Hoppity: Learning Graph Transformations to Detect and Fix Bugs in Programs. - Elizabeth Dinella; Hanjun Dai; Ziyang Li 002; Mayur Naik; Le Song; Ke Wang 022 (ICLR, 2020)

Scallop: From Probabilistic Deductive Databases to Scalable Differentiable Reasoning. - Jiani Huang; Ziyang Li 002; Binghong Chen; Karan Samel; Mayur Naik; Le Song; Xujie Si (NeurIPS, 2021)

ARBITRAR: User-Guided API Misuse Detection. - Ziyang Li 002; Aravind Machiry; Binghong Chen; Mayur Naik; Ke Wang 022; Le Song (SP, 2021)

Improved Logical Reasoning of Language Models via Differentiable Symbolic Programming. - Hanlin Zhang 002; Jiani Huang; Ziyang Li 002; Mayur Naik; Eric P. Xing (ACL (Findings), 2023)

LASER: Neuro-Symbolic Learning of Semantic Video Representations. - Jiani Huang; Ziyang Li 002; David Jacobs; Mayur Naik; Ser-Nam Lim (CoRR, 2023)

Scallop: A Language for Neurosymbolic Programming. - Ziyang Li 002; Jiani Huang; Mayur Naik (Proc. ACM Program. Lang., 2023)

Relational Programming with Foundational Models. - Ziyang Li 002; Jiani Huang; Jason Liu; Felix Zhu; Eric Zhao 007; William Dodds; Neelay Velingker; Rajeev Alur; Mayur Naik (AAAI, 2024)

DISCRET: Synthesizing Faithful Explanations For Treatment Effect Estimation. - Yinjun Wu; Mayank Keoliya; Kan Chen; Neelay Velingker; Ziyang Li 002; Emily J. Getzen; Qi Long; Mayur Naik; Ravi B. Parikh; Eric Wong 001 (ICML, 2024)

Data-Efficient Learning with Neural Programs. - Alaia Solko-Breslin; Seewon Choi; Ziyang Li 002; Neelay Velingker; Rajeev Alur; Mayur Naik; Eric Wong 001 (NeurIPS, 2024)

TYGR: Type Inference on Stripped Binaries using Graph Neural Networks. - Chang Zhu; Ziyang Li 002; Anton Xue; Ati Priya Bajaj; Wil Gibbs; Yibo Liu; Rajeev Alur; Tiffany Bao; Hanjun Dai; Adam Doupé; Mayur Naik; Yan Shoshitaishvili; et al. (USENIX Security Symposium, 2024)

LLM-Assisted Static Analysis for Detecting Security Vulnerabilities. - Ziyang Li 002; Saikat Dutta 001; Mayur Naik (CoRR, 2024)

Relational Programming with Foundation Models. - Ziyang Li 002; Jiani Huang; Jason Liu; Felix Zhu; Eric Zhao 007; William Dodds; Neelay Velingker; Rajeev Alur; Mayur Naik (CoRR, 2024)

Neurosymbolic Programming in Scallop: Principles and Practice. - Ziyang Li 002; Jiani Huang; Jason Liu; Mayur Naik (Found. Trends Program. Lang., 2024)

LASER: A Neuro-Symbolic Framework for Learning Spatio-Temporal Scene Graphs with Weak Supervision. - Jiani Huang; Ziyang Li 002; Mayur Naik; Ser-Nam Lim (ICLR, 2025)

IRIS: LLM-Assisted Static Analysis for Detecting Security Vulnerabilities. - Ziyang Li 002; Saikat Dutta 001; Mayur Naik (ICLR, 2025)

Understanding the Effectiveness of Large Language Models in Detecting Security Vulnerabilities. - Avishree Khare; Saikat Dutta 001; Ziyang Li 002; Alaia Solko-Breslin; Rajeev Alur; Mayur Naik (ICST, 2025)

NeuroStrata: Harnessing Neuro-Symbolic Paradigms for Improved Testability and Verifiability of Autonomous CPS. - Xi Zheng 001; Ziyang Li 002; Ivan Ruchkin; Ruzica Piskac; Miroslav Pajic (SIGSOFT FSE Companion, 2025)

NeuroStrata: Harnessing Neurosymbolic Paradigms for Improved Design, Testability, and Verifiability of Autonomous CPS. - Xi Zheng 001; Ziyang Li 002; Ivan Ruchkin; Ruzica Piskac; Miroslav Pajic (CoRR, 2025)

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 002; Mayur Naik (CoRR, 2025)

QLCoder: A Query Synthesizer For Static Analysis of Security Vulnerabilities. - Claire Wang; Ziyang Li 002; Saikat Dutta 001; Mayur Naik (CoRR, 2025)

Lobster: A GPU-Accelerated Framework for Neurosymbolic Programming. - Paul Biberstein; Ziyang Li 002; Joseph Devietti; Mayur Naik (ASPLOS (1), 2026)