Trapit Bansal

Publication Activity (10 Years)

Years Active: 2014-2022
Publications (10 Years): 28

Top Topics

Natural Language

Top Venues

Publications

Trapit Bansal, Salaheddin Alzubi, Tong Wang, Jay-Yoon Lee, Andrew McCallum
Meta-Adapters: Parameter Efficient Few-shot Fine-tuning through Meta-Learning. AutoML (2022)
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)
Dung Thai, Raghuveer Thirukovalluru, Trapit Bansal, Andrew McCallum
Simultaneously Self-Attending to Text and Entities for Knowledge-Informed Text Representations. RepL4NLP@ACL-IJCNLP (2021)
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)
Akansha Singh Bansal, Trapit Bansal, David E. Irwin
A Moment in the Sun: Solar Nowcasting from Multispectral Satellite Data using Self-Supervised Learning. CoRR (2021)
Trapit Bansal, Karthick Gunasekaran, Tong Wang, Tsendsuren Munkhdalai, Andrew McCallum
Diverse Distributions of Self-Supervised Tasks for Meta-Learning in NLP. CoRR (2021)
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)
Trapit Bansal, Rishikesh Jha, Tsendsuren Munkhdalai, Andrew McCallum
Self-Supervised Meta-Learning for Few-Shot Natural Language Classification Tasks. EMNLP (1) (2020)
Trapit Bansal, Rishikesh Jha, Andrew McCallum
Learning to Few-Shot Learn Across Diverse Natural Language Classification Tasks. COLING (2020)
Trapit Bansal, Rishikesh Jha, Tsendsuren Munkhdalai, Andrew McCallum
Self-Supervised Meta-Learning for Few-Shot Natural Language Classification Tasks. CoRR (2020)
Trapit Bansal, Patrick Verga, Neha Choudhary, Andrew McCallum
Simultaneously Linking Entities and Extracting Relations from Biomedical Text without Mention-Level Supervision. AAAI (2020)
Vaishnavi Kommaraju, Karthick Gunasekaran, Kun Li, Trapit Bansal, Andrew McCallum, Ivana Williams, Ana-Maria Istrate
Unsupervised Pre-training for Biomedical Question Answering. CoRR (2020)
Trapit Bansal, Da-Cheng Juan, Sujith Ravi, Andrew McCallum
A2N: Attending to Neighbors for Knowledge Graph Inference. ACL (1) (2019)
Trapit Bansal, Patrick Verga, Neha Choudhary, Andrew McCallum
Simultaneously Linking Entities and Extracting Relations from Biomedical Text Without Mention-level Supervision. CoRR (2019)
Trapit Bansal, Rishikesh Jha, Andrew McCallum
Learning to Few-Shot Learn Across Diverse Natural Language Classification Tasks. CoRR (2019)
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)
Trapit Bansal, Jakub Pachocki, Szymon Sidor, Ilya Sutskever, Igor Mordatch
Emergent Complexity via Multi-Agent Competition. ICLR (Poster) (2018)
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)
Dung Thai, Shikhar Murty, Trapit Bansal, Luke Vilnis, David Belanger, Andrew McCallum
Low-Rank Hidden State Embeddings for Viterbi Sequence Labeling. CoRR (2017)
Trapit Bansal, Jakub Pachocki, Szymon Sidor, Ilya Sutskever, Igor Mordatch
Emergent Complexity via Multi-Agent Competition. CoRR (2017)
Trapit Bansal, Arvind Neelakantan, Andrew McCallum
RelNet: End-to-end Modeling of Entities & Relations. CoRR (2017)
Maruan Al-Shedivat, Trapit Bansal, Yuri Burda, Ilya Sutskever, Igor Mordatch, Pieter Abbeel
Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments. CoRR (2017)
Trapit Bansal, Arvind Neelakantan, Andrew McCallum
RelNet: End-to-end Modeling of Entities & Relations. AKBC@NIPS (2017)
Trapit Bansal, David Belanger, Andrew McCallum
Ask the GRU: Multi-Task Learning for Deep Text Recommendations. CoRR (2016)
Trapit Bansal, David Belanger, Andrew McCallum
: Multi-task Learning for Deep Text Recommendations. RecSys (2016)
Trapit Bansal, Mrinal Kanti Das, Chiranjib Bhattacharyya
Content Driven User Profiling for Comment-Worthy Recommendations of News and Blog Articles. RecSys (2015)
Goutham Tholpadi, Mrinal Kanti Das, Trapit Bansal, Chiranjib Bhattacharyya
Relating Romanized Comments to News Articles by Inferring Multi-Glyphic Topical Correspondence. AAAI (2015)
Mrinal Kanti Das, Trapit Bansal, Chiranjib Bhattacharyya
Ordered Stick-Breaking Prior for Sequential MCMC Inference of Bayesian Nonparametric Models. ICML (2015)
Trapit Bansal, Chiranjib Bhattacharyya, Ravindran Kannan
A provable SVD-based algorithm for learning topics in dominant admixture corpus. CoRR (2014)
Trapit Bansal, Chiranjib Bhattacharyya, Ravindran Kannan
A provable SVD-based algorithm for learning topics in dominant admixture corpus. NIPS (2014)
Mrinal Kanti Das, Trapit Bansal, Chiranjib Bhattacharyya
Going beyond Corr-LDA for detecting specific comments on news & blogs. WSDM (2014)