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ASQA: Factoid Questions Meet Long-Form Answers



Ivan Stelmakh , Yi Luan , Bhuwan Dhingra , Ming-Wei Chang


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FRUIT: Faithfully Reflecting Updated Information in Text



Robert L. Logan IV , Alexandre Passos , Sameer Singh , Ming-Wei Chang

* v1.0 

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Large Dual Encoders Are Generalizable Retrievers



Jianmo Ni , Chen Qu , Jing Lu , Zhuyun Dai , Gustavo Hernández Ábrego , Ji Ma , Vincent Y. Zhao , Yi Luan , Keith B. Hall , Ming-Wei Chang , Yinfei Yang


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Revisiting the Primacy of English in Zero-shot Cross-lingual Transfer



Iulia Turc , Kenton Lee , Jacob Eisenstein , Ming-Wei Chang , Kristina Toutanova


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Joint Passage Ranking for Diverse Multi-Answer Retrieval



Sewon Min , Kenton Lee , Ming-Wei Chang , Kristina Toutanova , Hannaneh Hajishirzi

* 13 pages 

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Unlocking Compositional Generalization in Pre-trained Models Using Intermediate Representations



Jonathan Herzig , Peter Shaw , Ming-Wei Chang , Kelvin Guu , Panupong Pasupat , Yuan Zhang


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CapWAP: Captioning with a Purpose



Adam Fisch , Kenton Lee , Ming-Wei Chang , Jonathan H. Clark , Regina Barzilay

* EMNLP 2020 

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Compositional Generalization and Natural Language Variation: Can a Semantic Parsing Approach Handle Both?



Peter Shaw , Ming-Wei Chang , Panupong Pasupat , Kristina Toutanova


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Open Question Answering over Tables and Text



Wenhu Chen , Ming-Wei Chang , Eva Schlinger , William Wang , William W. Cohen

* Technical Report 

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Probabilistic Assumptions Matter: Improved Models for Distantly-Supervised Document-Level Question Answering



Hao Cheng , Ming-Wei Chang , Kenton Lee , Kristina Toutanova

* ACL2020 

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