Dinesh Garg

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 37

Top Topics

High Dimensions

Question Answer

Image Manipulation

Top Venues

Publications

Prince Kumar, Srikanth Tamilselvam, Dinesh Garg
Read between the lines - Functionality Extraction From READMEs. CoRR (2024)
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
An Approach to Build Zero-Shot Slot-Filling System for Industry-Grade Conversational Assistants. CoRR (2024)
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)
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 (2023)
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 (2023)
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 (2022)
Sumit Negi, Manisha Verma, Rajdeep H. Banerjee, Pooja A, Lydia Chilton, Mithun Das Gupta, Vinay P. Namboodiri, Dinesh Garg
First Workshop on Content Understanding and Generation for E-commerce. KDD (2022)
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)
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)
Sukannya Purkayastha, Saswati Dana, Dinesh Garg, Dinesh Khandelwal, G. P. Shrivatsa Bhargav
A Deep Neural Approach to KGQA via SPARQL Silhouette Generation. IJCNN (2022)
Philip Tetlow, Dinesh Garg, Leigh Chase, Mark Mattingley-Scott, Nicholas Bronn, Kugendran Naidoo, Emil Reinert
Towards a Semantic Information Theory (Introducing Quantum Corollas). CoRR (2022)
Shourya Aggarwal, Divyanshu Mandowara, Vishwajeet Agrawal, Dinesh Khandelwal, Parag Singla, Dinesh Garg
Explanations for CommonsenseQA: New Dataset and Models. ACL/IJCNLP (1) (2021)
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)
G. P. Shrivatsa Bhargav, Dinesh Khandelwal, Dinesh Garg, Saswati Dana
Semantic Answer Type Prediction. SMART@ISWC (2021)
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 (2021)
Amar Prakash Azad, Dinesh Garg, Priyanka Agrawal, Arun Kumar
Deep Domain Adaptation under Label Scarcity. COMAD/CODS (2021)
Sukannya Purkayastha, Saswati Dana, Dinesh Garg, Dinesh Khandelwal, G. P. Shrivatsa Bhargav
Knowledge Graph Question Answering via SPARQL Silhouette Generation. CoRR (2021)
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 (2020)
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)
Santosh K. Srivastava, Dinesh Khandelwal, Dhiraj Madan, Dinesh Garg, Hima Karanam, L. Venkata Subramaniam
Inductive Quantum Embedding. NeurIPS (2020)
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)
Michael R. Glass, Alfio Gliozzo, Rishav Chakravarti, Anthony Ferritto, Lin Pan, G. P. Shrivatsa Bhargav, Dinesh Garg, Avirup Sil
Span Selection Pre-training for Question Answering. ACL (2020)
Michael R. Glass, Alfio Gliozzo, Rishav Chakravarti, Anthony Ferritto, Lin Pan, G. P. Shrivatsa Bhargav, Dinesh Garg, Avirup Sil
Span Selection Pre-training for Question Answering. CoRR (2019)
Dinesh Garg, Shajith Ikbal, Santosh K. Srivastava, Harit Vishwakarma, Hima P. Karanam, L. Venkata Subramaniam
Quantum Embedding of Knowledge for Reasoning. NeurIPS (2019)
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 (2019)
Richa Tripathi, Amit Reza, Dinesh Garg
Prediction of the disease controllability in a complex network using machine learning algorithms. CoRR (2019)
Kshiteej Sheth, Dinesh Garg, Anirban Dasgupta
Improved linear embeddings via Lagrange duality. Mach. Learn. 108 (4) (2019)
Amar Prakash Azad, Dinesh Garg, Priyanka Agrawal, Arun Kumar
Deep Domain Adaptation under Deep Label Scarcity. CoRR (2018)
Kshiteej Sheth, Dinesh Garg, Anirban Dasgupta
Improved Linear Embeddings via Lagrange Duality. CoRR (2017)
Deepak P, Dinesh Garg, Shirish K. Shevade
Latent Space Embedding for Retrieval in Question-Answer Archives. EMNLP (2017)
Rohit Vaish, Dinesh Garg
Manipulating Gale-Shapley Algorithm: Preserving Stability and Remaining Inconspicuous. IJCAI (2017)
Vishal Kakkar, Shirish K. Shevade, S. Sundararajan, Dinesh Garg
A Sparse Nonlinear Classifier Design Using AUC Optimization. SDM (2017)
Divya Padmanabhan, Satyanath Bhat, Dinesh Garg, Shirish K. Shevade, Y. Narahari
A Robust UCB Scheme for Active Learning in Regression from Strategic Crowds. CoRR (2016)
Alankar Jain, Vivek S. Borkar, Dinesh Garg
Fast rumor source identification via random walks. Soc. Netw. Anal. Min. 6 (1) (2016)
Vishal Kakkar, Shirish K. Shevade, S. Sundararajan, Dinesh Garg
A Sparse Nonlinear Classifier Design Using AUC Optimization. CoRR (2016)
Divya Padmanabhan, Satyanath Bhat, Dinesh Garg, Shirish K. Shevade, Y. Narahari
A Robust UCB scheme for active learning in regression from strategic crowds. IJCNN (2016)
Ashish Bora, Vivek S. Borkar, Dinesh Garg, Rajesh Sundaresan
Edge conductance estimation using MCMC. Allerton (2016)
Pankaj Dayama, Balakrishnan Narayanaswamy, Dinesh Garg, Y. Narahari
Truthful Interval Cover Mechanisms for Crowdsourcing Applications. AAMAS (2015)
Avradeep Bhowmik, Vivek S. Borkar, Dinesh Garg, Madhavan Pallan
Submodularity in Team Formation Problem. SDM (2014)
Ramasuri Narayanam, Dinesh Garg, Hemank Lamba
Discovering signature of social networks with application to community detection. COMSNETS (2014)
Rakesh Pimplikar, Dinesh Garg, Deepesh Bharani, Gyana R. Parija
Learning to Propagate Rare Labels. CIKM (2014)
Gugan Thoppe, Vivek S. Borkar, Dinesh Garg
An Improved Block Coordinate Descent Method for Quadratic Programming in High Dimensions. CoRR (2014)
Swaprava Nath, Pankaj Dayama, Dinesh Garg, Yadati Narahari, James Y. Zou
Mechanism Design for Time Critical and Cost Critical Task Execution via Crowdsourcing. WINE (2012)
Swaprava Nath, Pankaj Dayama, Dinesh Garg, Y. Narahari, James Y. Zou
Mechanism Design for Time Critical and Cost Critical Task Execution via Crowdsourcing CoRR (2012)
Dinesh Garg, Sourangshu Bhattacharya, S. Sundararajan, Shirish K. Shevade
Mechanism Design for Cost Optimal PAC Learning in the Presence of Strategic Noisy Annotators CoRR (2012)
Dinesh Garg, Sourangshu Bhattacharya, S. Sundararajan, Shirish K. Shevade
Mechanism Design for Cost Optimal PAC Learning in the Presence of Strategic Noisy Annotators. UAI (2012)
Swaprava Nath, Pankaj Dayama, Dinesh Garg, Y. Narahari, James Y. Zou
Threats and Trade-Offs in Resource Critical Crowdsourcing Tasks Over Networks. AAAI (2012)
Michael Grabchak, Narayan L. Bhamidipati, Rushi Bhatt, Dinesh Garg
Adaptive policies for selecting groupon style chunked reward ads in a stochastic knapsack framework. WWW (2011)
Dinesh Garg, Sundararajan Sellamanickam, Shirish K. Shevade
A Game Theoretic Approach for Feature Clustering and Its Application to Feature Selection. PAKDD (1) (2011)
Ramakrishnan Kannan, Dinesh Garg, Karthik Subbian, Y. Narahari
Nash Bargaining Based Ad Networks for Sponsored Search Auctions. CEC (2009)
Dinesh Garg, Y. Narahari
An Optimal Mechanism for Sponsored Search Auctions on the Web and Comparison With Other Mechanisms. IEEE Trans Autom. Sci. Eng. 6 (4) (2009)
Lakshmish Ramaswamy, P. Deepak, Ramana Polavarapu, Kutila Gunasekera, Dinesh Garg, Karthik Visweswariah, Shivkumar Kalyanaraman
CAESAR: A Context-Aware, Social Recommender System for Low-End Mobile Devices. Mobile Data Management (2009)
Ramakrishnan Kannan, Dinesh Garg, Karthik Subbian, Yadati Narahari
A Nash bargaining approach to retention enhancing bid optimization in sponsored search auctions with discrete bids. CASE (2008)
Dinesh Garg, Y. Narahari
Mechanism Design for Single Leader Stackelberg Problems and Application to Procurement Auction Design. IEEE Trans Autom. Sci. Eng. 5 (3) (2008)
Dinesh Garg, Nanda Kambhatla, Maja Vukovic, Gopal Pingali
Mining Top Issues from Contact Center Logs for Self Help Portals. IEEE SCC (2) (2008)
Prasad M. Deshpande, Dinesh Garg, Ramasuri Narayanam
Auction Based Models for Ticket Allocation Problem in IT Service Delivery Industry. IEEE SCC (1) (2008)
Dinesh Garg, Kamal Jain, Kunal Talwar, Vijay V. Vazirani
A primal-dual algorithm for computing Fisher equilibrium in the absence of gross substitutability property. Theor. Comput. Sci. 378 (2) (2007)
Dinesh Garg, Y. Narahari, Siva Sankar Reddy
Design of an Optimal Auction for Sponsored Search Auction. CEC/EEE (2007)
Zon-Yin Shae, Dinesh Garg, Rajarshi Bhose, Ritabrata Mukherjee, Sinem Güven
Efficient Internet Chat Services for Help Desk Agents. IEEE SCC (2007)
Dinesh Garg, Y. Narahari, Nukala Viswanadham
Achieving sharp deliveries in supply chains through variance pool allocation. Eur. J. Oper. Res. 171 (1) (2006)
Dinesh Garg, Yadati Narahari
Design of Incentive Compatible Mechanisms for Stackelberg Problems. WINE (2005)
Dinesh Garg, Yadati Narahari
Price of Anarchy of Network Routing Games with Incomplete Information. WINE (2005)
Dinesh Garg, Kamal Jain, Kunal Talwar, Vijay V. Vazirani
A Primal-Dual Algorithm for Computing Fisher Equilibrium in the Absence of Gross Substitutability Property. WINE (2005)
Dinesh Garg, Yadati Narahari, Earnest Foster, Devadatta M. Kulkarni, Jeffrey D. Tew
A Groves Mechanism Approach to Decentralized Design of Supply Chains. CEC (2005)
Dinesh Garg, Yadati Narahari, Nukala Viswanadham
Design of six sigma supply chains. IEEE Trans Autom. Sci. Eng. 1 (1) (2004)
Dinesh Garg, Yadati Narahari, Nukala Viswanadham
Design of six sigma supply chains. ICRA (2003)
Dinesh Garg, Yadati Narahari, Nukala Viswanadham
A new approach to achieving sharp and timely deliveries in supply chain networks. IROS (2003)
Dinesh Garg, Yadati Narahari, Nukala Viswanadham
Achieving Sharp Deliveries in Supply Chains through Variance Pool Allocation. ICRA (2002)