Dinesh Garg

72 papers A* 13A 6B 5Misc 1Journal 27Unranked 19
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
Transforming Code Understanding: Clustering-Based Retrieval for Improved Summarization in Domain-Specific Languages.
COLING (Industry)
Baban Gain, Dibyanayan Bandyopadhyay, Samrat Mukherjee, Aryan Sahoo, Saswati Dana, Palanivel A. Kodeswaran, Sayandeep Sen, Asif Ekbal, Dinesh Garg
2024 J jnl
An Approach to Build Zero-Shot Slot-Filling System for Industry-Grade Conversational Assistants.
CoRR
G. P. Shrivatsa Bhargav, Sumit Neelam, Udit Sharma, Shajith Ikbal, Dheeraj Sreedhar, Hima Karanam, Sachindra Joshi, Pankaj Dhoolia, Dinesh Garg, Kyle Croutwater, Haode Qi, Eric Wayne, J. William Murdock
2024 — conf
Read between the lines - Functionality Extraction From READMEs.
NAACL-HLT (Findings)
Prince Kumar, Srikanth Tamilselvam, Dinesh Garg
2024 J jnl
Read between the lines - Functionality Extraction From READMEs.
CoRR
Prince Kumar, Srikanth Tamilselvam, Dinesh Garg
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 A* conf
First Workshop on Content Understanding and Generation for E-commerce.
KDD
Sumit Negi, Manisha Verma, Rajdeep H. Banerjee, Pooja A, Lydia B. Chilton, Mithun Das Gupta, Vinay P. Namboodiri, Dinesh Garg
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
Towards a Semantic Information Theory (Introducing Quantum Corollas).
CoRR
Philip Tetlow, Dinesh Garg, Leigh Chase, Mark Mattingley-Scott, Nicholas Bronn, Kugendran Naidoo, Emil Reinert
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
Deep Domain Adaptation under Label Scarcity.
COMAD/CODS
Amar Prakash Azad, Dinesh Garg, Priyanka Agrawal, Arun Kumar
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
Span Selection Pre-training for Question Answering.
ACL
Michael R. Glass, Alfio Gliozzo, Rishav Chakravarti, Anthony Ferritto, Lin Pan, G. P. Shrivatsa Bhargav, Dinesh Garg, Avirup Sil
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
Improved linear embeddings via Lagrange duality.
Mach. Learn.
Kshiteej Sheth, Dinesh Garg, Anirban Dasgupta
2019 J jnl
Prediction of the disease controllability in a complex network using machine learning algorithms.
CoRR
Richa Tripathi, Amit Reza, Dinesh Garg
2019 A* conf
Quantum Embedding of Knowledge for Reasoning.
NeurIPS
Dinesh Garg, Shajith Ikbal, Santosh K. Srivastava, Harit Vishwakarma, Hima P. Karanam, L. Venkata Subramaniam
2019 J jnl
Span Selection Pre-training for Question Answering.
CoRR
Michael R. Glass, Alfio Gliozzo, Rishav Chakravarti, Anthony Ferritto, Lin Pan, G. P. Shrivatsa Bhargav, Dinesh Garg, Avirup Sil
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
Deep Domain Adaptation under Deep Label Scarcity.
CoRR
Amar Prakash Azad, Dinesh Garg, Priyanka Agrawal, Arun Kumar
2017 A conf
A Sparse Nonlinear Classifier Design Using AUC Optimization.
SDM
Vishal Kakkar, Shirish K. Shevade, S. Sundararajan, Dinesh Garg
2017 J jnl
Improved Linear Embeddings via Lagrange Duality.
CoRR
Kshiteej Sheth, Dinesh Garg, Anirban Dasgupta
2017 A* conf
Latent Space Embedding for Retrieval in Question-Answer Archives.
EMNLP
Deepak P, Dinesh Garg, Shirish K. Shevade
2017 A* conf
Manipulating Gale-Shapley Algorithm: Preserving Stability and Remaining Inconspicuous.
IJCAI
Rohit Vaish, Dinesh Garg
2016 J jnl
A Robust UCB Scheme for Active Learning in Regression from Strategic Crowds.
CoRR
Divya Padmanabhan, Satyanath Bhat, Dinesh Garg, Shirish K. Shevade, Y. Narahari
2016 B conf
A Robust UCB scheme for active learning in regression from strategic crowds.
IJCNN
Divya Padmanabhan, Satyanath Bhat, Dinesh Garg, Shirish K. Shevade, Y. Narahari
2016 J jnl
A Sparse Nonlinear Classifier Design Using AUC Optimization.
CoRR
Vishal Kakkar, Shirish K. Shevade, S. Sundararajan, Dinesh Garg
2016 — conf
Edge conductance estimation using MCMC.
Allerton
Ashish Bora, Vivek S. Borkar, Dinesh Garg, Rajesh Sundaresan
2016 J jnl
Fast rumor source identification via random walks.
Soc. Netw. Anal. Min.
Alankar Jain, Vivek S. Borkar, Dinesh Garg
2015 A conf
Truthful Interval Cover Mechanisms for Crowdsourcing Applications.
AAMAS
Pankaj Dayama, Balakrishnan Narayanaswamy, Dinesh Garg, Y. Narahari
2014 J jnl
An Improved Block Coordinate Descent Method for Quadratic Programming in High Dimensions.
CoRR
Gugan Thoppe, Vivek S. Borkar, Dinesh Garg
2014 Misc conf
Discovering signature of social networks with application to community detection.
COMSNETS
Ramasuri Narayanam, Dinesh Garg, Hemank Lamba
2014 A conf
Learning to Propagate Rare Labels.
CIKM
Rakesh Pimplikar, Dinesh Garg, Deepesh Bharani, Gyana R. Parija
2014 A conf
Submodularity in Team Formation Problem.
SDM
Avradeep Bhowmik, Vivek S. Borkar, Dinesh Garg, Madhavan Pallan
2012 J jnl
Mechanism Design for Cost Optimal PAC Learning in the Presence of Strategic Noisy Annotators
CoRR
Dinesh Garg, Sourangshu Bhattacharya, S. Sundararajan, Shirish K. Shevade
2012 A conf
Mechanism Design for Cost Optimal PAC Learning in the Presence of Strategic Noisy Annotators.
UAI
Dinesh Garg, Sourangshu Bhattacharya, S. Sundararajan, Shirish K. Shevade
2012 J jnl
Mechanism Design for Time Critical and Cost Critical Task Execution via Crowdsourcing
CoRR
Swaprava Nath, Pankaj Dayama, Dinesh Garg, Y. Narahari, James Y. Zou
2012 — conf
Mechanism Design for Time Critical and Cost Critical Task Execution via Crowdsourcing.
WINE
Swaprava Nath, Pankaj Dayama, Dinesh Garg, Yadati Narahari, James Y. Zou
2012 A* conf
Threats and Trade-Offs in Resource Critical Crowdsourcing Tasks Over Networks.
AAAI
Swaprava Nath, Pankaj Dayama, Dinesh Garg, Y. Narahari, James Y. Zou
2011 — conf
A Game Theoretic Approach for Feature Clustering and Its Application to Feature Selection.
PAKDD (1)
Dinesh Garg, Sundararajan Sellamanickam, Shirish K. Shevade
2011 A* conf
Adaptive policies for selecting groupon style chunked reward ads in a stochastic knapsack framework.
WWW
Michael Grabchak, Narayan L. Bhamidipati, Rushi Bhatt, Dinesh Garg
2009 J jnl
An Optimal Mechanism for Sponsored Search Auctions on the Web and Comparison With Other Mechanisms.
IEEE Trans Autom. Sci. Eng.
Dinesh Garg, Y. Narahari
2009 B conf
CAESAR: A Context-Aware, Social Recommender System for Low-End Mobile Devices.
Mobile Data Management
Lakshmish Ramaswamy, P. Deepak, Ramana Polavarapu, Kutila Gunasekera, Dinesh Garg, Karthik Visweswariah, Shivkumar Kalyanaraman
2009 — book
Game Theoretic Problems in Network Economics and Mechanism Design Solutions.
Y. Narahari, Dinesh Garg, Ramasuri Narayanam, V. Hastagiri Prakash
2009 B conf
Nash Bargaining Based Ad Networks for Sponsored Search Auctions.
CEC
Ramakrishnan Kannan, Dinesh Garg, Karthik Subbian, Y. Narahari
2008 — conf
A Nash bargaining approach to retention enhancing bid optimization in sponsored search auctions with discrete bids.
CASE
Ramakrishnan Kannan, Dinesh Garg, Karthik Subbian, Yadati Narahari
2008 — conf
Auction Based Models for Ticket Allocation Problem in IT Service Delivery Industry.
IEEE SCC (1)
Prasad M. Deshpande, Dinesh Garg, Ramasuri Narayanam
2008 J jnl
Mechanism Design for Single Leader Stackelberg Problems and Application to Procurement Auction Design.
IEEE Trans Autom. Sci. Eng.
Dinesh Garg, Y. Narahari
2008 — conf
Mining Top Issues from Contact Center Logs for Self Help Portals.
IEEE SCC (2)
Dinesh Garg, Nanda Kambhatla, Maja Vukovic, Gopal Pingali
2007 J jnl
A primal-dual algorithm for computing Fisher equilibrium in the absence of gross substitutability property.
Theor. Comput. Sci.
Dinesh Garg, Kamal Jain, Kunal Talwar, Vijay V. Vazirani
2007 — conf
Design of an Optimal Auction for Sponsored Search Auction.
CEC/EEE
Dinesh Garg, Y. Narahari, Siva Sankar Reddy
2007 — conf
Efficient Internet Chat Services for Help Desk Agents.
IEEE SCC
Zon-Yin Shae, Dinesh Garg, Rajarshi Bhose, Ritabrata Mukherjee, Sinem Güven
2006 J jnl
Achieving sharp deliveries in supply chains through variance pool allocation.
Eur. J. Oper. Res.
Dinesh Garg, Y. Narahari, Nukala Viswanadham
2005 B conf
A Groves Mechanism Approach to Decentralized Design of Supply Chains.
CEC
Dinesh Garg, Yadati Narahari, Earnest Foster, Devadatta M. Kulkarni, Jeffrey D. Tew
2005 — conf
A Primal-Dual Algorithm for Computing Fisher Equilibrium in the Absence of Gross Substitutability Property.
WINE
Dinesh Garg, Kamal Jain, Kunal Talwar, Vijay V. Vazirani
2005 — conf
Design of Incentive Compatible Mechanisms for Stackelberg Problems.
WINE
Dinesh Garg, Yadati Narahari
2005 — conf
Price of Anarchy of Network Routing Games with Incomplete Information.
WINE
Dinesh Garg, Yadati Narahari
2004 J jnl
Design of six sigma supply chains.
IEEE Trans Autom. Sci. Eng.
Dinesh Garg, Yadati Narahari, Nukala Viswanadham
2003 A conf
A new approach to achieving sharp and timely deliveries in supply chain networks.
IROS
Dinesh Garg, Yadati Narahari, Nukala Viswanadham
2003 A* conf
Design of six sigma supply chains.
ICRA
Dinesh Garg, Yadati Narahari, Nukala Viswanadham
2002 A* conf
Achieving Sharp Deliveries in Supply Chains through Variance Pool Allocation.
ICRA
Dinesh Garg, Yadati Narahari, Nukala Viswanadham