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Unsupervised Pre-training for Biomedical Question Answering

Sep 27, 2020
Vaishnavi Kommaraju, Karthick Gunasekaran, Kun Li, Trapit Bansal, Andrew McCallum, Ivana Williams, Ana-Maria Istrate

* To appear in BioASQ workshop 2020 

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Self-Supervised Meta-Learning for Few-Shot Natural Language Classification Tasks

Sep 17, 2020
Trapit Bansal, Rishikesh Jha, Tsendsuren Munkhdalai, Andrew McCallum

* To appear in EMNLP 2020 

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Simultaneously Linking Entities and Extracting Relations from Biomedical Text Without Mention-level Supervision

Dec 02, 2019
Trapit Bansal, Pat Verga, Neha Choudhary, Andrew McCallum

* Accepted in AAAI 2020 

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Learning to Few-Shot Learn Across Diverse Natural Language Classification Tasks

Nov 10, 2019
Trapit Bansal, Rishikesh Jha, Andrew McCallum

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Emergent Complexity via Multi-Agent Competition

Mar 14, 2018
Trapit Bansal, Jakub Pachocki, Szymon Sidor, Ilya Sutskever, Igor Mordatch

* Published as a conference paper at ICLR 2018 

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Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments

Feb 23, 2018
Maruan Al-Shedivat, Trapit Bansal, Yuri Burda, Ilya Sutskever, Igor Mordatch, Pieter Abbeel

* Published as a conference paper at ICLR 2018 

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RelNet: End-to-End Modeling of Entities & Relations

Nov 16, 2017
Trapit Bansal, Arvind Neelakantan, Andrew McCallum

* Accepted in AKBC 2017 

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Low-Rank Hidden State Embeddings for Viterbi Sequence Labeling

Aug 02, 2017
Dung Thai, Shikhar Murty, Trapit Bansal, Luke Vilnis, David Belanger, Andrew McCallum

* 4 pages, ICML 2017 DeepStruct Workshop 

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Ask the GRU: Multi-Task Learning for Deep Text Recommendations

Sep 09, 2016
Trapit Bansal, David Belanger, Andrew McCallum

* 8 pages 

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A provable SVD-based algorithm for learning topics in dominant admixture corpus

Nov 04, 2014
Trapit Bansal, Chiranjib Bhattacharyya, Ravindran Kannan

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