| Aqua: Asp-based visual question answering K Basu, F Shakerin, G Gupta International Symposium on Practical Aspects of Declarative Languages, 57-72, 2020 | 42 | 2020 |
| A new algorithm to automate inductive learning of default theories F Shakerin, E Salazar, G Gupta Theory and Practice of Logic Programming 17 (5-6), 1010-1026, 2017 | 32 | 2017 |
| Knowledge-driven natural language understanding of english text and its applications K Basu, SC Varanasi, F Shakerin, J Arias, G Gupta Proceedings of the AAAI Conference on Artificial Intelligence 35 (14), 12554 …, 2021 | 30 | 2021 |
| Induction of non-monotonic logic programs to explain boosted tree models using lime F Shakerin, G Gupta Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 3052-3059, 2019 | 22 | 2019 |
| Square: Semantics-based question answering and reasoning engine K Basu, SC Varanasi, F Shakerin, G Gupta arXiv preprint arXiv:2009.10239, 2020 | 14 | 2020 |
| White-box induction from SVM models: explainable AI with logic programming F Shakerin, G Gupta Theory and Practice of Logic Programming 20 (5), 656-670, 2020 | 14 | 2020 |
| FOLD-RM: a scalable, efficient, and explainable inductive learning algorithm for multi-category classification of mixed data H Wang, F Shakerin, G Gupta Theory and Practice of Logic Programming 22 (5), 658-677, 2022 | 11 | 2022 |
| A case for query-driven predicate answer set programming G Gupta, E Salazar, K Marple, Z Chen, F Shakerin EPiC Series in Computing 51, 64-68, 2017 | 11 | 2017 |
| Automating common sense reasoning with ASP and s (CASP) G Gupta, E Salazar, SC Varanasi, K Basu, J Arias, F Shakerin, R Min, F Li, ... Technical report, 2022 | 7 | 2022 |
| An asp-based approach to answering natural language questions for texts D Pendharkar, K Basu, F Shakerin, G Gupta Theory and Practice of Logic Programming 22 (3), 419-443, 2022 | 6 | 2022 |
| Logic programming-based approaches in explainable AI and natural language processing F Shakerin Department of Computer Science, The University of Texas at Dallas. PhD thesis, 2020 | 5 | 2020 |
| Prolog: past, present, and future G Gupta, E Salazar, F Shakerin, J Arias, SC Varanasi, K Basu, H Wang, ... Prolog: The Next 50 Years, 48-61, 2023 | 4 | 2023 |
| Logic-based explainable and incremental machine learning G Gupta, H Wang, K Basu, F Shakerin, E Salazar, SC Varanasi, ... Prolog: The Next 50 Years, 346-358, 2023 | 3 | 2023 |
| Whitebox induction of default rules using high-utility itemset mining F Shakerin, G Gupta International Symposium on Practical Aspects of Declarative Languages, 168-176, 2020 | 3 | 2020 |
| Tutorial: Automating Commonsense Reasoning. G Gupta, E Salazar, SC Varanasi, K Basu, J Arias, F Shakerin, F Li, ... ICLP Workshops, 2022 | 2 | 2022 |
| Formalizing Informal Logic and Natural Language Deductivism. G Gupta, S Varnasi, K Basu, Z Chen, E Salazar, F Shakerin, S Erbatur, ... ICLP Workshops, 2021 | 2 | 2021 |
| Induction of non-monotonic rules from statistical learning models using high-utility itemset mining F Shakerin, G Gupta arXiv preprint arXiv:1905.11226, 2019 | 2 | 2019 |
| Heuristic Based Induction of Answer Set Programs, From Default theories to Combinatorial problems S Farhad, G Gupta Up-and-Coming and Short Papers of the 28th International Conference on …, 2018 | 2* | 2018 |
| Automating Common Sense Reasoning G Gupta, E Salazar, SC Varanasi, K Basu, F Shakerin, F Li, H Wang, ... | 2 | |
| Induction of Non-monotonic Logic Programs To Explain Statistical Learning Models F Shakerin arXiv preprint arXiv:1909.09017, 2019 | 1 | 2019 |
