Mayur Naik - Publications
Mayur Naik
Students
Ph.D. Advisees
Undergrad Researchers
Publications
Monographs
Preprints
Peer-Reviewed Papers
Invited Articles
Alumni
Graduated Ph.D. Students
Graduated Postdocs
Sponsors
Monographs
Neurosymbolic Programming in Scallop: Principles and Practice
Ziyang Li, Jiani Huang, Jason Liu, Mayur Naik.
Foundations and Trends in Programming Languages.
NOW Publishers, 2024.
Preprints
Detecting Safety Violations Across Many Agent Traces
Adam Stein, Davis Brown, Hamed Hassani, Mayur Naik, Eric Wong.
April 2026.
Do We Need Frontier Models to Verify Mathematical Proofs?
Aaditya Naik, Guruprerana Shabadi, Rajeev Alur, Mayur Naik.
April 2026.
An ECG Language Model for Forecasting Cardiac Events
Neelay Velingker, Alaia Solko-Breslin, Mayank Keoliya, Seewon Choi, Jiayi Xin, Anika Marathe, Alireza Oraii, Rajat Deo, Sameed Khatana, Rajeev Alur, Mayur Naik, Eric Wong.
February 2026.
Delta Activations: A Representation for Finetuned Large Language Models
Zhiqiu Xu, Amish Sethi, Mayur Naik, Ser-Nam Lim.
September 2025.
The Road to Generalizable Neuro-Symbolic Learning Should be Paved with Foundation Models
Adam Stein, Aaditya Naik, Neelay Velingker, Mayur Naik, Eric Wong.
May 2025.
Peer-Reviewed Papers
QLCoder: A Query Synthesizer For Static Analysis of Security Vulnerabilities
Claire Wang, Ziyang Li, Saikat Dutta, Mayur Naik.
ICLR 2026.
Lobster: A GPU-Accelerated Framework for Neurosymbolic Programming
Paul Biberstein, Ziyang Li, Joseph Devietti, Mayur Naik.
ASPLOS 2026.
ESCA: Contextualizing Embodied Agents via Scene-Graph Generation
Jiani Huang, Amish Sethi*, Matthew Kuo*, Mayank Keoliya, Neelay Velingker, JungHo Jung, Ser-Nam Lim, Ziyang Li, Mayur Naik.
NeurIPS 2025.
Spotlight Paper
Once Upon an Input: Reasoning via Per-Instance Program Synthesis
Adam Stein*, Neelay Velingker*, Mayur Naik, Eric Wong.
NeurIPS 2025.
Dolphin: A Programmable Framework for Scalable Neurosymbolic Learning
Aaditya Naik, Jason Liu, Claire Wang, Amish Sethi, Saikat Dutta, Mayur Naik, Eric Wong.
ICML 2025.
IRIS: LLM-Assisted Static Analysis for Detecting Security Vulnerabilities
Ziyang Li, Saikat Dutta, Mayur Naik.
ICLR 2025.
LASER: A Neuro-Symbolic Framework for Learning Spatial-Temporal Scene Graphs with Weak Supervision
Jiani Huang, Ziyang Li, Mayur Naik, Ser-Nam Lim.
ICLR 2025.
Understanding the Effectiveness of Large Language Models in Detecting Security Vulnerabilities
Avishree Khare*, Saikat Dutta*, Ziyang Li, Alaia Solko-Breslin, Rajeev Alur, Mayur Naik.
ICST 2025.
Data-Efficient Learning with Neural Programs
Alaia Solko-Breslin, Seewon Choi, Ziyang Li, Neelay Velingker, Rajeev Alur, Mayur Naik, Eric Wong.
NeurIPS 2024.
Crowd-sourced machine learning prediction of Long COVID using data from the National COVID Cohort Collaborative
Timothy Bergquist et al..
eBioMedicine 2024.
NIH L3C Honorable Mention Award
TYGR: Type Inference on Stripped Binaries using Graph Neural Networks
Ziyang Li*, Chang Zhu*, Anton Xue, Ati Priya Bajaj, William Gibbs, Yibo Liu, Rajeev Alur, Tiffany Bao, Hanjun Dai, Adam Doupé, Mayur Naik, Yan Shoshitaishvili, Ruoyu Wang, Aravind Machiry.
USENIX Security 2024.
Towards Compositionality in Concept Learning
Adam Stein, Aaditya Naik, Yinjun Wu, Mayur Naik, Eric Wong.
ICML 2024.
DISCRET: Synthesizing Faithful Explanations For Treatment Effect Estimation
Yinjun Wu*, Mayank Keoliya*, Kan Chen, Neelay Velingker, Ziyang Li, Emily Getzen, Qi Long, Mayur Naik, Ravi Parikh, Eric Wong.
ICML 2024.
Spotlight Paper
TorchQL: A Programming Framework for Integrity Constraints in Machine Learning
Aaditya Naik, Adam Stein, Yinjun Wu, Mayur Naik, Eric Wong.
OOPSLA 2024.
Relational Programming with Foundation Models
Ziyang Li, Jiani Huang, Jason Liu, Felix Zhu, Eric Zhao, William Dodds, Neelay Velingker, Rajeev Alur, Mayur Naik.
AAAI 2024.
Relational Query Synthesis ⋈ Decision Tree Learning
Aaditya Naik, Aalok Thakkar, Adam Stein, Rajeev Alur, Mayur Naik.
VLDB 2024.
Mobius: Synthesizing Relational Queries with Recursive and Invented Predicates
Aalok Thakkar, Nathaniel Sands, George Petrou, Rajeev Alur, Mayur Naik, Mukund Raghothaman.
OOPSLA 2023.
Improved Logical Reasoning of Language Models via Differentiable Symbolic Programming
Hanlin Zhang*, Jiani Huang*, Ziyang Li, Mayur Naik, Eric Xing.
Findings of ACL 2023.
Do Machine Learning Models Learn Statistical Rules Inferred from Data?
Aaditya Naik, Yinjun Wu, Mayur Naik, Eric Wong.
ICML 2023.
Scallop: A Language for Neurosymbolic Programming
Ziyang Li*, Jiani Huang*, Mayur Naik.
PLDI 2023.
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Learning to Select Pivotal Samples for Meta Re-weighting
Yinjun Wu, Adam Stein, Jacob Gardner, Mayur Naik.
AAAI 2023.
Oral Presentation
Synthesizing Formal Network Specifications from Input-Output Examples
Haoxian Chen, Chenyuan Wu, Andrew Zhao, Mukund Raghothaman, Mayur Naik, Boon Thau Loo.
IEEE/ACM ToN 2022.
DeepMerge: Learning to Merge Programs
Elizabeth Dinella, Todd Mytkowicz, Alexey Svyatkovskiy, Christian Bird, Mayur Naik, Shuvendu Lahiri.
IEEE TSE 2022 and FSE 2022 (Journal-First Track).
CodeTrek: Flexible Modeling of Code using an Extensible Relational Representation
Pardis Pashakhanloo, Aaditya Naik, Yuepeng Wang, Hanjun Dai, Petros Maniatis, Mayur Naik.
ICLR 2022.
PacJam: Securing Dependencies Continuously via Package-Oriented Debloating
Pardis Pashakhanloo, Aravind Machiry, Hyonyoung Choi, Anthony Canino, Kihong Heo, Insup Lee, Mayur Naik.
Asia CCS 2022.
Scallop: From Probabilistic Deductive Databases to Scalable Differentiable Reasoning
Jiani Huang*, Ziyang Li*, Binghong Chen, Karan Samel, Mayur Naik, Le Song, Xujie Si.
NeurIPS 2021.
Sporq: An Interactive Environment for Exploring Code Using Query-by-Example
Aaditya Naik, Jonathan Mendelson, Nate Sands, Yuepeng Wang, Mayur Naik, Mukund Raghothaman.
UIST 2021.
Example-Guided Synthesis of Relational Queries
Aalok Thakkar, Aaditya Naik, Nate Sands, Rajeev Alur, Mayur Naik, Mukund Raghothaman.
PLDI 2021.
Arbitrar: User-Guided API Misuse Detection
Ziyang Li, Aravind Machiry, Binghong Chen, Ke Wang, Mayur Naik, Le Song.
S&P 2021.
GenSynth: Synthesizing Datalog Programs without Language Bias
Jonathan Mendelson, Aaditya Naik, Mukund Raghothaman, Mayur Naik.
AAAI 2021.
Generating Programmatic Referring Expressions via Program Synthesis
Jiani Huang, Calvin Smith, Osbert Bastani, Rishabh Singh, Aws Albarghouthi, Mayur Naik.
ICML 2020.
Code2Inv: A Deep Learning Framework for Program Verification
Xujie Si*, Aaditya Naik*, Hanjun Dai, Mayur Naik, Le Song.
CAV 2020.
Hoppity: Learning Graph Transformations to Detect and Fix Bugs in Programs
Elizabeth Dinella*, Hanjun Dai*, Ziyang Li, Mayur Naik, Le Song, Ke Wang.
ICLR 2020.
Spotlight Paper
Provenance-Guided Synthesis of Datalog Programs
Mukund Raghothaman, Jonathan Mendelson, David Zhao, Mayur Naik, Bernhard Scholz.
POPL 2020.
Synthesizing Datalog Programs using Numerical Relaxation
Xujie Si*, Mukund Raghothaman*, Kihong Heo, Mayur Naik.
IJCAI 2019.
Continuously Reasoning about Programs using Differential Bayesian Inference
Kihong Heo*, Mukund Raghothaman*, Xujie Si, Mayur Naik.
PLDI 2019.
Distinguished Paper Award
Learning Neurosymbolic Generative Models via Program Synthesis
Halley Young, Osbert Bastani, Mayur Naik.
ICML 2019.
Learning a Meta-Solver for Syntax-Guided Program Synthesis
Xujie Si*, Yuan Yang*, Hanjun Dai, Mayur Naik, Le Song.
ICLR 2019.
Learning Loop Invariants for Program Verification
Xujie Si*, Hanjun Dai*, Mukund Raghothaman, Mayur Naik, Le Song.
NeurIPS 2018.
Spotlight Paper
Syntax-Guided Synthesis of Datalog Programs
Xujie Si*, Woosuk Lee*, Richard Zhang, Aws Albarghouthi, Paris Koutris, Mayur Naik.
FSE 2018.
Effective Program Debloating via Reinforcement Learning
Kihong Heo*, Woosuk Lee*, Pardis Pashakhanloo, Mayur Naik.
CCS 2018.
User-Guided Program Reasoning Using Bayesian Inference
Mukund Raghothaman*, Sulekha Kulkarni*, Kihong Heo, Mayur Naik.
PLDI 2018.
Accelerating Search-Based Program Synthesis Using Learned Probabilistic Models
Woosuk Lee, Kihong Heo, Rajeev Alur, Mayur Naik.
PLDI 2018.
Effective Interactive Resolution of Static Analysis Alarms
Xin Zhang, Radu Grigore, Xujie Si, Mayur Naik.
OOPSLA 2017.
Constraint-Based Synthesis of Datalog Programs
Aws Albarghouthi, Paraschos Koutris, Mayur Naik, Calvin Smith.
CP 2017.
Accelerating Program Analyses by Cross-Program Training
Sulekha Kulkarni, Ravi Mangal, Xin Zhang, Mayur Naik.
OOPSLA 2016.
On Incremental Core-Guided MaxSAT Solving
Xujie Si, Xin Zhang, Vasco Manquinho, Mikolas Janota, Alexey Ignatiev, Mayur Naik.
CP 2016.
APISan: Sanitizing API Usages through Semantic Cross-checking
Insu Yun, Changwoo Min, Xujie Si, Yeongjin Jang, Taesoo Kim, Mayur Naik.
USENIX Security 2016.
Scaling Relational Inference Using Proofs and Refutations
Ravi Mangal, Xin Zhang, Aditya Kamath, Aditya Nori, Mayur Naik.
AAAI 2016.
Query-Guided Maximum Satisfiability
Xin Zhang, Ravi Mangal, Aditya Nori, Mayur Naik.
POPL 2016.
Mantis: Efficient Predictions of Execution Time, Energy Usage, Memory Usage and Network Usage on Smart Mobile Devices
Yongin Kwon, Sangmin Lee, Hayoon Yi, Donghyun Kwon, Seungjun Yang, Byung-Gon Chun, Ling Huang, Petros Maniatis, Mayur Naik, Yunheung Paek.
IEEE TMC 2015.
Volt: A Lazy Grounding Framework for Solving Very Large MaxSAT Instances
Ravi Mangal, Xin Zhang, Aditya Nori, Mayur Naik.
SAT 2015.
A User-Guided Approach to Program Analysis
Ravi Mangal, Xin Zhang, Aditya Nori, Mayur Naik.
FSE 2015.
Distinguished Paper Award
FlexJava: Language Support for Safe and Modular Approximate Programming
Jongse Park, Hadi Esmaeilzadeh, Xin Zhang, Mayur Naik, William Harris.
FSE 2015.
Modularity in Lattices: A Case Study on the Correspondence between Top-Down and Bottom-Up Analysis
Ghila Castelnuovo, Mayur Naik, Noam Rinetzky, Mooly Sagiv, Hongseok Yang.
SAS 2015.
COSMOS: Computation Offloading as a Service for Mobile Devices
Cong Shi, Karim Habak, Pranesh Pandurangan, Mostafa Ammar, Mayur Naik, Ellen Zegura.
MobiHoc 2014.
On Abstraction Refinement for Program Analyses in Datalog
Xin Zhang, Ravi Mangal, Radu Grigore, Mayur Naik, Hongseok Yang.
PLDI 2014.
Distinguished Paper Award
Hybrid Top-Down and Bottom-Up Interprocedural Analysis
Xin Zhang, Ravi Mangal, Mayur Naik, Hongseok Yang.
PLDI 2014.
A Correspondence between Two Approaches to Interprocedural Analysis in the Presence of Join
Ravi Mangal, Mayur Naik, Hongseok Yang.
ESOP 2014.
Best Paper Award Nominee
Dynodroid: An Input Generation System for Android Apps
Aravind Machiry, Rohan Tahiliani, Mayur Naik.
FSE 2013.
Test-of-Time Paper Award
and
Distinguished Artifact Award
Mantis: Automatic Performance Prediction for Smartphone Applications
Yongin Kwon, Sangmin Lee, Hayoon Yi, Donghyun Kwon, Seungjun Yang, Byung-Gon Chun, Ling Huang, Petros Maniatis, Mayur Naik, Yunheung Paek.
USENIX ATC 2013.
Finding Optimum Abstractions in Parametric Dataflow Analysis
Xin Zhang, Mayur Naik, Hongseok Yang.
PLDI 2013.
Automated Concolic Testing of Smartphone Apps
Saswat Anand, Mayur Naik, Hongseok Yang, Mary Jean Harrold.
FSE 2012.
Test-of-Time Paper Award
Abstractions from Tests
Mayur Naik, Hongseok Yang, Ghila Castelnuovo, Mooly Sagiv.
POPL 2012.
Yada: Straightforward Parallel Programming
David Gay, Joel Galenson, Mayur Naik, Kathy Yelick.
Parallel Computing, Elsevier, 2011.
Scaling Abstraction Refinement via Pruning
Percy Liang and Mayur Naik.
PLDI 2011.
CloneCloud: Elastic Execution between Mobile Device and Cloud
Byung-Gon Chun, Sunghwan Ihm, Petros Maniatis, Mayur Naik, Ashwin Patti.
EuroSys 2011.
Test-of-Time Paper Award
Learning Minimal Abstractions
Percy Liang, Omer Tripp, Mayur Naik.
POPL 2011.
Predicting Execution Time of Computer Programs Using Sparse Polynomial Regression
Ling Huang, Jinzhu Jia, Bin Yu, Byung-Gon Chun, Petros Maniatis, Mayur Naik.
NIPS 2010.
An Effective Dynamic Analysis for Detecting Generalized Deadlocks
Pallavi Joshi, Mayur Naik, Koushik Sen, David Gay.
FSE 2010.
A Dynamic Evaluation of the Precision of Static Heap Abstractions
Percy Liang, Omer Tripp, Mayur Naik, Mooly Sagiv.
OOPSLA 2010.
CalFuzzer: An Extensible Active Testing Framework for Concurrent Programs
Pallavi Joshi, Mayur Naik, Chang-Seo Park, Koushik Sen.
CAV 2009.
Lightweight Annotations for Controlling Sharing in Concurrent Data Structures
Zachary Anderson, David Gay, Mayur Naik.
PLDI 2009.
A Randomized Dynamic Program Analysis Technique for Detecting Real Deadlocks
Pallavi Joshi, Chang-Seo Park, Koushik Sen, Mayur Naik.
PLDI 2009.
Effective Static Deadlock Detection
Mayur Naik, Chang-Seo Park, Koushik Sen, David Gay.
ICSE 2009.
Distinguished Paper Award
A Type System Equivalent to a Model Checker
Mayur Naik and Jens Palsberg.
ACM TOPLAS 2008.
Conditional Must Not Aliasing for Static Race Detection
Mayur Naik and Alex Aiken.
POPL 2007.
Effective Static Race Detection for Java
Mayur Naik, Alex Aiken, John Whaley.
PLDI 2006.
Statistical Debugging: Simultaneous Isolation of Multiple Bugs
Alice Zheng, Michael Jordan, Ben Liblit, Mayur Naik, Alex Aiken.
ICML 2006.
Scalable Statistical Bug Isolation
Ben Liblit, Mayur Naik, Alice Zheng, Alex Aiken, Michael Jordan.
PLDI 2005.
A Type System Equivalent to a Model Checker
Mayur Naik and Jens Palsberg.
ESOP 2005.
Compiling with Code-Size Constraints
Mayur Naik and Jens Palsberg.
ACM TECS 2004.
From Symptom to Cause: Localizing Errors in Counterexample Traces
Thomas Ball, Mayur Naik, Sriram Rajamani.
POPL 2003.
Compiling with Code-Size Constraints
Mayur Naik and Jens Palsberg.
LCTES 2002.
Invited Articles
Rethinking Static Analysis by Combining Discrete and Continuous Reasoning
Mayur Naik.
SAS 2019.
Maximum Satisfiability in Program Analysis: Applications and Techniques
Mayur Naik, Xujie Si, Xin Zhang, Radu Grigore.
VMCAI 2018.
Maximum Satisfiability in Software Analysis: Applications and Techniques
Xujie Si, Xin Zhang, Radu Grigore, Mayur Naik.
CAV 2017.
ILP-based Resource-aware Compilation
Jens Palsberg and Mayur Naik.
Multiprocessor Systems-on-Chips, Elsevier, 2004.