Rushin Shah
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Cross-lingual transfer learning for multilingual task oriented dialog
S Schuster, S Gupta, R Shah, M Lewis
arXiv preprint arXiv:1810.13327, 2018
Topical clustering of tweets
KD Rosa, R Shah, B Lin, A Gershman, R Frederking
Proceedings of the ACM SIGIR: SWSM 63, 2011
Semantic parsing for task oriented dialog using hierarchical representations
S Gupta, R Shah, M Mohit, A Kumar, M Lewis
arXiv preprint arXiv:1810.07942, 2018
SYNERGY: a named entity recognition system for resource-scarce languages such as Swahili using online machine translation
R Shah, B Lin, A Gershman, R Frederking
Proceedings of the Second Workshop on African Language Technology (AfLaT …, 2010
Improving semantic parsing for task oriented dialog
A Einolghozati, P Pasupat, S Gupta, R Shah, M Mohit, M Lewis, ...
arXiv preprint arXiv:1902.06000, 2019
Span-based hierarchical semantic parsing for task-oriented dialog
P Pasupat, S Gupta, K Mandyam, R Shah, M Lewis, L Zettlemoyer
Proceedings of the 2019 conference on empirical methods in natural language …, 2019
Generating multi-perspective responses by assistant systems
E Koukoumidis, MR Hanson, R Subba, H Young, R Shah, J Yu, ...
US Patent 11,308,169, 2022
Improving robustness of task oriented dialog systems
A Einolghozati, S Gupta, M Mohit, R Shah
arXiv preprint arXiv:1911.05153, 2019
Pytext: A seamless path from nlp research to production
A Aly, K Lakhotia, S Zhao, M Mohit, B Oguz, A Arora, S Gupta, C Dewan, ...
arXiv preprint arXiv:1812.08729, 2018
A new approach to lexical disambiguation of Arabic text
R Shah, PS Dhillon, M Liberman, D Foster, M Maamouri, L Ungar
Proceedings of the 2010 Conference on Empirical Methods in Natural Language …, 2010
Lads: Rapid development of a learning-to-rank based related entity finding system using open advancement
B Lin, KD Rosa, R Shah, N Agarwal
Proceedings of the International Workshop on Entity-Oriented Search,(EOS’11 …, 2011
Presto: A multilingual dataset for parsing realistic task-oriented dialogs
R Goel, W Ammar, A Gupta, S Vashishtha, M Sano, F Surani, M Chang, ...
arXiv preprint arXiv:2303.08954, 2023
Update frequently, update fast: Retraining semantic parsing systems in a fraction of time
V Lialin, R Goel, A Simanovsky, A Rumshisky, R Shah
arXiv preprint arXiv:2010.07865, 2020
Overcoming conflicting data for model updates
D Gaddy, A Kouzemtchenko, PK Reddy, P Kolhar, R Shah
Workshop NLP Conv. AI (NLP4ConvAI) EMNLP, 2020
Cone: Metrics for automatic evaluation of named entity co-reference resolution
B Lin, R Shah, R Frederking, A Gershman
Proceedings of the 2010 Named Entities Workshop, 136-144, 2010
Continual learning for neural semantic parsing
V Lialin, R Goel, A Simanovsky, A Rumshisky, R Shah
arXiv preprint arXiv:2010.07865, 2020
Improving cross-document co-reference with semi-supervised information extraction modelsi.
R Shah, B Lin, KD Rosa, A Gershman, RE Frederking
MLSLP, 21-25, 2011
Improving Top-K Decoding for Non-Autoregressive Semantic Parsing via Intent Conditioning
G Oh, R Goel, C Hidey, S Paul, A Gupta, P Shah, R Shah
arXiv preprint arXiv:2204.06748, 2022
Algorithms for Biological Cell Sorting with a Lab-on-a-chip
A Ghosh, R Shah, A Bishnu, BB Bhattacharya
2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), 104-109, 2009
Overcoming conflicting data when updating a neural semantic parser
D Gaddy, A Kouzemtchenko, PR Muddireddy, P Kolhar, R Shah
arXiv preprint arXiv:2010.12675, 2020
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