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Analyzing the Abstractiveness-Factuality Tradeoff With Nonlinear Abstractiveness Constraints


Aug 05, 2021
Markus Dreyer, Mengwen Liu, Feng Nan, Sandeep Atluri, Sujith Ravi


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Improving Factual Consistency of Abstractive Summarization via Question Answering


May 10, 2021
Feng Nan, Cicero Nogueira dos Santos, Henghui Zhu, Patrick Ng, Kathleen McKeown, Ramesh Nallapati, Dejiao Zhang, Zhiguo Wang, Andrew O. Arnold, Bing Xiang

* ACL-IJCNLP 2021 

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Towards Clinical Encounter Summarization: Learning to Compose Discharge Summaries from Prior Notes


Apr 27, 2021
Han-Chin Shing, Chaitanya Shivade, Nima Pourdamghani, Feng Nan, Philip Resnik, Douglas Oard, Parminder Bhatia


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Supporting Clustering with Contrastive Learning


Mar 24, 2021
Dejiao Zhang, Feng Nan, Xiaokai Wei, Shangwen Li, Henghui Zhu, Kathleen McKeown, Ramesh Nallapati, Andrew Arnold, Bing Xiang

* NAACL 2021 

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Entity-level Factual Consistency of Abstractive Text Summarization


Feb 18, 2021
Feng Nan, Ramesh Nallapati, Zhiguo Wang, Cicero Nogueira dos Santos, Henghui Zhu, Dejiao Zhang, Kathleen McKeown, Bing Xiang

* EACL 2021 

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Answering Ambiguous Questions through Generative Evidence Fusion and Round-Trip Prediction


Nov 26, 2020
Yifan Gao, Henghui Zhu, Patrick Ng, Cicero Nogueira dos Santos, Zhiguo Wang, Feng Nan, Dejiao Zhang, Ramesh Nallapati, Andrew O. Arnold, Bing Xiang


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End-to-End Synthetic Data Generation for Domain Adaptation of Question Answering Systems


Oct 12, 2020
Siamak Shakeri, Cicero Nogueira dos Santos, Henry Zhu, Patrick Ng, Feng Nan, Zhiguo Wang, Ramesh Nallapati, Bing Xiang

* EMNLP 2020 

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Who did They Respond to? Conversation Structure Modeling using Masked Hierarchical Transformer


Nov 25, 2019
Henghui Zhu, Feng Nan, Zhiguo Wang, Ramesh Nallapati, Bing Xiang

* AAAI 2020 

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Topic Modeling with Wasserstein Autoencoders


Jul 24, 2019
Feng Nan, Ran Ding, Ramesh Nallapati, Bing Xiang

* to appear at ACL 2019 

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Sequential Dynamic Decision Making with Deep Neural Nets on a Test-Time Budget


May 31, 2017
Henghui Zhu, Feng Nan, Ioannis Paschalidis, Venkatesh Saligrama


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Adaptive Classification for Prediction Under a Budget


May 26, 2017
Feng Nan, Venkatesh Saligrama

* arXiv admin note: substantial text overlap with arXiv:1704.07505 

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Comments on the proof of adaptive submodular function minimization


May 10, 2017
Feng Nan, Venkatesh Saligrama


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Dynamic Model Selection for Prediction Under a Budget


Apr 25, 2017
Feng Nan, Venkatesh Saligrama


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Pruning Random Forests for Prediction on a Budget


Jun 16, 2016
Feng Nan, Joseph Wang, Venkatesh Saligrama


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Optimally Pruning Decision Tree Ensembles With Feature Cost


Jan 05, 2016
Feng Nan, Joseph Wang, Venkatesh Saligrama


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Feature-Budgeted Random Forest


Feb 20, 2015
Feng Nan, Joseph Wang, Venkatesh Saligrama


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Max-Cost Discrete Function Evaluation Problem under a Budget


Jan 12, 2015
Feng Nan, Joseph Wang, Venkatesh Saligrama


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