| Deep reinforcement learning for sequence-to-sequence models Y Keneshloo, T Shi, N Ramakrishnan, CK Reddy IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2019 | 252 | 2019 |
| Neural abstractive text summarization with sequence-to-sequence models T Shi, Y Keneshloo, N Ramakrishnan, CK Reddy ACM Transactions on Data Science 2 (1), 1-37, 2021 | 236 | 2021 |
| Short-text topic modeling via non-negative matrix factorization enriched with local word-context correlations T Shi, K Kang, J Choo, CK Reddy Proceedings of the 2018 World Wide Web Conference (WWW 2018), 1105-1114, 2018 | 202 | 2018 |
| Text-to-SQL Generation for Question Answering on Electronic Medical Records P Wang, T Shi, CK Reddy Proceedings of The Web Conference 2020 (WWW 2020), 350-361, 2020 | 73 | 2020 |
| A Simple and Effective Self-Supervised Contrastive Learning Framework for Aspect Detection T Shi, L Li, P Wang, CK Reddy AAAI 2021, 2020 | 40 | 2020 |
| LeafNATS: An Open-Source Toolkit and Live Demo System for Neural Abstractive Text Summarization T Shi, P Wang, CK Reddy NAACL (demo) 2019, 2019 | 17 | 2019 |
| A novel tensor-based temporal multi-task survival analysis model P Wang, T Shi, CK Reddy IEEE Transactions on Knowledge and Data Engineering 33 (9), 3311-3322, 2020 | 12 | 2020 |
| Document-Level Multi-Aspect Sentiment Classification for Online Reviews of Medical Experts T Shi, V Rakesh, S Wang, CK Reddy CIKM 2019, 2723-2731, 2019 | 11 | 2019 |
| GPView: A program for wave function analysis and visualization T Shi, P Wang Journal of Molecular Graphics and Modelling 70, 305-314, 2016 | 10 | 2016 |
| How geometric distortions scatter electronic excitations in conjugated macromolecules T Shi, H Li, S Tretiak, VY Chernyak The journal of physical chemistry letters 5 (22), 3946-3952, 2014 | 10 | 2014 |
| Neural abstractive text summarization with sequence-to-sequence models: a survey T Shi, Y Keneshloo, N Ramakrishnan, CK Reddy arXiv preprint arXiv:1812.02303, 2020 | 8 | 2020 |
| Corpus-level and concept-based explanations for interpretable document classification T Shi, X Zhang, P Wang, CK Reddy ACM Transactions on Knowledge Discovery from Data (TKDD) 16 (3), 1-17, 2021 | 6 | 2021 |
| Neural abstractive text summarization with sequence-to-sequence models (2018) T Shi, Y Keneshloo, N Ramakrishnan, CK Reddy arXiv preprint arXiv:1812.02303, 1812 | 6 | 1812 |
| Attention-based aspect reasoning for knowledge base question answering on clinical notes P Wang, T Shi, K Agarwal, S Choudhury, CK Reddy Proceedings of the 13th ACM International Conference on Bioinformatics …, 2022 | 5 | 2022 |
| Counting the number of excited states in organic semiconductor systems using topology MJ Catanzaro, T Shi, S Tretiak, VY Chernyak The Journal of chemical physics 142 (8), 2015 | 4 | 2015 |
| Event detection explorer: An interactive tool for event detection exploration W Zhang, B Ingale, H Shabir, T Li, T Shi, P Wang Companion Proceedings of the 28th International Conference on Intelligent …, 2023 | 3 | 2023 |
| An interpretable and uncertainty aware multi-task framework for multi-aspect sentiment analysis T Shi, P Wang, CK Reddy arXiv preprint arXiv:2009.09112, 2020 | 1 | 2020 |
| Task as Context: A Sensemaking Perspective on Annotating Inter-Dependent Event Attributes with Non-Experts T Li, P Wang, T Shi, Y Bian, A Esakia Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 11 …, 2023 | | 2023 |
| Text-to-ESQ: A Two-Stage Controllable Approach for Efficient Retrieval of Vaccine Adverse Events from NoSQL Database W Zhang, K Zeng, X Yang, T Shi, P Wang Proceedings of the 14th ACM International Conference on Bioinformatics …, 2023 | | 2023 |
| Exploring the Impact of Sub-Task Inter-Dependency on Crowdsourced Event Annotation T Li, P Wang, T Shi, A Esakia | | 2022 |
Chandan K. ReddyProfessor, Computer Science, Virginia TechVerified email at cs.vt.edu
