Lazy Generic Cuts. - Dinesh Khandelwal; Kush Bhatia; Chetan Arora 001; Parag Singla (Comput. Vis. Image Underst., 2016)

Max-Margin feature selection. - Yamuna Prasad; Dinesh Khandelwal; K. K. Biswas (Pattern Recognit. Lett., 2017)

Learning Higher Order Potentials for MRFs. - Dinesh Khandelwal; Parag Singla; Chetan Arora 001 (WACV, 2018)

Exploiting Test Time Evidence to Improve Predictions of Deep Neural Networks. - Dinesh Khandelwal; Suyash Agrawal; Parag Singla; Chetan Arora 001 (CoRR, 2018)

Translucent Answer Predictions in Multi-Hop Reading Comprehension. - G. P. Shrivatsa Bhargav; Michael R. Glass; Dinesh Garg; Shirish K. Shevade; Saswati Dana; Dinesh Khandelwal; L. Venkata Subramaniam; Alfio Gliozzo (AAAI, 2020)

The TechQA Dataset. - 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 003; et al. (ACL, 2020)

Inductive Quantum Embedding. - Santosh K. Srivastava; Dinesh Khandelwal; Dhiraj Madan; Dinesh Garg; Hima Karanam; L. Venkata Subramaniam (NeurIPS, 2020)

Question Answering over Knowledge Bases by Leveraging Semantic Parsing and Neuro-Symbolic Reasoning. - Pavan Kapanipathi; Ibrahim Abdelaziz; Srinivas Ravishankar; Salim Roukos; Alexander G. Gray; Ramón Fernandez Astudillo; Maria Chang 001; Cristina Cornelio; Saswati Dana; Achille Fokoue; Dinesh Garg; Alfio Gliozzo; et al. (CoRR, 2020)

Explanations for CommonsenseQA: New Dataset and Models. - Shourya Aggarwal; Divyanshu Mandowara; Vishwajeet Agrawal; Dinesh Khandelwal; Parag Singla; Dinesh Garg (ACL/IJCNLP (1), 2021)

Leveraging Abstract Meaning Representation for Knowledge Base Question Answering. - Pavan Kapanipathi; Ibrahim Abdelaziz; Srinivas Ravishankar; Salim Roukos; Alexander G. Gray; Ramón Fernandez Astudillo; Maria Chang 001; Cristina Cornelio; Saswati Dana; Achille Fokoue; Dinesh Garg; Alfio Gliozzo; et al. (ACL/IJCNLP (Findings), 2021)

Semantic Answer Type Prediction. - G. P. Shrivatsa Bhargav; Dinesh Khandelwal; Dinesh Garg; Saswati Dana (SMART@ISWC, 2021)

Knowledge Graph Question Answering via SPARQL Silhouette Generation. - Sukannya Purkayastha; Saswati Dana; Dinesh Garg; Dinesh Khandelwal; G. P. Shrivatsa Bhargav (CoRR, 2021)

SYGMA: System for Generalizable Modular Question Answering OverKnowledge Bases. - Sumit Neelam; Udit Sharma; Hima Karanam; Shajith Ikbal; Pavan Kapanipathi; Ibrahim Abdelaziz; Nandana Mihindukulasooriya; Young-Suk Lee 001; Santosh K. Srivastava; Cezar Pendus; Saswati Dana; Dinesh Garg; et al. (CoRR, 2021)

SYGMA: A System for Generalizable and Modular Question Answering Over Knowledge Bases. - Sumit Neelam; Udit Sharma; Hima Karanam; Shajith Ikbal; Pavan Kapanipathi; Ibrahim Abdelaziz; Nandana Mihindukulasooriya; Young-Suk Lee 001; Santosh K. Srivastava; Cezar Pendus; Saswati Dana; Dinesh Garg; et al. (EMNLP (Findings), 2022)

A Deep Neural Approach to KGQA via SPARQL Silhouette Generation. - Sukannya Purkayastha; Saswati Dana; Dinesh Garg; Dinesh Khandelwal; G. P. Shrivatsa Bhargav (IJCNN, 2022)

Zero-shot Entity Linking with Less Data. - G. P. Shrivatsa Bhargav; Dinesh Khandelwal; Saswati Dana; Dinesh Garg; Pavan Kapanipathi; Salim Roukos; Alexander G. Gray; L. Venkata Subramaniam (NAACL-HLT (Findings), 2022)

A Benchmark for Generalizable and Interpretable Temporal Question Answering over Knowledge Bases. - Sumit Neelam; Udit Sharma; Hima Karanam; Shajith Ikbal; Pavan Kapanipathi; Ibrahim Abdelaziz; Nandana Mihindukulasooriya; Young-Suk Lee 001; Santosh K. Srivastava; Cezar Pendus; Saswati Dana; Dinesh Garg; et al. (CoRR, 2022)

Targeted Extraction of Temporal Facts from Textual Resources for Improved Temporal Question Answering over Knowledge Bases. - Nithish Kannen; Udit Sharma; Sumit Neelam; Dinesh Khandelwal; Shajith Ikbal; Hima Karanam; L. Venkata Subramaniam (CoRR, 2022)

Best of Both Worlds: Towards Improving Temporal Knowledge Base Question Answering via Targeted Fact Extraction. - Nithish Kannen; Udit Sharma; Sumit Neelam; Dinesh Khandelwal; Shajith Ikbal; Hima Karanam; L. Venkata Subramaniam (EMNLP, 2023)

Image Manipulation via Multi-Hop Instructions - A New Dataset and Weakly-Supervised Neuro-Symbolic Approach. - Harman Singh; Poorva Garg; Mohit Gupta; Kevin Shah; Ashish Goswami; Satyam Modi; Arnab Kumar Mondal; Dinesh Khandelwal; Dinesh Garg; Parag Singla (EMNLP, 2023)

Image Manipulation via Multi-Hop Instructions - A New Dataset and Weakly-Supervised Neuro-Symbolic Approach. - Harman Singh; Poorva Garg; Mohit Gupta; Kevin Shah; Arnab Kumar Mondal; Dinesh Khandelwal; Parag Singla; Dinesh Garg (CoRR, 2023)

Fill in the Blank: Exploring and Enhancing LLM Capabilities for Backward Reasoning in Math Word Problems. - Aniruddha Deb; Neeva Oza; Sarthak Singla; Dinesh Khandelwal; Dinesh Garg; Parag Singla (CoRR, 2023)

Systematic Knowledge Injection into Large Language Models via Diverse Augmentation for Domain-Specific RAG. - Kushagra Bhushan; Yatin Nandwani; Dinesh Khandelwal; Sonam Gupta 001; Gaurav Pandey 001; Dinesh Raghu; Sachindra Joshi (NAACL (Findings), 2025)

Selective Self-to-Supervised Fine-Tuning for Generalization in Large Language Models. - Sonam Gupta 001; Yatin Nandwani; Asaf Yehudai; Dinesh Khandelwal; Dinesh Raghu; Sachindra Joshi (NAACL (Findings), 2025)

CETBench: A Novel Dataset constructed via Transformations over Programs for Benchmarking LLMs for Code-Equivalence Checking. - Neeva Oza; Ishaan Govil; Parul Gupta; Dinesh Khandelwal; Dinesh Garg; Parag Singla (CoRR, 2025)