Dinesh Khandelwal

29 papers A* 5A 1B 1Journal 15Unranked 7
YearRankTypeTitle / Venue / Authors
2025 J jnl
CETBench: A Novel Dataset constructed via Transformations over Programs for Benchmarking LLMs for Code-Equivalence Checking.
CoRR
Neeva Oza, Ishaan Govil, Parul Gupta, Dinesh Khandelwal, Dinesh Garg, Parag Singla
2025 — conf
Selective Self-to-Supervised Fine-Tuning for Generalization in Large Language Models.
NAACL (Findings)
Sonam Gupta, Yatin Nandwani, Asaf Yehudai, Dinesh Khandelwal, Dinesh Raghu, Sachindra Joshi
2025 J jnl
Selective Self-to-Supervised Fine-Tuning for Generalization in Large Language Models.
CoRR
Sonam Gupta, Yatin Nandwani, Asaf Yehudai, Dinesh Khandelwal, Dinesh Raghu, Sachindra Joshi
2025 — conf
Systematic Knowledge Injection into Large Language Models via Diverse Augmentation for Domain-Specific RAG.
NAACL (Findings)
Kushagra Bhushan, Yatin Nandwani, Dinesh Khandelwal, Sonam Gupta, Gaurav Pandey, Dinesh Raghu, Sachindra Joshi
2025 J jnl
Systematic Knowledge Injection into Large Language Models via Diverse Augmentation for Domain-Specific RAG.
CoRR
Kushagra Bhushan, Yatin Nandwani, Dinesh Khandelwal, Sonam Gupta, Gaurav Pandey, Dinesh Raghu, Sachindra Joshi
2023 A* conf
Best of Both Worlds: Towards Improving Temporal Knowledge Base Question Answering via Targeted Fact Extraction.
EMNLP
Nithish Kannen, Udit Sharma, Sumit Neelam, Dinesh Khandelwal, Shajith Ikbal, Hima Karanam, L. Venkata Subramaniam
2023 J jnl
Fill in the Blank: Exploring and Enhancing LLM Capabilities for Backward Reasoning in Math Word Problems.
CoRR
Aniruddha Deb, Neeva Oza, Sarthak Singla, Dinesh Khandelwal, Dinesh Garg, Parag Singla
2023 A* conf
Image Manipulation via Multi-Hop Instructions - A New Dataset and Weakly-Supervised Neuro-Symbolic Approach.
EMNLP
Harman Singh, Poorva Garg, Mohit Gupta, Kevin Shah, Ashish Goswami, Satyam Modi, Arnab Kumar Mondal, Dinesh Khandelwal, Dinesh Garg, Parag Singla
2023 J jnl
Image Manipulation via Multi-Hop Instructions - A New Dataset and Weakly-Supervised Neuro-Symbolic Approach.
CoRR
Harman Singh, Poorva Garg, Mohit Gupta, Kevin Shah, Arnab Kumar Mondal, Dinesh Khandelwal, Parag Singla, Dinesh Garg
2022 J jnl
A Benchmark for Generalizable and Interpretable Temporal Question Answering over Knowledge Bases.
CoRR
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
2022 B conf
A Deep Neural Approach to KGQA via SPARQL Silhouette Generation.
IJCNN
Sukannya Purkayastha, Saswati Dana, Dinesh Garg, Dinesh Khandelwal, G. P. Shrivatsa Bhargav
2022 — conf
SYGMA: A System for Generalizable and Modular Question Answering Over Knowledge Bases.
EMNLP (Findings)
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
2022 J jnl
Targeted Extraction of Temporal Facts from Textual Resources for Improved Temporal Question Answering over Knowledge Bases.
CoRR
Nithish Kannen, Udit Sharma, Sumit Neelam, Dinesh Khandelwal, Shajith Ikbal, Hima Karanam, L. Venkata Subramaniam
2022 — conf
Zero-shot Entity Linking with Less Data.
NAACL-HLT (Findings)
G. P. Shrivatsa Bhargav, Dinesh Khandelwal, Saswati Dana, Dinesh Garg, Pavan Kapanipathi, Salim Roukos, Alexander G. Gray, L. Venkata Subramaniam
2021 — conf
Explanations for CommonsenseQA: New Dataset and Models.
ACL/IJCNLP (1)
Shourya Aggarwal, Divyanshu Mandowara, Vishwajeet Agrawal, Dinesh Khandelwal, Parag Singla, Dinesh Garg
2021 J jnl
Knowledge Graph Question Answering via SPARQL Silhouette Generation.
CoRR
Sukannya Purkayastha, Saswati Dana, Dinesh Garg, Dinesh Khandelwal, G. P. Shrivatsa Bhargav
2021 — conf
Leveraging Abstract Meaning Representation for Knowledge Base Question Answering.
ACL/IJCNLP (Findings)
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
2021 J jnl
SYGMA: System for Generalizable Modular Question Answering OverKnowledge Bases.
CoRR
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
2021 — conf
Semantic Answer Type Prediction.
SMART@ISWC
G. P. Shrivatsa Bhargav, Dinesh Khandelwal, Dinesh Garg, Saswati Dana
2020 A* conf
Inductive Quantum Embedding.
NeurIPS
Santosh K. Srivastava, Dinesh Khandelwal, Dhiraj Madan, Dinesh Garg, Hima Karanam, L. Venkata Subramaniam
2020 J jnl
Question Answering over Knowledge Bases by Leveraging Semantic Parsing and Neuro-Symbolic Reasoning.
CoRR
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
2020 A* conf
The TechQA Dataset.
ACL
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
2020 A* conf
Translucent Answer Predictions in Multi-Hop Reading Comprehension.
AAAI
G. P. Shrivatsa Bhargav, Michael R. Glass, Dinesh Garg, Shirish K. Shevade, Saswati Dana, Dinesh Khandelwal, L. Venkata Subramaniam, Alfio Gliozzo
2019 J jnl
The TechQA Dataset.
CoRR
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
2018 J jnl
Exploiting Test Time Evidence to Improve Predictions of Deep Neural Networks.
CoRR
Dinesh Khandelwal, Suyash Agrawal, Parag Singla, Chetan Arora
2018 A conf
Learning Higher Order Potentials for MRFs.
WACV
Dinesh Khandelwal, Parag Singla, Chetan Arora
2017 J jnl
Max-Margin feature selection.
Pattern Recognit. Lett.
Yamuna Prasad, Dinesh Khandelwal, K. K. Biswas
2016 J jnl
Lazy Generic Cuts.
Comput. Vis. Image Underst.
Dinesh Khandelwal, Kush Bhatia, Chetan Arora, Parag Singla
2016 J jnl
Max-Margin Feature Selection.
CoRR
Yamuna Prasad, Dinesh Khandelwal, K. K. Biswas