| Leveraging abstract meaning representation for knowledge base question answering P Kapanipathi, I Abdelaziz, S Ravishankar, S Roukos, A Gray, R Astudillo, ... arXiv preprint arXiv:2012.01707, 2020 | 106* | 2020 |
| The techqa dataset V Castelli, R Chakravarti, S Dana, A Ferritto, R Florian, M Franz, D Garg, ... arXiv preprint arXiv:1911.02984, 2019 | 31 | 2019 |
| Physically consistent simulation of mesoscale chemical kinetics: The non-negative FIS-α method S Dana, S Raha Journal of Computational Physics 230 (24), 8813-8834, 2011 | 20 | 2011 |
| Translucent Answer Predictions in Multi-Hop Reading Comprehension AGIBMR G P Shrivatsa Bhargav (IISc), Michael R. Glass (IBM Research), Dinesh ... AAAI, 2020 | 12* | 2020 |
| SYGMA: system for generalizable modular question answering overknowledge bases S Neelam, U Sharma, H Karanam, S Ikbal, P Kapanipathi, I Abdelaziz, ... arXiv preprint arXiv:2109.13430, 2021 | 10 | 2021 |
| Computation of restoration of ligand response in the random kinetics of a prostate cancer cell signaling pathway S Dana, T Nakakuki, M Hatakeyama, S Kimura, S Raha computer methods and programs in biomedicine 101 (1), 1-22, 2011 | 8 | 2011 |
| A deep neural approach to kgqa via sparql silhouette generation S Purkayastha, S Dana, D Garg, D Khandelwal, GPS Bhargav 2022 International Joint Conference on Neural Networks (IJCNN), 1-8, 2022 | 7 | 2022 |
| A benchmark for generalizable and interpretable temporal question answering over knowledge bases S Neelam, U Sharma, H Karanam, S Ikbal, P Kapanipathi, I Abdelaziz, ... arXiv preprint arXiv:2201.05793, 2022 | 7 | 2022 |
| Knowledge graph question answering via SPARQL silhouette generation S Purkayastha, S Dana, D Garg, D Khandelwal, GP Bhargav arXiv preprint arXiv:2109.09475, 2021 | 6 | 2021 |
| Gas-selective signal amplification in fluctuation-based graphene FET sensors S Dana, MM Varma IEEE Sensors Journal 16 (17), 6533-6536, 2016 | 6 | 2016 |
| Activator-induced dynamic disorder and molecular memory in human two-pore domain hTREK1 K+ channel TK Nayak, S Dana, S Raha, SK Sikdar Journal of chemical biology 4, 69-84, 2011 | 5 | 2011 |
| Zero-shot Entity Linking with Less Data GPS Bhargav, D Khandelwal, S Dana, D Garg, P Kapanipathi, S Roukos, ... Findings of the Association for Computational Linguistics: NAACL 2022, 1681-1697, 2022 | 3 | 2022 |
| Explaining cross domain model predictions D Saswati, D Garg, S Chemmengath, S Kenkre, LV Subramaniam US Patent 11,501,115, 2022 | 1 | 2022 |
| Zero-shot entity linking based on symbolic information D Khandelwal, GPS Bhargav, D Saswati, D Garg, PK Bangalore, ... US Patent App. 17/575,951, 2023 | | 2023 |
| AI4Code S Tamilselvam, D Khandelwal, S Dana, P Kumar, D Garg Asian Conference on Machine Learning, 2022 | | 2022 |
| Chart erratum and refactoring ZA Silverstein, TL Hewitt, D Saswati, MS Jaiswal, JD Dunne US Patent 11,308,667, 2022 | | 2022 |
| Semantic Answer Type Prediction using Dense Type Embeddings GPS Bhargav, D Khandelwal, D Garg, S Dana SeMantic Answer Type and Relation Prediction Task at ISWC Semantic Web Challenge, 2021 | | 2021 |
| Constructing Micro Knowledge Graphs from Technical Support Documents A Kumar, N Gupta, S Dana The Semantic Web: ESWC 2021 Satellite Events: Virtual Event, June 6–10, 2021 …, 2021 | | 2021 |
| Chart erratum and refactoring ZASTLHSDSJD Dunne US Patent US11308667B1, 2020 | | 2020 |
| Entity and Relation Linking is All You Need for KGQA S Purkayatha, S Dana, GPS Bhargav, D Khandelwal, D Garg Annual Conference on Neural Information Processing Systems, 2020 | | 2020 |
