Equality and hashing for (almost) free: Generating implementations from abstraction functions. - Derek Rayside; Zev Benjamin; Rishabh Singh; Joseph P. Near; Aleksandar Milicevic; Daniel Jackson 001 (ICSE, 2009)

Subsumer-First: Steering Symbolic Reachability Analysis. - Andrey Rybalchenko; Rishabh Singh (SPIN, 2009)

Learning Component Interfaces with May and Must Abstractions. - Rishabh Singh; Dimitra Giannakopoulou; Corina S. Pasareanu (CAV, 2010)

Synthesizing data structure manipulations from storyboards. - Rishabh Singh; Armando Solar-Lezama (SIGSOFT FSE, 2011)

Synthesizing Number Transformations from Input-Output Examples. - Rishabh Singh; Sumit Gulwani (CAV, 2012)

SPT: Storyboard Programming Tool. - Rishabh Singh; Armando Solar-Lezama (CAV, 2012)

Spreadsheet data manipulation using examples. - Sumit Gulwani; William R. Harris; Rishabh Singh (Commun. ACM, 2012)

Automated Semantic Grading of Programs - Rishabh Singh; Sumit Gulwani; Armando Solar-Lezama (CoRR, 2012)

Learning Semantic String Transformations from Examples. - Rishabh Singh; Sumit Gulwani (Proc. VLDB Endow., 2012)

Syntax-guided synthesis. - Rajeev Alur; Rastislav Bodík; Garvit Juniwal; Milo M. K. Martin; Mukund Raghothaman; Sanjit A. Seshia; Rishabh Singh; Armando Solar-Lezama; Emina Torlak; Abhishek Udupa (FMCAD, 2013)

Automated feedback generation for introductory programming assignments. - Rishabh Singh; Sumit Gulwani; Armando Solar-Lezama (PLDI, 2013)

Feature engineering for clustering student solutions. - Elena L. Glassman; Rishabh Singh; Robert C. Miller (L@S, 2014)

Modular Synthesis of Sketches Using Models. - Rohit Singh 002; Rishabh Singh; Zhilei Xu; Rebecca Krosnick; Armando Solar-Lezama (VMCAI, 2014)

Accessible programming using program synthesis. - Rishabh Singh (2014)

Predicting a Correct Program in Programming by Example. - Rishabh Singh; Sumit Gulwani (CAV (1), 2015)

User Interaction Models for Disambiguation in Programming by Example. - Mikaël Mayer; Gustavo Soares; Maxim Grechkin; Vu Le 002; Mark Marron; Oleksandr Polozov; Rishabh Singh; Benjamin G. Zorn; Sumit Gulwani (UIST, 2015)

Results and Analysis of SyGuS-Comp'15. - Rajeev Alur; Dana Fisman; Rishabh Singh; Armando Solar-Lezama (SYNT, 2015)

OverCode: Visualizing Variation in Student Solutions to Programming Problems at Scale. - Elena L. Glassman; Jeremy Scott; Rishabh Singh; Philip J. Guo; Robert C. Miller (ACM Trans. Comput. Hum. Interact., 2015)

Syntax-Guided Synthesis. - Rajeev Alur; Rastislav Bodík; Eric Dallal; Dana Fisman; Pranav Garg 001; Garvit Juniwal; Hadas Kress-Gazit; P. Madhusudan; Milo M. K. Martin; Mukund Raghothaman; Shambwaditya Saha; Sanjit A. Seshia; et al. (Dependable Software Systems Engineering, 2015)

Qlose: Program Repair with Quantitative Objectives. - Loris D'Antoni; Roopsha Samanta; Rishabh Singh (CAV (2), 2016)

Understanding Conversational Programmers: A Perspective from the Software Industry. - Parmit K. Chilana; Rishabh Singh; Philip J. Guo (CHI, 2016)

FIDEX: filtering spreadsheet data using examples. - Xinyu Wang 006; Sumit Gulwani; Rishabh Singh (OOPSLA, 2016)

Transforming spreadsheet data types using examples. - Rishabh Singh; Sumit Gulwani (POPL, 2016)

SyncWorld: A cloud storage/synchronization service using Java and Php. - Rishabh Singh; Aman Abidi; Mohammed Abdul Qadeer (WOCN, 2016)

SyGuS-Comp 2016: Results and Analysis. - Rajeev Alur; Dana Fisman; Rishabh Singh; Armando Solar-Lezama (SYNT@CAV, 2016)

Automated Correction for Syntax Errors in Programming Assignments using Recurrent Neural Networks. - Sahil Bhatia; Rishabh Singh (CoRR, 2016)

TerpreT: A Probabilistic Programming Language for Program Induction. - Alexander L. Gaunt; Marc Brockschmidt; Rishabh Singh; Nate Kushman; Pushmeet Kohli; Jonathan Taylor 001; Daniel Tarlow (CoRR, 2016)

Summary - TerpreT: A Probabilistic Programming Language for Program Induction. - Alexander L. Gaunt; Marc Brockschmidt; Rishabh Singh; Nate Kushman; Pushmeet Kohli; Jonathan Taylor 001; Daniel Tarlow (CoRR, 2016)

BlinkFill: Semi-supervised Programming By Example for Syntactic String Transformations. - Rishabh Singh (Proc. VLDB Endow., 2016)

A Vector Quantization Based Feature Descriptor for Online Signature Verification. - Vivek Venugopal; Abhishek Sharma 006; Rishabh Singh; Abhinav Sharma; Suresh Sundaram 001 (ICDAR, 2017)

Neuro-Symbolic Program Synthesis. - Emilio Parisotto; Abdel-rahman Mohamed; Rishabh Singh; Lihong Li 001; Dengyong Zhou; Pushmeet Kohli (ICLR (Poster), 2017)

RobustFill: Neural Program Learning under Noisy I/O. - Jacob Devlin; Jonathan Uesato; Surya Bhupatiraju; Rishabh Singh; Abdel-rahman Mohamed; Pushmeet Kohli (ICML, 2017)

Learn&Fuzz: machine learning for input fuzzing. - Patrice Godefroid; Hila Peleg; Rishabh Singh (ASE, 2017)

Data-Driven Feedback Generator for Online Programing Courses. - Ke Wang 022; Benjamin Lin; Bjorn Rettig; Paul Pardi; Rishabh Singh (L@S, 2017)

Neural Program Meta-Induction. - Jacob Devlin; Rudy Bunel; Rishabh Singh; Matthew J. Hausknecht; Pushmeet Kohli (NIPS, 2017)

NoFAQ: synthesizing command repairs from examples. - Loris D'Antoni; Rishabh Singh; Michael Vaughn (ESEC/SIGSOFT FSE, 2017)

AP: Artificial Programming. - Rishabh Singh; Pushmeet Kohli (SNAPL, 2017)

Deep API Programmer: Learning to Program with APIs. - Surya Bhupatiraju; Rishabh Singh; Abdel-rahman Mohamed; Pushmeet Kohli (CoRR, 2017)

Semantic Code Repair using Neuro-Symbolic Transformation Networks. - Jacob Devlin; Jonathan Uesato; Rishabh Singh; Pushmeet Kohli (CoRR, 2017)

Not all bytes are equal: Neural byte sieve for fuzzing. - Mohit Rajpal; William Blum; Rishabh Singh (CoRR, 2017)

Data-Driven Feedback Generation for Introductory Programming Exercises. - Ke Wang 022; Rishabh Singh; Zhendong Su 001 (CoRR, 2017)

Dynamic Neural Program Embedding for Program Repair. - Ke Wang 022; Rishabh Singh; Zhendong Su 001 (CoRR, 2017)

SyGuS-Comp 2017: Results and Analysis. - Rajeev Alur; Dana Fisman; Rishabh Singh; Armando Solar-Lezama (SYNT@CAV, 2017)

Approaches and Applications of Inductive Programming (Dagstuhl Seminar 17382). - Ute Schmid; Stephen H. Muggleton; Rishabh Singh (Dagstuhl Reports, 2017)

Program Synthesis. - Sumit Gulwani; Oleksandr Polozov; Rishabh Singh (Found. Trends Program. Lang., 2017)

Synthesis of data completion scripts using finite tree automata. - Xinyu Wang 006; Isil Dillig; Rishabh Singh (Proc. ACM Program. Lang., 2017)

gAR-age: A Feedback-Enabled Blended Ecosystem for Vehicle Health Monitoring. - Sitara Shah; Snigdha Petluru; Rishabh Singh; Saurabh Srivastava (AutomotiveUI, 2018)

Nearest-Instance-Centroid-Estimation Linear Discriminant Analysis (Nice Lda). - Rishabh Singh; Kan Li 002; José C. Príncipe (ICASSP, 2018)

Leveraging Grammar and Reinforcement Learning for Neural Program Synthesis. - Rudy Bunel; Matthew J. Hausknecht; Jacob Devlin; Rishabh Singh; Pushmeet Kohli (ICLR (Poster), 2018)

Learning and Analyzing Vector Encoding of Symbolic Representation. - Roland Fernandez; Asli Celikyilmaz; Paul Smolensky; Rishabh Singh (ICLR (Workshop), 2018)

Dynamic Neural Program Embeddings for Program Repair. - Ke Wang 022; Rishabh Singh; Zhendong Su 001 (ICLR (Poster), 2018)

Programmatically Interpretable Reinforcement Learning. - Abhinav Verma 001; Vijayaraghavan Murali; Rishabh Singh; Pushmeet Kohli; Swarat Chaudhuri (ICML, 2018)

Neuro-symbolic program corrector for introductory programming assignments. - Sahil Bhatia; Pushmeet Kohli; Rishabh Singh (ICSE, 2018)

Correntropy Based Hierarchical Linear Dynamical System For Speech Recognition. - Rishabh Singh; José C. Príncipe (IJCNN, 2018)

Natural Language to Structured Query Generation via Meta-Learning. - Po-Sen Huang; Chenglong Wang; Rishabh Singh; Wen-tau Yih; Xiaodong He 001 (NAACL-HLT (2), 2018)

Interpreting Neural Network Judgments via Minimal, Stable, and Symbolic Corrections. - Xin Zhang 035; Armando Solar-Lezama; Rishabh Singh (NeurIPS, 2018)

Search, align, and repair: data-driven feedback generation for introductory programming exercises. - Ke Wang 022; Rishabh Singh; Zhendong Su 001 (PLDI, 2018)

Deep Reinforcement Fuzzing. - Konstantin Böttinger; Patrice Godefroid; Rishabh Singh (IEEE Symposium on Security and Privacy Workshops, 2018)

Search-based program synthesis. - Rajeev Alur; Rishabh Singh; Dana Fisman; Armando Solar-Lezama (Commun. ACM, 2018)

Learning and analyzing vector encoding of symbolic representations. - Roland Fernandez; Asli Celikyilmaz; Rishabh Singh; Paul Smolensky (CoRR, 2018)

Program Repair via Direct State Manipulation. - Qinheping Hu; Isaac Evavold; Roopsha Samanta; Rishabh Singh; Loris D'Antoni (CoRR, 2018)

Towards Mixed Optimization for Reinforcement Learning with Program Synthesis. - Surya Bhupatiraju; Kumar Krishna Agrawal; Rishabh Singh (CoRR, 2018)

Execution-Guided Neural Program Decoding. - Chenglong Wang; Po-Sen Huang; Alex Polozov; Marc Brockschmidt; Rishabh Singh (CoRR, 2018)

WebRelate: integrating web data with spreadsheets using examples. - Jeevana Priya Inala; Rishabh Singh (Proc. ACM Program. Lang., 2018)

Program synthesis using abstraction refinement. - Xinyu Wang 006; Isil Dillig; Rishabh Singh (Proc. ACM Program. Lang., 2018)

VPDS: An AI-Based Automated Vehicle Occupancy and Violation Detection System. - Abhinav Kumar 004; Aishwarya Gupta 001; Bishal Santra; K. S. Lalitha; Manasa Kolla; Mayank Gupta 002; Rishabh Singh (AAAI, 2019)

Synthetic Datasets for Neural Program Synthesis. - Richard Shin; Neel Kant; Kavi Gupta; Chris Bender; Brandon Trabucco; Rishabh Singh; Dawn Song (ICLR (Poster), 2019)

Neural Program Repair by Jointly Learning to Localize and Repair. - Marko Vasic; Aditya Kanade 001; Petros Maniatis; David Bieber; Rishabh Singh (ICLR (Poster), 2019)

Learning Transferable Graph Exploration. - Hanjun Dai; Yujia Li 001; Chenglong Wang; Rishabh Singh; Po-Sen Huang; Pushmeet Kohli (NeurIPS, 2019)

Direct Manipulation for Imperative Programs. - Qinheping Hu; Roopsha Samanta; Rishabh Singh; Loris D'Antoni (SAS, 2019)

Neural-Guided Symbolic Regression with Semantic Prior. - Li Li 060; Minjie Fan; Rishabh Singh; Patrick Riley 001 (CoRR, 2019)

SyGuS-Comp 2018: Results and Analysis. - Rajeev Alur; Dana Fisman; Saswat Padhi; Rishabh Singh; Abhishek Udupa (CoRR, 2019)

MoËT: Interpretable and Verifiable Reinforcement Learning via Mixture of Expert Trees. - Marko Vasic; Andrija Petrovic; Kaiyuan Wang; Mladen Nikolic; Rishabh Singh; Sarfraz Khurshid (CoRR, 2019)

Solving Program Sketches with Large Integer Values. - Rong Pan; Qinheping Hu; Rishabh Singh; Loris D'Antoni (ESOP, 2020)

Composite Dynamic Texture Synthesis Using Hierarchical Linear Dynamical System. - Rishabh Singh; Shujian Yu; José C. Príncipe (ICASSP, 2020)

Global Relational Models of Source Code. - Vincent J. Hellendoorn; Charles Sutton; Rishabh Singh; Petros Maniatis; David Bieber (ICLR, 2020)

Generating Programmatic Referring Expressions via Program Synthesis. - Jiani Huang; Calvin Smith; Osbert Bastani; Rishabh Singh; Aws Albarghouthi; Mayur Naik (ICML, 2020)

Cyberbullying and Indian Society: Outcomes from Social Conclave Conference. - Rishabh Reddy; Rishabh Singh; Vidhi Kapoor; Prathamesh P. Churi (ISTAS, 2020)

Learning Discrete Energy-based Models via Auxiliary-variable Local Exploration. - Hanjun Dai; Rishabh Singh; Bo Dai 001; Charles Sutton; Dale Schuurmans (NeurIPS, 2020)

Time Series Analysis using a Kernel based Multi-Modal Uncertainty Decomposition Framework. - Rishabh Singh; José C. Príncipe (UAI, 2020)

Artificial Intelligence and Machine Learning Empower Advanced Biomedical Material Design to Toxicity Prediction. - Ajay Vikram Singh; Daniel Rosenkranz; Mohammad Hasan Dad Ansari; Rishabh Singh; Anurag Kanase; Shubham Pratap Singh; Blair Johnston; Jutta Tentschert; Peter Laux; Andreas Luch (Adv. Intell. Syst., 2020)

Towards a Kernel based Physical Interpretation of Model Uncertainty. - Rishabh Singh; José C. Príncipe (CoRR, 2020)

Towards Modular Algorithm Induction. - Daniel A. Abolafia; Rishabh Singh; Manzil Zaheer; Charles Sutton (CoRR, 2020)

Neural Program Synthesis with a Differentiable Fixer. - Matej Balog; Rishabh Singh; Petros Maniatis; Charles Sutton (CoRR, 2020)

BUSTLE: Bottom-up program-Synthesis Through Learning-guided Exploration. - Augustus Odena; Kensen Shi; David Bieber; Rishabh Singh; Charles Sutton (CoRR, 2020)

Deep Learning & Software Engineering: State of Research and Future Directions. - Prem Devanbu; Matthew B. Dwyer; Sebastian G. Elbaum; Michael Lowry; Kevin Moran; Denys Poshyvanyk; Baishakhi Ray; Rishabh Singh; Xiangyu Zhang 001 (CoRR, 2020)

Joy of Learning Through Internet Memes. - Rishabh Reddy; Rishabh Singh; Vidhi Kapoor; Prathamesh P. Churi (Int. J. Eng. Pedagog., 2020)

Augmented example-based synthesis using relational perturbation properties. - Shengwei An; Rishabh Singh; Sasa Misailovic; Roopsha Samanta (Proc. ACM Program. Lang., 2020)

Bias: Bijective Input And Surjectivity In Zero Shot Learning. - Rishabh Singh (ICIP, 2021)

BUSTLE: Bottom-Up Program Synthesis Through Learning-Guided Exploration. - Augustus Odena; Kensen Shi; David Bieber; Rishabh Singh; Charles Sutton; Hanjun Dai (ICLR, 2021)

Scaling Symbolic Methods using Gradients for Neural Model Explanation. - Subham Sekhar Sahoo; Subhashini Venugopalan; Li Li 060; Rishabh Singh; Patrick Riley 001 (ICLR, 2021)

SpreadsheetCoder: Formula Prediction from Semi-structured Context. - Xinyun Chen; Petros Maniatis; Rishabh Singh; Charles Sutton; Hanjun Dai; Max Lin; Denny Zhou (ICML, 2021)

Latent Programmer: Discrete Latent Codes for Program Synthesis. - Joey Hong; David Dohan; Rishabh Singh; Charles Sutton; Manzil Zaheer (ICML, 2021)

DAWSSM: A plug-and-play Drone Assisted Water Sampling and Sensing Module. - Digvijay Singh; Rishabh Singh; Rahul Ajmeria; Manik Gupta; R. N. Ponnalagu (IECON, 2021)

Learning Semantic Representations to Verify Hardware Designs. - Shobha Vasudevan; Wenjie Jiang 001; David Bieber; Rishabh Singh; Hamid Shojaei; Richard Ho 001; Charles Sutton (NeurIPS, 2021)

A Kernel Framework to Quantify a Model's Local Predictive Uncertainty under Data Distributional Shifts. - Rishabh Singh; José C. Príncipe (CoRR, 2021)

Image to Image Translation : Generating maps from satellite images. - Vaishali V. Ingale; Rishabh Singh; Pragati Patwal (CoRR, 2021)

Deep Geospatial Interpolation Networks. - Sumit Kumar Varshney; Jeetu Kumar; Aditya Tiwari; Rishabh Singh; Venkata M. V. Gunturi; Narayanan C. Krishnan (CoRR, 2021)

Quantifying Model Predictive Uncertainty with Perturbation Theory. - Rishabh Singh; José C. Príncipe (CoRR, 2021)

Question paper generation through progressive model and difficulty calculation on the Promexa Mobile Application. - Rishabh Singh; Devansh Timbadia; Vidhi Kapoor; Rishabh Reddy; Prathamesh P. Churi; Omkar Pimple (Educ. Inf. Technol., 2021)

Special Issue on Syntax-Guided Synthesis Preface. - Dana Fisman; Rishabh Singh; Armando Solar-Lezama (Formal Methods Syst. Des., 2021)

Neurosymbolic Programming. - Swarat Chaudhuri; Kevin Ellis; Oleksandr Polozov; Rishabh Singh; Armando Solar-Lezama; Yisong Yue (Found. Trends Program. Lang., 2021)

Toward a Kernel-Based Uncertainty Decomposition Framework for Data and Models. - Rishabh Singh; José C. Príncipe (Neural Comput., 2021)

Platt-Bin: Efficient Posterior Calibrated Training for NLP Classifiers. - Rishabh Singh; Shirin Goshtasbpour (ACL (Findings), 2022)

ECG Fiducial Point Localization Using a Deep Learning Model. - Murtadha D. Hssayeni; Arash Andalib; Rishabh Singh; Diego Pava; Kan Li; Steven Borzak; Robert Chait; Kaustubh Kale (ICMLA, 2022)

Quantifying Model Uncertainty for Semantic Segmentation using Operators in the RKHS. - Rishabh Singh; José C. Príncipe (CoRR, 2022)

Robust Dependence Measure using RKHS based Uncertainty Moments and Optimal Transport. - Rishabh Singh; José C. Príncipe (CoRR, 2022)

Prediction of Stress Level on Indian Working Professionals Using Machine Learning. - Kavita Pabreja; Anubhuti Singh; Rishabh Singh; Rishita Agnihotri; Shriam Kaushik; Tanvi Malhotra (Int. J. Hum. Cap. Inf. Technol. Prof., 2022)

MoËT: Mixture of Expert Trees and its application to verifiable reinforcement learning. - Marko Vasic; Andrija Petrovic; Kaiyuan Wang; Mladen Nikolic; Rishabh Singh; Sarfraz Khurshid (Neural Networks, 2022)

Solving Program Sketches with Large Integer Values. - Qinheping Hu; Rishabh Singh; Loris D'Antoni (ACM Trans. Program. Lang. Syst., 2022)

TF-Coder: Program Synthesis for Tensor Manipulations. - Kensen Shi; David Bieber; Rishabh Singh (ACM Trans. Program. Lang. Syst., 2022)

Measuring the Impact of Programming Language Distribution. - Gabriel Orlanski; Kefan Xiao; Xavier Garcia; Jeffrey Hui; Joshua Howland; Jonathan Malmaud; Jacob Austin; Rishabh Singh; Michele Catasta (ICML, 2023)

Finding Local Dependent Regions in PDFs using RKHS Uncertainty Moments and Optimal Transport. - Rishabh Singh; Yaxin Ma; José C. Príncipe (IJCNN, 2024)

EdgeFlowNet: 100FPS@1W Dense Optical Flow for Tiny Mobile Robots. - Sai Ramana Kiran Pinnama Raju; Rishabh Singh; Manoj Velmurugan; Nitin J. Sanket (IEEE Robotics Autom. Lett., 2025)

SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution. - Yuxiang Wei 003; Olivier Duchenne; Jade Copet; Quentin Carbonneaux; Lingming Zhang 001; Daniel Fried; Gabriel Synnaeve; Rishabh Singh; Sida I. Wang (CoRR, 2025)