Trapit Bansal

According to our database, Trapit Bansal authored at least 21 papers between 2014 and 2022.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2022

A moment in the sun: solar nowcasting from multispectral satellite data using self-supervised learning.

Akansha Singh Bansal, Trapit Bansal, David E. Irwin

Proceedings of the e-Energy '22: The Thirteenth ACM International Conference on Future Energy Systems, Virtual Event, 28 June 2022, 2022

Meta-Adapters: Parameter Efficient Few-shot Fine-tuning through Meta-Learning.

Trapit Bansal, Salaheddin Alzubi, Tong Wang, Jay-Yoon Lee, Andrew McCallum

Proceedings of the International Conference on Automated Machine Learning, 2022

2021

Simultaneously Self-Attending to Text and Entities for Knowledge-Informed Text Representations.

Dung Thai, Raghuveer Thirukovalluru, Trapit Bansal, Andrew McCallum

Proceedings of the 6th Workshop on Representation Learning for NLP, 2021

Diverse Distributions of Self-Supervised Tasks for Meta-Learning in NLP.

Trapit Bansal, Karthick Prasad Gunasekaran, Tong Wang, Tsendsuren Munkhdalai, Andrew McCallum

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2020

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

Trapit Bansal, Rishikesh Jha, Tsendsuren Munkhdalai, Andrew McCallum

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

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

Trapit Bansal, Rishikesh Jha, Andrew McCallum

Proceedings of the 28th International Conference on Computational Linguistics, 2020

Unsupervised Pre-training for Biomedical Question Answering.

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

Proceedings of the Working Notes of CLEF 2020, 2020

Simultaneously Linking Entities and Extracting Relations from Biomedical Text without Mention-Level Supervision.

Trapit Bansal, Patrick Verga, Neha Choudhary, Andrew McCallum

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

A2N: Attending to Neighbors for Knowledge Graph Inference.

Trapit Bansal, Da-Cheng Juan, Sujith Ravi, Andrew McCallum

Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018

Emergent Complexity via Multi-Agent Competition.

Trapit Bansal, Jakub Pachocki, Szymon Sidor, Ilya Sutskever, Igor Mordatch

Proceedings of the 6th International Conference on Learning Representations, 2018

Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments.

Maruan Al-Shedivat, Trapit Bansal, Yura Burda, Ilya Sutskever, Igor Mordatch, Pieter Abbeel

Proceedings of the 6th International Conference on Learning Representations, 2018

Marginal Likelihood Training of BiLSTM-CRF for Biomedical Named Entity Recognition from Disjoint Label Sets.

Nathan Greenberg, Trapit Bansal, Patrick Verga, Andrew McCallum

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

2017

Low-Rank Hidden State Embeddings for Viterbi Sequence Labeling.

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

CoRR, 2017

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

Trapit Bansal, Arvind Neelakantan, Andrew McCallum

Proceedings of the 6th Workshop on Automated Knowledge Base Construction, 2017

2016

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

Trapit Bansal, David Belanger, Andrew McCallum

CoRR, 2016

<i>Ask the GRU</i>: Multi-task Learning for Deep Text Recommendations.

Trapit Bansal, David Belanger, Andrew McCallum

Proceedings of the 10th ACM Conference on Recommender Systems, 2016

2015

Content Driven User Profiling for Comment-Worthy Recommendations of News and Blog Articles.

Trapit Bansal, Mrinal Kanti Das, Chiranjib Bhattacharyya

Proceedings of the 9th ACM Conference on Recommender Systems, 2015

Ordered Stick-Breaking Prior for Sequential MCMC Inference of Bayesian Nonparametric Models.

Mrinal Kanti Das, Trapit Bansal, Chiranjib Bhattacharyya

Proceedings of the 32nd International Conference on Machine Learning, 2015

Relating Romanized Comments to News Articles by Inferring Multi-Glyphic Topical Correspondence.

Goutham Tholpadi, Mrinal Kanti Das, Trapit Bansal, Chiranjib Bhattacharyya

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

Going beyond Corr-LDA for detecting specific comments on news & blogs.

Mrinal Kanti Das, Trapit Bansal, Chiranjib Bhattacharyya

Proceedings of the Seventh ACM International Conference on Web Search and Data Mining, 2014

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

Trapit Bansal, Chiranjib Bhattacharyya, Ravindran Kannan

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014