Artificial intelligence for mixed pixel resolution. - Nitish Gupta; V. K. Panchal (IGARSS, 2011)

DNA: An SDN framework for Distributed Network Analytics (Demo Paper). - Alexander Clemm; Mouli Chandramouli; Nitish Gupta; Robert Lerche; Ashwin Pankaj; Manjunath Patil; Ganesan Rajam; V. Anbalagan; Joe Zhang; Yifan Zhang (IM, 2015)

Collectively Embedding Multi-Relational Data for Predicting User Preferences. - Nitish Gupta; Sameer Singh 001 (CoRR, 2015)

Revisiting the Evaluation for Cross Document Event Coreference. - Shyam Upadhyay; Nitish Gupta; Christos Christodoulopoulos 001; Dan Roth 001 (COLING, 2016)

RapMap: a rapid, sensitive and accurate tool for mapping RNA-seq reads to transcriptomes. - Avi Srivastava; Hirak Sarkar; Nitish Gupta; Rob Patro (Bioinform., 2016)

Efficient Index Maintenance Under Dynamic Genome Modification. - Nitish Gupta; Komal Sanjeev; Tim Wall; Carl Kingsford; Rob Patro (CoRR, 2016)

Entity Linking via Joint Encoding of Types, Descriptions, and Context. - Nitish Gupta; Sameer Singh 001; Dan Roth 001 (EMNLP, 2017)

UI CCG TAC-KBP2017 Submissions: Entity Discovery and Linking, and Event Nugget Detection and Co-reference. - Chase Duncan; Liang-Wei Chan; Haoruo Peng; Hao Wu 034; Shyam Upadhyay; Nitish Gupta; Chen-Tse Tsai; Mark Sammons; Dan Roth 001 (TAC, 2017)

Neural Compositional Denotational Semantics for Question Answering. - Nitish Gupta; Mike Lewis (EMNLP, 2018)

Joint Multilingual Supervision for Cross-lingual Entity Linking. - Shyam Upadhyay; Nitish Gupta; Dan Roth 001 (EMNLP, 2018)

Real-Time Hardware-In-the-Loop Emulation Framework for DSRC-Based Connected Vehicle Applications. - Ghayoor Shah; Rodolfo Valiente; Nitish Gupta; S. M. Osman Gani; Behrad Toghi; Yaser P. Fallah; Somak Datta Gupta (CAVS, 2019)

Robust Named Entity Recognition with Truecasing Pretraining. - Stephen Mayhew 001; Nitish Gupta; Dan Roth 001 (AAAI, 2020)

Overestimation of Syntactic Representation in Neural Language Models. - Jordan Kodner; Nitish Gupta (ACL, 2020)

Obtaining Faithful Interpretations from Compositional Neural Networks. - Sanjay Subramanian; Ben Bogin; Nitish Gupta; Tomer Wolfson; Sameer Singh 001; Jonathan Berant; Matt Gardner 001 (ACL, 2020)

Evaluating Models' Local Decision Boundaries via Contrast Sets. - Matt Gardner 001; Yoav Artzi; Victoria Basmova; Jonathan Berant; Ben Bogin; Sihao Chen; Pradeep Dasigi; Dheeru Dua; Yanai Elazar; Ananth Gottumukkala; Nitish Gupta; Hannaneh Hajishirzi; et al. (EMNLP (Findings), 2020)

Improving Compositional Generalization in Semantic Parsing. - Inbar Oren; Jonathan Herzig; Nitish Gupta; Matt Gardner 001; Jonathan Berant (EMNLP (Findings), 2020)

What do we expect from Multiple-choice QA Systems? - Krunal Shah; Nitish Gupta; Dan Roth 001 (EMNLP (Findings), 2020)

Neural Module Networks for Reasoning over Text. - Nitish Gupta; Kevin Lin; Dan Roth 001; Sameer Singh 001; Matt Gardner 001 (ICLR, 2020)

Azure SQL Database Always Encrypted. - Panagiotis Antonopoulos; Arvind Arasu; Kunal D. Singh; Ken Eguro; Nitish Gupta; Rajat Jain; Raghav Kaushik; Hanuma Kodavalla; Donald Kossmann; Nikolas Ogg; Ravi Ramamurthy; Jakub Szymaszek; et al. (SIGMOD Conference, 2020)

Evaluating NLP Models via Contrast Sets. - Matt Gardner 001; Yoav Artzi; Victoria Basmova; Jonathan Berant; Ben Bogin; Sihao Chen; Pradeep Dasigi; Dheeru Dua; Yanai Elazar; Ananth Gottumukkala; Nitish Gupta; Hanna Hajishirzi; et al. (CoRR, 2020)

Overestimation of Syntactic Representationin Neural Language Models. - Jordan Kodner; Nitish Gupta (CoRR, 2020)

Enforcing Consistency in Weakly Supervised Semantic Parsing. - Nitish Gupta; Sameer Singh 001; Matt Gardner 001 (ACL/IJCNLP (2), 2021)

Paired Examples as Indirect Supervision in Latent Decision Models. - Nitish Gupta; Sameer Singh 001; Matt Gardner 001; Dan Roth 001 (EMNLP (1), 2021)

Adversarial Generation of Temporal Data: A Critique on Fidelity of Synthetic Data. - Ankur Debnath; Nitish Gupta; Govind Waghmare; Hardik Wadhwa; Siddhartha Asthana; Ankur Arora (PKDD/ECML Workshops (1), 2021)

Real-time SIL Emulation Architecture for Cooperative Automated Vehicles. - Nitish Gupta (CoRR, 2021)

Bootstrapping Multilingual Semantic Parsers using Large Language Models. - Abhijeet Awasthi; Nitish Gupta; Bidisha Samanta; Shachi Dave; Sunita Sarawagi; Partha P. Talukdar (CoRR, 2022)

Optimizing Real-Time Performances for Timed-Loop Racing under F1TENTH. - Nitish Gupta; Kurt M. Wilson; Zhishan Guo (CoRR, 2022)

QA Is the New KR: Question-Answer Pairs as Knowledge Bases. - William W. Cohen; Wenhu Chen; Michiel de Jong; Nitish Gupta; Alessandro Presta; Pat Verga; John Wieting (AAAI, 2023)

Bootstrapping Multilingual Semantic Parsers using Large Language Models. - Abhijeet Awasthi; Nitish Gupta; Bidisha Samanta; Shachi Dave; Sunita Sarawagi; Partha Talukdar (EACL, 2023)

Event Linking: Grounding Event Mentions to Wikipedia. - Xiaodong Yu 003; Wenpeng Yin 001; Nitish Gupta; Dan Roth 001 (EACL, 2023)

XTREME-UP: A User-Centric Scarce-Data Benchmark for Under-Represented Languages. - Sebastian Ruder; Jonathan H. Clark; Alexander Gutkin; Mihir Kale; Min Ma; Massimo Nicosia; Shruti Rijhwani; Parker Riley; Jean Michel A. Sarr; Xinyi Wang 001; John Wieting; Nitish Gupta; et al. (EMNLP (Findings), 2023)

Microsoft Purview: A System for Central Governance of Data. - Shafi Ahmad; Dillidorai Arumugam; Srdan Bozovic; Elnata Degefa; Sailesh Duvvuri; Steven Gott; Nitish Gupta; Joachim Hammer; Nivedita Kaluskar; Raghav Kaushik; Rakesh Khanduja; Prasad Mujumdar; et al. (Proc. VLDB Endow., 2023)

IndicGenBench: A Multilingual Benchmark to Evaluate Generation Capabilities of LLMs on Indic Languages. - Harman Singh; Nitish Gupta; Shikhar Bharadwaj; Dinesh Tewari; Partha Talukdar (ACL (1), 2024)

Potential-Based Reward Shaping for Intrinsic Motivation. - Grant C. Forbes; Nitish Gupta; Leonardo Villalobos-Arias; Colin M. Potts; Arnav Jhala; David L. Roberts 001 (AAMAS, 2024)

LLM Augmented LLMs: Expanding Capabilities through Composition. - Rachit Bansal; Bidisha Samanta; Siddharth Dalmia; Nitish Gupta; Sriram Ganapathy; Abhishek Bapna; Prateek Jain; Partha Talukdar (ICLR, 2024)

Protecting Your Online Persona: A Preferential Selective Encryption Approach for Enhanced Privacy in Tweets, Images, Memes, and Metadata. - Nisha P. Shetty; Balachandra Muniyal; Aman Priyanshu; Dhruthi Kumar; Leander Melroy Maben; Yash Agrawal; Ruchita Natarajan; Shravya Gunda; Nitish Gupta (IEEE Access, 2024)

LLM Augmented LLMs: Expanding Capabilities through Composition. - Rachit Bansal; Bidisha Samanta; Siddharth Dalmia; Nitish Gupta; Shikhar Vashishth; Sriram Ganapathy; Abhishek Bapna; Prateek Jain; Partha Talukdar (CoRR, 2024)

Mufu: Multilingual Fused Learning for Low-Resource Translation with LLM. - Zheng Wei Lim; Nitish Gupta; Honglin Yu; Trevor Cohn (ICLR, 2025)