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2020 – today
- 2022
[c19]Trapit Bansal, Salaheddin Alzubi, Tong Wang, Jay-Yoon Lee, Andrew McCallum:
Meta-Adapters: Parameter Efficient Few-shot Fine-tuning through Meta-Learning. AutoML 2022: 19/1-18- [c18]Akansha Singh Bansal, Trapit Bansal, David E. Irwin:
A moment in the sun: solar nowcasting from multispectral satellite data using self-supervised learning. e-Energy 2022: 251-262 - 2021
- [c17]Trapit Bansal, Karthick Prasad Gunasekaran, Tong Wang, Tsendsuren Munkhdalai, Andrew McCallum:
Diverse Distributions of Self-Supervised Tasks for Meta-Learning in NLP. EMNLP (1) 2021: 5812-5824 - [c16]Dung Thai, Raghuveer Thirukovalluru, Trapit Bansal, Andrew McCallum:
Simultaneously Self-Attending to Text and Entities for Knowledge-Informed Text Representations. RepL4NLP@ACL-IJCNLP 2021: 241-247 - [e1]Anna Rogers, Iacer Calixto, Ivan Vulic, Naomi Saphra, Nora Kassner, Oana-Maria Camburu, Trapit Bansal, Vered Shwartz:
Proceedings of the 6th Workshop on Representation Learning for NLP, RepL4NLP@ACL-IJCNLP 2021, Online, August 6, 2021. Association for Computational Linguistics 2021, ISBN 978-1-954085-72-5 [contents] - [i12]Trapit Bansal, Karthick Gunasekaran, Tong Wang, Tsendsuren Munkhdalai, Andrew McCallum:
Diverse Distributions of Self-Supervised Tasks for Meta-Learning in NLP. CoRR abs/2111.01322 (2021) - [i11]Akansha Singh Bansal, Trapit Bansal, David E. Irwin:
A Moment in the Sun: Solar Nowcasting from Multispectral Satellite Data using Self-Supervised Learning. CoRR abs/2112.13974 (2021) - 2020
- [c15]Trapit Bansal, Patrick Verga, Neha Choudhary, Andrew McCallum:
Simultaneously Linking Entities and Extracting Relations from Biomedical Text without Mention-Level Supervision. AAAI 2020: 7407-7414 - [c14]Vaishnavi Kommaraju, Karthick Gunasekaran, Kun Li, Trapit Bansal, Andrew McCallum, Ivana Williams, Ana-Maria Istrate:
Unsupervised Pre-training for Biomedical Question Answering. CLEF (Working Notes) 2020 - [c13]Trapit Bansal, Rishikesh Jha, Andrew McCallum:
Learning to Few-Shot Learn Across Diverse Natural Language Classification Tasks. COLING 2020: 5108-5123 - [c12]Trapit Bansal, Rishikesh Jha, Tsendsuren Munkhdalai, Andrew McCallum:
Self-Supervised Meta-Learning for Few-Shot Natural Language Classification Tasks. EMNLP (1) 2020: 522-534 - [i10]Trapit Bansal, Rishikesh Jha, Tsendsuren Munkhdalai, Andrew McCallum:
Self-Supervised Meta-Learning for Few-Shot Natural Language Classification Tasks. CoRR abs/2009.08445 (2020) - [i9]Vaishnavi Kommaraju, Karthick Gunasekaran, Kun Li, Trapit Bansal, Andrew McCallum, Ivana Williams, Ana-Maria Istrate:
Unsupervised Pre-training for Biomedical Question Answering. CoRR abs/2009.12952 (2020)
2010 – 2019
- 2019
- [c11]Trapit Bansal, Da-Cheng Juan, Sujith Ravi, Andrew McCallum:
A2N: Attending to Neighbors for Knowledge Graph Inference. ACL (1) 2019: 4387-4392 - [i8]Trapit Bansal, Rishikesh Jha, Andrew McCallum:
Learning to Few-Shot Learn Across Diverse Natural Language Classification Tasks. CoRR abs/1911.03863 (2019) - [i7]Trapit Bansal, Patrick Verga, Neha Choudhary, Andrew McCallum:
Simultaneously Linking Entities and Extracting Relations from Biomedical Text Without Mention-level Supervision. CoRR abs/1912.01070 (2019) - 2018
- [c10]Nathan Greenberg, Trapit Bansal, Patrick Verga, Andrew McCallum:
Marginal Likelihood Training of BiLSTM-CRF for Biomedical Named Entity Recognition from Disjoint Label Sets. EMNLP 2018: 2824-2829 - [c9]Maruan Al-Shedivat, Trapit Bansal, Yura Burda, Ilya Sutskever, Igor Mordatch, Pieter Abbeel:
Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments. ICLR 2018 - [c8]Trapit Bansal, Jakub Pachocki, Szymon Sidor, Ilya Sutskever, Igor Mordatch:
Emergent Complexity via Multi-Agent Competition. ICLR (Poster) 2018 - 2017
- [c7]Trapit Bansal, Arvind Neelakantan, Andrew McCallum:
RelNet: End-to-end Modeling of Entities & Relations. AKBC@NIPS 2017 - [i6]Trapit Bansal, Arvind Neelakantan, Andrew McCallum:
RelNet: End-to-end Modeling of Entities & Relations. CoRR abs/1706.07179 (2017) - [i5]Dung Thai, Shikhar Murty, Trapit Bansal, Luke Vilnis, David Belanger, Andrew McCallum:
Low-Rank Hidden State Embeddings for Viterbi Sequence Labeling. CoRR abs/1708.00553 (2017) - [i4]Maruan Al-Shedivat, Trapit Bansal, Yuri Burda, Ilya Sutskever, Igor Mordatch, Pieter Abbeel:
Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments. CoRR abs/1710.03641 (2017) - [i3]Trapit Bansal, Jakub Pachocki, Szymon Sidor, Ilya Sutskever, Igor Mordatch:
Emergent Complexity via Multi-Agent Competition. CoRR abs/1710.03748 (2017) - 2016
- [c6]Trapit Bansal, David Belanger, Andrew McCallum:
Ask the GRU: Multi-task Learning for Deep Text Recommendations. RecSys 2016: 107-114 - [i2]Trapit Bansal, David Belanger, Andrew McCallum:
Ask the GRU: Multi-Task Learning for Deep Text Recommendations. CoRR abs/1609.02116 (2016) - 2015
- [c5]Goutham Tholpadi, Mrinal Kanti Das, Trapit Bansal, Chiranjib Bhattacharyya:
Relating Romanized Comments to News Articles by Inferring Multi-Glyphic Topical Correspondence. AAAI 2015: 311-317 - [c4]Mrinal Kanti Das, Trapit Bansal, Chiranjib Bhattacharyya:
Ordered Stick-Breaking Prior for Sequential MCMC Inference of Bayesian Nonparametric Models. ICML 2015: 550-559 - [c3]Trapit Bansal, Mrinal Kanti Das
, Chiranjib Bhattacharyya:
Content Driven User Profiling for Comment-Worthy Recommendations of News and Blog Articles. RecSys 2015: 195-202 - 2014
- [c2]Trapit Bansal, Chiranjib Bhattacharyya, Ravindran Kannan:
A provable SVD-based algorithm for learning topics in dominant admixture corpus. NIPS 2014: 1997-2005 - [c1]Mrinal Kanti Das, Trapit Bansal, Chiranjib Bhattacharyya:
Going beyond Corr-LDA for detecting specific comments on news & blogs. WSDM 2014: 483-492 - [i1]Trapit Bansal, Chiranjib Bhattacharyya, Ravindran Kannan:
A provable SVD-based algorithm for learning topics in dominant admixture corpus. CoRR abs/1410.6991 (2014)
Coauthor Index
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