Kaheer Suleman. 2017 · 2017
Earlier work this paper cites.
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Cited alongside, same era.
Text length adaptation in sentiment classification
Reinald Kim Amplayo, Seonjae Lim, and Seung-won Hwang. 2019 · 2019
Cited alongside, same era.
MRQA 2019 shared task: Evaluating generalization in reading comprehension
Adam Fisch, Alon Talmor, Robin Jia, Minjoon Seo, Eunsol Choi, and Danqi Chen. 2019 · 2019
Cited alongside, same era.
MultiQA: An empirical investigation of generalization and transfer in reading comprehension
Alon Talmor and Jonathan Berant. 2019 · 2019
Cited alongside, same era.
Open-domain question answering
Danqi Chen and Wen-tau Yih. 2020 · 2020
Cited alongside, same era.
Look at the first sentence: Position bias in question answering
End-to-end synthetic data generation for domain adaptation of question answering systems
Siamak Shakeri, Cicero Nogueira dos Santos, Henghui Zhu, Patrick Ng, Feng Nan, Zhiguo Wang, Ramesh Nallapati, and Bing Xiang. 2020 · 2020
Later among the works it cites.
On position embeddings in bert
Benyou Wang, Lifeng Shang, Christina Lioma, Xin Jiang, Hao Yang, Qun Liu, and Jakob Grue Simonsen. 2020 · 2020
Later among the works it cites.
Machine reading comprehension: The role of contextualized language models and beyond
Zhuosheng Zhang, Hai Zhao, and Rui Wang. 2020 · 2020
Later among the works it cites.
Improving unsupervised question answering via summarization-informed question generation
Chenyang Lyu, Lifeng Shang, Yvette Graham, Jennifer Foster, Xin Jiang, and Qun Liu. 2021 · 2021
Later among the works it cites.
Multi-domain multilingual question answering
Sebastian Ruder and Avi Sil. 2021 · 2021
Later among the works it cites.
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Miyoung Ko, Jinhyuk Lee, Hyunjae Kim, Gangwoo Kim, and Jaewoo Kang. 2020 · 2020
Cited alongside, same era.
What do models learn from question answering datasets?
Priyanka Sen and Amir Saffari. 2020 · 2020
Cited alongside, same era.
Sequence length is a domain: Length-based overfitting in transformer models
Dusan Varis and Ondřej Bojar. 2021 · 2021
Later among the works it cites.
Adversarial examples for evaluating reading comprehension systems
Robin Jia and Percy Liang. 2017 · 2031
Closest in time.