Trapit Bansal
Title
Cited by
Cited by
Year
Ask the GRU: Multi-task learning for deep text recommendations
T Bansal, D Belanger, A McCallum
Proceedings of the 10th ACM Conference on Recommender Systems, 107-114, 2016
2232016
Emergent complexity via multi-agent competition
T Bansal, J Pachocki, S Sidor, I Sutskever, I Mordatch
arXiv preprint arXiv:1710.03748, 2017
2162017
Continuous adaptation via meta-learning in nonstationary and competitive environments
M Al-Shedivat, T Bansal, Y Burda, I Sutskever, I Mordatch, P Abbeel
arXiv preprint arXiv:1710.03641, 2017
1942017
Content driven user profiling for comment-worthy recommendations of news and blog articles
T Bansal, M Das, C Bhattacharyya
Proceedings of the 9th ACM Conference on Recommender Systems, 195-202, 2015
542015
Marginal likelihood training of BiLSTM-CRF for biomedical named entity recognition from disjoint label sets
N Greenberg, T Bansal, P Verga, A McCallum
Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018
482018
A provable SVD-based algorithm for learning topics in dominant admixture corpus
T Bansal, C Bhattacharyya, R Kannan
arXiv preprint arXiv:1410.6991, 2014
432014
A2N: Attending to neighbors for knowledge graph inference
T Bansal, DC Juan, S Ravi, A McCallum
Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019
302019
Relnet: End-to-end modeling of entities & relations
T Bansal, A Neelakantan, A McCallum
arXiv preprint arXiv:1706.07179, 2017
232017
Learning to few-shot learn across diverse natural language classification tasks
T Bansal, R Jha, A McCallum
arXiv preprint arXiv:1911.03863, 2019
192019
Going beyond corr-lda for detecting specific comments on news & blogs
MK Das, T Bansal, C Bhattacharyya
Proceedings of the 7th ACM international conference on Web search and data …, 2014
162014
Self-supervised meta-learning for few-shot natural language classification tasks
T Bansal, R Jha, T Munkhdalai, A McCallum
arXiv preprint arXiv:2009.08445, 2020
42020
Simultaneously linking entities and extracting relations from biomedical text without mention-level supervision
T Bansal, P Verga, N Choudhary, A McCallum
Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 7407-7414, 2020
42020
Unsupervised Pre-training for Biomedical Question Answering
V Kommaraju, K Gunasekaran, K Li, T Bansal, A McCallum, I Williams, ...
arXiv preprint arXiv:2009.12952, 2020
12020
Relating romanized comments to news articles by inferring multi-glyphic topical correspondence
G Tholpadi, M Das, T Bansal, C Bhattacharyya
Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015
12015
Ordered Stick-Breaking Prior for Sequential MCMC Inference of Bayesian Nonparametric Models
M Das, T Bansal, C Bhattacharyya
1*
Low-Rank Hidden State Embeddings for Viterbi Sequence Labeling
D Thai, S Murty, T Bansal, L Vilnis, D Belanger, A McCallum
arXiv preprint arXiv:1708.00553, 2017
2017
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