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ORCIDDinesh Khandelwal
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2020 – today
- 2023
[c12]Harman Singh, Poorva Garg, Mohit Gupta, Kevin Shah, Ashish Goswami, Satyam Modi, Arnab Kumar Mondal, Dinesh Khandelwal, Dinesh Garg, Parag Singla:
Image Manipulation via Multi-Hop Instructions - A New Dataset and Weakly-Supervised Neuro-Symbolic Approach. EMNLP 2023: 2975-3007- [c11]Nithish Kannen, Udit Sharma, Sumit Neelam, Dinesh Khandelwal, Shajith Ikbal, Hima Karanam, L. Venkata Subramaniam:
Best of Both Worlds: Towards Improving Temporal Knowledge Base Question Answering via Targeted Fact Extraction. EMNLP 2023: 4729-4744 - [i10]Harman Singh, Poorva Garg, Mohit Gupta, Kevin Shah, Arnab Kumar Mondal, Dinesh Khandelwal, Parag Singla, Dinesh Garg:
Image Manipulation via Multi-Hop Instructions - A New Dataset and Weakly-Supervised Neuro-Symbolic Approach. CoRR abs/2305.14410 (2023) - [i9]Aniruddha Deb, Neeva Oza, Sarthak Singla, Dinesh Khandelwal, Dinesh Garg, Parag Singla:
Fill in the Blank: Exploring and Enhancing LLM Capabilities for Backward Reasoning in Math Word Problems. CoRR abs/2310.01991 (2023) - 2022
- [c10]Sumit Neelam, Udit Sharma, Hima Karanam, Shajith Ikbal, Pavan Kapanipathi, Ibrahim Abdelaziz, Nandana Mihindukulasooriya, Young-Suk Lee, Santosh K. Srivastava, Cezar Pendus, Saswati Dana, Dinesh Garg, Achille Fokoue, G. P. Shrivatsa Bhargav, Dinesh Khandelwal, Srinivas Ravishankar, Sairam Gurajada, Maria Chang, Rosario Uceda-Sosa, Salim Roukos, Alexander Gray, Guilherme Lima, Ryan Riegel, Francois P. S. Luus, L. Venkata Subramaniam:
SYGMA: A System for Generalizable and Modular Question Answering Over Knowledge Bases. EMNLP (Findings) 2022: 3866-3879 - [c9]Sukannya Purkayastha, Saswati Dana, Dinesh Garg, Dinesh Khandelwal, G. P. Shrivatsa Bhargav:
A Deep Neural Approach to KGQA via SPARQL Silhouette Generation. IJCNN 2022: 1-8 - [c8]G. P. Shrivatsa Bhargav, Dinesh Khandelwal, Saswati Dana, Dinesh Garg, Pavan Kapanipathi, Salim Roukos, Alexander G. Gray, L. Venkata Subramaniam:
Zero-shot Entity Linking with Less Data. NAACL-HLT (Findings) 2022: 1681-1697 - [i8]Sumit Neelam, Udit Sharma, Hima Karanam, Shajith Ikbal, Pavan Kapanipathi, Ibrahim Abdelaziz, Nandana Mihindukulasooriya, Young-Suk Lee, Santosh K. Srivastava, Cezar Pendus, Saswati Dana, Dinesh Garg, Achille Fokoue, G. P. Shrivatsa Bhargav, Dinesh Khandelwal, Srinivas Ravishankar, Sairam Gurajada, Maria Chang, Rosario Uceda-Sosa, Salim Roukos, Alexander G. Gray, Guilherme Lima, Ryan Riegel, Francois P. S. Luus, L. Venkata Subramaniam:
A Benchmark for Generalizable and Interpretable Temporal Question Answering over Knowledge Bases. CoRR abs/2201.05793 (2022) - [i7]Nithish Kannen, Udit Sharma, Sumit Neelam, Dinesh Khandelwal, Shajith Ikbal, Hima Karanam, L. Venkata Subramaniam:
Targeted Extraction of Temporal Facts from Textual Resources for Improved Temporal Question Answering over Knowledge Bases. CoRR abs/2203.11054 (2022) - 2021
- [c7]Shourya Aggarwal, Divyanshu Mandowara, Vishwajeet Agrawal, Dinesh Khandelwal, Parag Singla, Dinesh Garg:
Explanations for CommonsenseQA: New Dataset and Models. ACL/IJCNLP (1) 2021: 3050-3065 - [c6]Pavan Kapanipathi, Ibrahim Abdelaziz, Srinivas Ravishankar, Salim Roukos, Alexander G. Gray, Ramón Fernandez Astudillo, Maria Chang, Cristina Cornelio, Saswati Dana, Achille Fokoue, Dinesh Garg, Alfio Gliozzo, Sairam Gurajada, Hima Karanam, Naweed Khan, Dinesh Khandelwal, Young-Suk Lee, Yunyao Li, Francois P. S. Luus, Ndivhuwo Makondo, Nandana Mihindukulasooriya, Tahira Naseem, Sumit Neelam, Lucian Popa, Revanth Gangi Reddy, Ryan Riegel, Gaetano Rossiello, Udit Sharma, G. P. Shrivatsa Bhargav, Mo Yu:
Leveraging Abstract Meaning Representation for Knowledge Base Question Answering. ACL/IJCNLP (Findings) 2021: 3884-3894 - [c5]G. P. Shrivatsa Bhargav, Dinesh Khandelwal, Dinesh Garg, Saswati Dana:
Semantic Answer Type Prediction. SMART@ISWC 2021: 14-22 - [i6]Sukannya Purkayastha, Saswati Dana, Dinesh Garg, Dinesh Khandelwal, G. P. Shrivatsa Bhargav:
Knowledge Graph Question Answering via SPARQL Silhouette Generation. CoRR abs/2109.09475 (2021) - [i5]Sumit Neelam, Udit Sharma, Hima Karanam, Shajith Ikbal, Pavan Kapanipathi, Ibrahim Abdelaziz, Nandana Mihindukulasooriya, Young-Suk Lee, Santosh K. Srivastava, Cezar Pendus, Saswati Dana, Dinesh Garg, Achille Fokoue, G. P. Shrivatsa Bhargav, Dinesh Khandelwal, Srinivas Ravishankar, Sairam Gurajada, Maria Chang, Rosario Uceda-Sosa, Salim Roukos, Alexander G. Gray, Guilherme Lima, Ryan Riegel, Francois P. S. Luus, L. Venkata Subramaniam:
SYGMA: System for Generalizable Modular Question Answering OverKnowledge Bases. CoRR abs/2109.13430 (2021) - 2020
- [c4]G. P. Shrivatsa Bhargav, Michael R. Glass, Dinesh Garg, Shirish K. Shevade, Saswati Dana, Dinesh Khandelwal, L. Venkata Subramaniam, Alfio Gliozzo:
Translucent Answer Predictions in Multi-Hop Reading Comprehension. AAAI 2020: 7700-7707 - [c3]Vittorio Castelli, Rishav Chakravarti, Saswati Dana, Anthony Ferritto, Radu Florian, Martin Franz, Dinesh Garg, Dinesh Khandelwal, J. Scott McCarley, Mike McCawley, Mohamed Nasr, Lin Pan, Cezar Pendus, John F. Pitrelli, Saurabh Pujar, Salim Roukos, Andrzej Sakrajda, Avirup Sil, Rosario Uceda-Sosa, Todd Ward, Rong Zhang:
The TechQA Dataset. ACL 2020: 1269-1278 - [c2]Santosh K. Srivastava, Dinesh Khandelwal, Dhiraj Madan, Dinesh Garg, Hima Karanam, L. Venkata Subramaniam:
Inductive Quantum Embedding. NeurIPS 2020 - [i4]Pavan Kapanipathi, Ibrahim Abdelaziz, Srinivas Ravishankar, Salim Roukos, Alexander G. Gray, Ramón Fernandez Astudillo, Maria Chang, Cristina Cornelio, Saswati Dana, Achille Fokoue, Dinesh Garg, Alfio Gliozzo, Sairam Gurajada, Hima Karanam, Naweed Khan, Dinesh Khandelwal, Young-Suk Lee, Yunyao Li, Francois P. S. Luus, Ndivhuwo Makondo, Nandana Mihindukulasooriya, Tahira Naseem, Sumit Neelam, Lucian Popa, Revanth Gangi Reddy, Ryan Riegel, Gaetano Rossiello, Udit Sharma, G. P. Shrivatsa Bhargav, Mo Yu:
Question Answering over Knowledge Bases by Leveraging Semantic Parsing and Neuro-Symbolic Reasoning. CoRR abs/2012.01707 (2020)
2010 – 2019
- 2019
- [i3]Vittorio Castelli, Rishav Chakravarti, Saswati Dana, Anthony Ferritto, Radu Florian, Martin Franz, Dinesh Garg, Dinesh Khandelwal, J. Scott McCarley, Mike McCawley, Mohamed Nasr, Lin Pan, Cezar Pendus, John F. Pitrelli, Saurabh Pujar, Salim Roukos, Andrzej Sakrajda, Avirup Sil, Rosario Uceda-Sosa, Todd Ward, Rong Zhang:
The TechQA Dataset. CoRR abs/1911.02984 (2019) - 2018
- [c1]Dinesh Khandelwal, Parag Singla, Chetan Arora:
Learning Higher Order Potentials for MRFs. WACV 2018: 812-820 - [i2]Dinesh Khandelwal, Suyash Agrawal, Parag Singla, Chetan Arora:
Exploiting Test Time Evidence to Improve Predictions of Deep Neural Networks. CoRR abs/1811.09796 (2018) - 2017
- [j2]Yamuna Prasad, Dinesh Khandelwal, K. K. Biswas:
Max-Margin feature selection. Pattern Recognit. Lett. 95: 51-57 (2017) - 2016
- [j1]Dinesh Khandelwal, Kush Bhatia, Chetan Arora, Parag Singla:
Lazy Generic Cuts. Comput. Vis. Image Underst. 143: 80-91 (2016) - [i1]Yamuna Prasad, Dinesh Khandelwal, K. K. Biswas:
Max-Margin Feature Selection. CoRR abs/1606.04506 (2016)
Coauthor Index
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