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Nitish Gupta
Nitish Gupta
Research Scientist, Google AI
Dirección de correo verificada de google.com - Página principal
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Evaluating NLP Models via Contrast Sets
M Gardner, Y Artzi, V Basmova, J Berant, B Bogin, S Chen, P Dasigi, ...
Findings of the Association for Computational Linguistics: EMNLP 2020, 2020
416*2020
Entity Linking via Joint Encoding of Types, Descriptions, and Context
N Gupta, S Singh, D Roth
Conference on Empirical Methods in Natural Language Processing (EMNLP) 2017 …, 2017
2592017
Neural Module Networks for Reasoning over Text
N Gupta, K Lin, D Roth, S Singh, M Gardner
The International Conference on Learning Representations (ICLR) 2020, 2020
1422020
Improving Compositional Generalization in Semantic Parsing
I Oren, J Herzig, N Gupta, M Gardner, J Berant
Findings of the Association for Computational Linguistics: EMNLP 2020, 2020
642020
Obtaining Faithful Interpretations from Compositional Neural Networks
S Subramanian, B Bogin, N Gupta, T Wolfson, S Singh, J Berant, ...
Association for Computational Linguistics (ACL) 2020, 2020
542020
Joint Multilingual Supervision for Cross-Lingual Entity Linking
S Upadhyay, N Gupta, D Roth
Conference on Empirical Methods in Natural Language Processing (EMNLP) 2018, 2018
472018
Robust Named Entity Recognition with Truecasing Pretraining
S Mayhew, N Gupta, D Roth
Proceedings of the AAAI Conference on Artificial Intelligence 2020, 2020
332020
Neural Compositional Denotational Semantics for Question Answering
N Gupta, M Lewis
Conference on Empirical Methods in Natural Language Processing (EMNLP) 2018, 2018
262018
Revisiting the Evaluation for Cross Document Event Coreference
DR Shyam Upadhyay, Nitish Gupta, Christos Christodoulopoulos
Computational Linguistics (COLING) 2016, 2016
22*2016
Xtreme-up: A user-centric scarce-data benchmark for under-represented languages
S Ruder, JH Clark, A Gutkin, M Kale, M Ma, M Nicosia, S Rijhwani, P Riley, ...
arXiv preprint arXiv:2305.11938, 2023
142023
Overestimation of Syntactic Representationin Neural Language Models
J Kodner, N Gupta
Association for Computational Linguistics (ACL) 2020, 2020
132020
Collectively Embedding Multi-Relational Data for Predicting User Preferences
N Gupta, S Singh
arXiv preprint arXiv:1504.06165, 2015
102015
Llm augmented llms: Expanding capabilities through composition
R Bansal, B Samanta, S Dalmia, N Gupta, S Vashishth, S Ganapathy, ...
arXiv preprint arXiv:2401.02412, 2024
82024
Paired examples as indirect supervision in latent decision models
N Gupta, S Singh, M Gardner, D Roth
Conference on Empirical Methods in Natural Language Processing (EMNLP) 2021, 2021
82021
What do we expect from Multiple-choice QA Systems?
K Shah, N Gupta, D Roth
Findings of the Association for Computational Linguistics: EMNLP 2020, 2020
72020
UI CCG TAC-KBP2017 Submissions: Entity Discovery and Linking, and Event Nugget Detection and Co-reference.
C Duncan, LW Chan, H Peng, H Wu, S Upadhyay, N Gupta, CT Tsai, ...
TAC, 2017
62017
Bootstrapping multilingual semantic parsers using large language models
A Awasthi, N Gupta, B Samanta, S Dave, S Sarawagi, P Talukdar
arXiv preprint arXiv:2210.07313, 2022
52022
Enforcing Consistency in Weakly Supervised Semantic Parsing
N Gupta, S Singh, M Gardner
Association for Computational Linguistics (ACL) 2021, 2021
52021
QA is the new KR: question-answer pairs as knowledge bases
WW Cohen, W Chen, M De Jong, N Gupta, A Presta, P Verga, J Wieting
Proceedings of the AAAI Conference on Artificial Intelligence 37 (13), 15385 …, 2023
32023
Collective Factorization for Relational Data: An Evaluation on the Yelp Datasets
N Gupta, S Singh
Technical report, Technical report, Yelp Dataset Challenge, Round 4, 2015
32015
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Artículos 1–20