Ravi Mangal

44 papers A* 7A 3B 6Journal 19Unranked 8
YearRankTypeTitle / Venue / Authors
2026 J jnl
SecCodePRM: A Process Reward Model for Code Security.
CoRR
Weichen Yu, Ravi Mangal, Yinyi Luo, Kai Hu, Jingxuan He, Corina S. Pasareanu, Matt Fredrikson
2025 J jnl
A Mixture of Linear Corrections Generates Secure Code.
CoRR
Weichen Yu, Ravi Mangal, Terry Yue Zhuo, Matt Fredrikson, Corina S. Pasareanu
2025 B conf
Conformal Safety Shielding for Imperfect-Perception Agents.
RV
William Scarbro, Calum Imrie, Sinem Getir Yaman, Kavan Fatehi, Corina S. Pasareanu, Radu Calinescu, Ravi Mangal
2025 J jnl
Conformal Safety Shielding for Imperfect-Perception Agents.
CoRR
William Scarbro, Calum Imrie, Sinem Getir Yaman, Kavan Fatehi, Corina S. Pasareanu, Radu Calinescu, Ravi Mangal
2025 B conf
Debugging and Runtime Analysis of Neural Networks with VLMs (A Case Study).
CAIN
Boyue Caroline Hu, Divya Gopinath, Corina S. Pasareanu, Nina Narodytska, Ravi Mangal, Susmit Jha
2025 J jnl
Debugging and Runtime Analysis of Neural Networks with VLMs (A Case Study).
CoRR
Boyue Caroline Hu, Divya Gopinath, Corina S. Pasareanu, Nina Narodytska, Ravi Mangal, Susmit Jha
2025 J jnl
On Selecting Few-Shot Examples for LLM-based Code Vulnerability Detection.
CoRR
Md Abdul Hannan, Ronghao Ni, Chi Zhang, Limin Jia, Ravi Mangal, Corina S. Pasareanu
2025 B conf
Random Perturbation Attack on LLMs for Code Generation.
CAIN
Qiulu Peng, Chi Zhang, Ravi Mangal, Corina S. Pasareanu, Limin Jia
2025 — conf
Scenario-Based Compositional Verification of Autonomous Systems with Neural Perception.
SAIV
Christopher Watson, Rajeev Alur, Divya Gopinath, Ravi Mangal, Corina S. Pasareanu
2025 J jnl
Scenario-based Compositional Verification of Autonomous Systems with Neural Perception.
CoRR
Christopher Watson, Rajeev Alur, Divya Gopinath, Ravi Mangal, Corina S. Pasareanu
2025 A* conf
Validating Mechanistic Interpretations: An Axiomatic Approach.
ICML
Nils Palumbo, Ravi Mangal, Zifan Wang, Saranya Vijayakumar, Corina S. Pasareanu, Somesh Jha
2025 J jnl
When "Correct" Is Not Safe: Can We Trust Functionally Correct Patches Generated by Code Agents?
CoRR
Yibo Peng, James Song, Lei Li, Xinyu Yang, Mihai Christodorescu, Ravi Mangal, Corina S. Pasareanu, Haizhong Zheng, Beidi Chen
2024 A* conf
Attacks and Defenses for Large Language Models on Coding Tasks.
ASE
Chi Zhang, Zifan Wang, Ruoshi Zhao, Ravi Mangal, Matt Fredrikson, Limin Jia, Corina S. Pasareanu
2024 — conf
Concept-Based Analysis of Neural Networks via Vision-Language Models.
SAIV
Ravi Mangal, Nina Narodytska, Divya Gopinath, Boyue Caroline Hu, Anirban Roy, Susmit Jha, Corina S. Pasareanu
2024 J jnl
Concept-based Analysis of Neural Networks via Vision-Language Models.
CoRR
Ravi Mangal, Nina Narodytska, Divya Gopinath, Boyue Caroline Hu, Anirban Roy, Susmit Jha, Corina S. Pasareanu
2024 J jnl
Controller Synthesis for Autonomous Systems With Deep-Learning Perception Components.
IEEE Trans. Software Eng.
Radu Calinescu, Calum Imrie, Ravi Mangal, Genaína Nunes Rodrigues, Corina S. Pasareanu, Misael Alpizar Santana, Gricel Vázquez
2024 — conf
Formal Verification Techniques for Vision-Based Autonomous Systems - A Survey.
Principles of Verification (3)
Sayan Mitra, Corina S. Pasareanu, Pavithra Prabhakar, Sanjit A. Seshia, Ravi Mangal, Yangge Li, Christopher Watson, Divya Gopinath, Huafeng Yu
2024 J jnl
Mechanistically Interpreting a Transformer-based 2-SAT Solver: An Axiomatic Approach.
CoRR
Nils Palumbo, Ravi Mangal, Zifan Wang, Saranya Vijayakumar, Corina S. Pasareanu, Somesh Jha
2023 B conf
Assumption Generation for Learning-Enabled Autonomous Systems.
RV
Corina S. Pasareanu, Ravi Mangal, Divya Gopinath, Huafeng Yu
2023 J jnl
Assumption Generation for the Verification of Learning-Enabled Autonomous Systems.
CoRR
Corina S. Pasareanu, Ravi Mangal, Divya Gopinath, Huafeng Yu
2023 — conf
Closed-Loop Analysis of Vision-Based Autonomous Systems: A Case Study.
CAV (1)
Corina S. Pasareanu, Ravi Mangal, Divya Gopinath, Sinem Getir Yaman, Calum Imrie, Radu Calinescu, Huafeng Yu
2023 J jnl
Closed-loop Analysis of Vision-based Autonomous Systems: A Case Study.
CoRR
Corina S. Pasareanu, Ravi Mangal, Divya Gopinath, Sinem Getir Yaman, Calum Imrie, Radu Calinescu, Huafeng Yu
2023 B conf
Feature-Guided Analysis of Neural Networks.
FASE
Divya Gopinath, Luca Lungeanu, Ravi Mangal, Corina S. Pasareanu, Siqi Xie, Huafeng Yu
2023 J jnl
Is Certifying 𝓁
CoRR
Ravi Mangal, Klas Leino, Zifan Wang, Kai Hu, Weicheng Yu, Corina S. Pasareanu, Anupam Datta, Matt Fredrikson
2023 A* conf
On the Perils of Cascading Robust Classifiers.
ICLR
Ravi Mangal, Zifan Wang, Chi Zhang, Klas Leino, Corina S. Pasareanu, Matt Fredrikson
2023 J jnl
Transfer Attacks and Defenses for Large Language Models on Coding Tasks.
CoRR
Chi Zhang, Zifan Wang, Ravi Mangal, Matt Fredrikson, Limin Jia, Corina S. Pasareanu
2022 — conf
A Cascade of Checkers for Run-time Certification of Local Robustness.
NSV/FoMLAS@CAV
Ravi Mangal, Corina S. Pasareanu
2022 J jnl
Degradation Attacks on Certifiably Robust Neural Networks.
Trans. Mach. Learn. Res.
Klas Leino, Chi Zhang, Ravi Mangal, Matt Fredrikson, Bryan Parno, Corina S. Pasareanu
2022 J jnl
Discrete-Event Controller Synthesis for Autonomous Systems with Deep-Learning Perception Components.
CoRR
Radu Calinescu, Calum Imrie, Ravi Mangal, Corina S. Pasareanu, Misael Alpizar Santana, Gricel Vázquez
2022 J jnl
On the Perils of Cascading Robust Classifiers.
CoRR
Ravi Mangal, Zifan Wang, Chi Zhang, Klas Leino, Corina S. Pasareanu, Matt Fredrikson
2022 — conf
Self-correcting Neural Networks for Safe Classification.
NSV/FoMLAS@CAV
Klas Leino, Aymeric Fromherz, Ravi Mangal, Matt Fredrikson, Bryan Parno, Corina S. Pasareanu
2021 — —
Reasoning about programs in statistically modeled first-order environments.
Ravi Mangal
2021 J jnl
Self-Repairing Neural Networks: Provable Safety for Deep Networks via Dynamic Repair.
CoRR
Klas Leino, Aymeric Fromherz, Ravi Mangal, Matt Fredrikson, Bryan Parno, Corina S. Pasareanu
2020 B conf
Probabilistic Lipschitz Analysis of Neural Networks.
SAS
Ravi Mangal, Kartik Sarangmath, Aditya V. Nori, Alessandro Orso
2019 J jnl
Robustness of Neural Networks: A Probabilistic and Practical Approach.
CoRR
Ravi Mangal, Aditya V. Nori, Alessandro Orso
2019 — conf
Robustness of neural networks: a probabilistic and practical approach.
ICSE (NIER)
Ravi Mangal, Aditya V. Nori, Alessandro Orso
2016 A conf
Accelerating program analyses by cross-program training.
OOPSLA
Sulekha Kulkarni, Ravi Mangal, Xin Zhang, Mayur Naik
2016 A* conf
Query-guided maximum satisfiability.
POPL
Xin Zhang, Ravi Mangal, Aditya V. Nori, Mayur Naik
2016 A* conf
Scaling Relational Inference Using Proofs and Refutations.
AAAI
Ravi Mangal, Xin Zhang, Aditya Kamath, Aditya V. Nori, Mayur Naik
2015 — conf
A user-guided approach to program analysis.
ESEC/SIGSOFT FSE
Ravi Mangal, Xin Zhang, Aditya V. Nori, Mayur Naik
2015 A conf
Volt: A Lazy Grounding Framework for Solving Very Large MaxSAT Instances.
SAT
Ravi Mangal, Xin Zhang, Aditya V. Nori, Mayur Naik
2014 A conf
A Correspondence between Two Approaches to Interprocedural Analysis in the Presence of Join.
ESOP
Ravi Mangal, Mayur Naik, Hongseok Yang
2014 A* conf
Hybrid top-down and bottom-up interprocedural analysis.
PLDI
Xin Zhang, Ravi Mangal, Mayur Naik, Hongseok Yang
2014 A* conf
On abstraction refinement for program analyses in Datalog.
PLDI
Xin Zhang, Ravi Mangal, Radu Grigore, Mayur Naik, Hongseok Yang