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NLP practitioners often want to take existing trained models and apply them to data from new domains.
Roberta: A robustly optimized bert pretraining approach
Y. Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, M. Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
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Building a Large Annotated Corpus of English: The Penn Treebank
Mitchell P. Marcus, Beatrice Santorini, and Mary Ann Marcinkiewicz. 1993 · 1993
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A value for n-person games
Lloyd S Shapley. 1997 · 1997
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Coarse-to-fine n-best parsing and MaxEnt discriminative reranking
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Victoria Fossum and Kevin Knight. 2009 · 2009
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SQuAD: 100,000+ questions for machine comprehension of text
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“Why should I trust you?” Explaining the predictions of any classifier
Marco Tulio Ribeiro, Sameer Singh, and Carlos Guestrin. 2016 · 2016
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Findings of the 2017 conference on machine translation (WMT17)
Ondřej Bojar, Rajen Chatterjee, Christian Federmann, Yvette Graham, Barry Haddow, Shujian Huang, Matthias Huck, Philipp Koehn, Qun Liu, Varvara Logacheva, Christof Monz, Matteo Negri, Matt Post, Raphael Rubino, Lucia Specia, and Marco Turchi. 2017 · 2017
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Finale Doshi-Velez and Been Kim. 2017 · 2017
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On calibration of modern neural networks
Chuan Guo, Geoff Pleiss, Yu Sun, and Kilian Q. Weinberger. 2017 · 2017
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Adversarial examples for evaluating reading comprehension systems
Robin Jia and Percy Liang. 2017 · 2017
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TriviaQA: A large scale distantly supervised challenge dataset for reading comprehension
Mandar Joshi, Eunsol Choi, Daniel Weld, and Luke Zettlemoyer. 2017 · 2017
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A unified approach to interpreting model predictions
Scott Lundberg and Su-In Lee. 2017 · 2017
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Regularizing neural networks by penalizing confident output distributions
Gabriel Pereyra, George Tucker, Jan Chorowski, Łukasz Kaiser, and Geoffrey Hinton. 2017 · 2017
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Axiomatic attribution for deep networks
Mukund Sundararajan, Ankur Taly, and Qiqi Yan. 2017 · 2017
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Do explanations make VQA models more predictable to a human?
Arjun Chandrasekaran, Viraj Prabhu, Deshraj Yadav, Prithvijit Chattopadhyay, and Devi Parikh. 2018 · 2018
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Comparing automatic and human evaluation of local explanations for text classification
Domain adaptation with BERT-based domain classification and data selection
Xiaofei Ma, Peng Xu, Zhiguo Wang, Ramesh Nallapati, and Bing Xiang. 2019 · 2019
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Right for the wrong reasons: Diagnosing syntactic heuristics in natural language inference
Tom McCoy, Ellie Pavlick, and Tal Linzen. 2019 · 2019
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MultiQA: An empirical investigation of generalization and transfer in reading comprehension
Alon Talmor and Jonathan Berant. 2019 · 2019
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GLUE: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R. Bowman. 2019 · 2019
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Reranking for neural semantic parsing
Pengcheng Yin and Graham Neubig. 2019 · 2019
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Calibration of pre-trained transformers
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Dong Nguyen. 2018 · 2018
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Stacking with auxiliary features for visual question answering
Nazneen Fatema Rajani and Raymond Mooney. 2018 · 2018
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Anchors: High-precision model-agnostic explanations
Marco Tulio Ribeiro, Sameer Singh, and Carlos Guestrin. 2018 · 2018
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A broad-coverage challenge corpus for sentence understanding through inference
Adina Williams, Nikita Nangia, and Samuel Bowman. 2018 · 2018
Cited alongside, same era.
HotpotQA: A dataset for diverse, explainable multi-hop question answering
Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William W. Cohen, Ruslan Salakhutdinov, and Christopher D. Manning. 2018 · 2018
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Understanding dataset design choices for multi-hop reasoning
Jifan Chen and Greg Durrett. 2019 · 2019
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MRQA 2019 shared task: Evaluating generalization in reading comprehension
Adam Fisch, Alon Talmor, Robin Jia, Minjoon Seo, Eunsol Choi, and Danqi Chen. 2019 · 2019
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Shrey Desai and Greg Durrett. 2020 · 2020
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Multi-source domain adaptation for text classification via distancenet-bandits
Han Guo, Ramakanth Pasunuru, and Mohit Bansal. 2020 · 2020
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Evaluating explainable AI: Which algorithmic explanations help users predict model behavior?
Peter Hase and Mohit Bansal. 2020 · 2020
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Selective question answering under domain shift
Amita Kamath, Robin Jia, and Percy Liang. 2020 · 2020
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Compositional explanations of neurons
Jesse Mu and Jacob Andreas. 2020 · 2020
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Neural unsupervised domain adaptation in NLP—A survey
Alan Ramponi and Barbara Plank. 2020 · 2020
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Connecting attributions and QA model behavior on realistic counterfactuals
Xi Ye, Rohan Nair, and Greg Durrett. 2021 · 2021
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Knowing more about questions can help: Improving calibration in question answering
Shujian Zhang, Chengyue Gong, and Eunsol Choi. 2021 · 2021
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