A new approach to achieving sharp and timely deliveries in supply chain networks. - Dinesh Garg; Yadati Narahari; Nukala Viswanadham (IROS, 2003)

Design of six sigma supply chains. - Dinesh Garg; Yadati Narahari; Nukala Viswanadham (IEEE Trans Autom. Sci. Eng., 2004)

A Groves Mechanism Approach to Decentralized Design of Supply Chains. - Dinesh Garg; Yadati Narahari; Earnest Foster; Devadatta M. Kulkarni; Jeffrey D. Tew (CEC, 2005)

Design of Incentive Compatible Mechanisms for Stackelberg Problems. - Dinesh Garg; Yadati Narahari (WINE, 2005)

Price of Anarchy of Network Routing Games with Incomplete Information. - Dinesh Garg; Yadati Narahari (WINE, 2005)

Achieving sharp deliveries in supply chains through variance pool allocation. - Dinesh Garg; Y. Narahari; Nukala Viswanadham (Eur. J. Oper. Res., 2006)

Efficient Internet Chat Services for Help Desk Agents. - Zon-Yin Shae; Dinesh Garg; Rajarshi Bhose; Ritabrata Mukherjee; Sinem Güven (IEEE SCC, 2007)

Design of an Optimal Auction for Sponsored Search Auction. - Dinesh Garg; Y. Narahari; Siva Sankar Reddy (CEC/EEE, 2007)

A primal-dual algorithm for computing Fisher equilibrium in the absence of gross substitutability property. - Dinesh Garg; Kamal Jain; Kunal Talwar; Vijay V. Vazirani (Theor. Comput. Sci., 2007)

Auction Based Models for Ticket Allocation Problem in IT Service Delivery Industry. - Prasad M. Deshpande; Dinesh Garg; Ramasuri Narayanam (IEEE SCC (1), 2008)

Mining Top Issues from Contact Center Logs for Self Help Portals. - Dinesh Garg; Nanda Kambhatla; Maja Vukovic; Gopal Pingali (IEEE SCC (2), 2008)

A Nash bargaining approach to retention enhancing bid optimization in sponsored search auctions with discrete bids. - Ramakrishnan Kannan; Dinesh Garg; Karthik Subbian; Yadati Narahari (CASE, 2008)

Mechanism Design for Single Leader Stackelberg Problems and Application to Procurement Auction Design. - Dinesh Garg; Y. Narahari (IEEE Trans Autom. Sci. Eng., 2008)

CAESAR: A Context-Aware, Social Recommender System for Low-End Mobile Devices. - Lakshmish Ramaswamy; P. Deepak 001; Ramana Polavarapu; Kutila Gunasekera; Dinesh Garg; Karthik Visweswariah; Shivkumar Kalyanaraman (Mobile Data Management, 2009)

Nash Bargaining Based Ad Networks for Sponsored Search Auctions. - Ramakrishnan Kannan; Dinesh Garg; Karthik Subbian; Y. Narahari (CEC, 2009)

An Optimal Mechanism for Sponsored Search Auctions on the Web and Comparison With Other Mechanisms. - Dinesh Garg; Y. Narahari (IEEE Trans Autom. Sci. Eng., 2009)

Game Theoretic Problems in Network Economics and Mechanism Design Solutions. - Y. Narahari; Dinesh Garg; Ramasuri Narayanam; V. Hastagiri Prakash (Springer, 2009)

A Game Theoretic Approach for Feature Clustering and Its Application to Feature Selection. - Dinesh Garg; Sundararajan Sellamanickam; Shirish K. Shevade (PAKDD (1), 2011)

Adaptive policies for selecting groupon style chunked reward ads in a stochastic knapsack framework. - Michael Grabchak; Narayan L. Bhamidipati; Rushi Bhatt; Dinesh Garg (WWW, 2011)

Threats and Trade-Offs in Resource Critical Crowdsourcing Tasks Over Networks. - Swaprava Nath; Pankaj Dayama 001; Dinesh Garg; Y. Narahari; James Y. Zou (AAAI, 2012)

Mechanism Design for Cost Optimal PAC Learning in the Presence of Strategic Noisy Annotators. - Dinesh Garg; Sourangshu Bhattacharya; S. Sundararajan; Shirish K. Shevade (UAI, 2012)

Mechanism Design for Time Critical and Cost Critical Task Execution via Crowdsourcing. - Swaprava Nath; Pankaj Dayama 001; Dinesh Garg; Yadati Narahari; James Y. Zou (WINE, 2012)

Learning to Propagate Rare Labels. - Rakesh Pimplikar; Dinesh Garg; Deepesh Bharani; Gyana R. Parija (CIKM, 2014)

Discovering signature of social networks with application to community detection. - Ramasuri Narayanam; Dinesh Garg; Hemank Lamba (COMSNETS, 2014)

Submodularity in Team Formation Problem. - Avradeep Bhowmik; Vivek S. Borkar; Dinesh Garg; Madhavan Pallan (SDM, 2014)

An Improved Block Coordinate Descent Method for Quadratic Programming in High Dimensions. - Gugan Thoppe; Vivek S. Borkar; Dinesh Garg (CoRR, 2014)

Truthful Interval Cover Mechanisms for Crowdsourcing Applications. - Pankaj Dayama 001; Balakrishnan Narayanaswamy; Dinesh Garg; Y. Narahari (AAMAS, 2015)

Edge conductance estimation using MCMC. - Ashish Bora; Vivek S. Borkar; Dinesh Garg; Rajesh Sundaresan (Allerton, 2016)

A Robust UCB scheme for active learning in regression from strategic crowds. - Divya Padmanabhan; Satyanath Bhat; Dinesh Garg; Shirish K. Shevade; Y. Narahari (IJCNN, 2016)

Fast rumor source identification via random walks. - Alankar Jain; Vivek S. Borkar; Dinesh Garg (Soc. Netw. Anal. Min., 2016)

Latent Space Embedding for Retrieval in Question-Answer Archives. - Deepak P 001; Dinesh Garg; Shirish K. Shevade (EMNLP, 2017)

Manipulating Gale-Shapley Algorithm: Preserving Stability and Remaining Inconspicuous. - Rohit Vaish; Dinesh Garg (IJCAI, 2017)

A Sparse Nonlinear Classifier Design Using AUC Optimization. - Vishal Kakkar; Shirish K. Shevade; S. Sundararajan; Dinesh Garg (SDM, 2017)

Deep Domain Adaptation under Deep Label Scarcity. - Amar Prakash Azad; Dinesh Garg; Priyanka Agrawal; Arun Kumar 002 (CoRR, 2018)

Quantum Embedding of Knowledge for Reasoning. - Dinesh Garg; Shajith Ikbal; Santosh K. Srivastava; Harit Vishwakarma; Hima P. Karanam; L. Venkata Subramaniam (NeurIPS, 2019)

Prediction of the disease controllability in a complex network using machine learning algorithms. - Richa Tripathi; Amit Reza; Dinesh Garg (CoRR, 2019)

Improved linear embeddings via Lagrange duality. - Kshiteej Sheth; Dinesh Garg; Anirban Dasgupta 001 (Mach. Learn., 2019)

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)

Span Selection Pre-training for Question Answering. - Michael R. Glass; Alfio Gliozzo; Rishav Chakravarti; Anthony Ferritto; Lin Pan 003; G. P. Shrivatsa Bhargav; Dinesh Garg; Avirup Sil (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)

Deep Domain Adaptation under Label Scarcity. - Amar Prakash Azad; Dinesh Garg; Priyanka Agrawal; Arun Kumar 002 (COMAD/CODS, 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)

First Workshop on Content Understanding and Generation for E-commerce. - Sumit Negi; Manisha Verma; Rajdeep H. Banerjee; Pooja A; Lydia B. Chilton; Mithun Das Gupta; Vinay P. Namboodiri; Dinesh Garg (KDD, 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)

Towards a Semantic Information Theory (Introducing Quantum Corollas). - Philip Tetlow; Dinesh Garg; Leigh Chase; Mark Mattingley-Scott; Nicholas Bronn; Kugendran Naidoo; Emil Reinert (CoRR, 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)

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)

Read between the lines - Functionality Extraction From READMEs. - Prince Kumar; Srikanth Tamilselvam; Dinesh Garg (NAACL-HLT (Findings), 2024)

An Approach to Build Zero-Shot Slot-Filling System for Industry-Grade Conversational Assistants. - 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; et al. (CoRR, 2024)

Transforming Code Understanding: Clustering-Based Retrieval for Improved Summarization in Domain-Specific Languages. - Baban Gain; Dibyanayan Bandyopadhyay; Samrat Mukherjee; Aryan Sahoo; Saswati Dana; Palanivel A. Kodeswaran; Sayandeep Sen; Asif Ekbal; Dinesh Garg (COLING (Industry), 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)