Ravi Mangal

Orcid: 0000-0001-6267-6995

According to our database1, Ravi Mangal authored at least 26 papers between 2014 and 2024.

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Bibliography

2024
Controller Synthesis for Autonomous Systems With Deep-Learning Perception Components.
IEEE Trans. Software Eng., June, 2024

Mechanistically Interpreting a Transformer-based 2-SAT Solver: An Axiomatic Approach.
CoRR, 2024

Concept-Based Analysis of Neural Networks via Vision-Language Models.
Proceedings of the AI Verification - First International Symposium, 2024

2023
Transfer Attacks and Defenses for Large Language Models on Coding Tasks.
CoRR, 2023

Is Certifying 𝓁<sub>p</sub> Robustness Still Worthwhile?
CoRR, 2023

Assumption Generation for the Verification of Learning-Enabled Autonomous Systems.
CoRR, 2023

Assumption Generation for Learning-Enabled Autonomous Systems.
Proceedings of the Runtime Verification - 23rd International Conference, 2023

On the Perils of Cascading Robust Classifiers.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Feature-Guided Analysis of Neural Networks.
Proceedings of the Fundamental Approaches to Software Engineering, 2023

Closed-Loop Analysis of Vision-Based Autonomous Systems: A Case Study.
Proceedings of the Computer Aided Verification - 35th International Conference, 2023

2022
Degradation Attacks on Certifiably Robust Neural Networks.
Trans. Mach. Learn. Res., 2022

Discrete-Event Controller Synthesis for Autonomous Systems with Deep-Learning Perception Components.
CoRR, 2022

A Cascade of Checkers for Run-time Certification of Local Robustness.
Proceedings of the Software Verification and Formal Methods for ML-Enabled Autonomous Systems, 2022

Self-correcting Neural Networks for Safe Classification.
Proceedings of the Software Verification and Formal Methods for ML-Enabled Autonomous Systems, 2022

2021
Reasoning about programs in statistically modeled first-order environments.
PhD thesis, 2021

Self-Repairing Neural Networks: Provable Safety for Deep Networks via Dynamic Repair.
CoRR, 2021

2020
Probabilistic Lipschitz Analysis of Neural Networks.
Proceedings of the Static Analysis - 27th International Symposium, 2020

2019
Robustness of neural networks: a probabilistic and practical approach.
Proceedings of the 41st International Conference on Software Engineering: New Ideas and Emerging Results, 2019

2016
Query-guided maximum satisfiability.
Proceedings of the 43rd Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, 2016

Accelerating program analyses by cross-program training.
Proceedings of the 2016 ACM SIGPLAN International Conference on Object-Oriented Programming, 2016

Scaling Relational Inference Using Proofs and Refutations.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
A user-guided approach to program analysis.
Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering, 2015

Volt: A Lazy Grounding Framework for Solving Very Large MaxSAT Instances.
Proceedings of the Theory and Applications of Satisfiability Testing - SAT 2015, 2015

2014
Hybrid top-down and bottom-up interprocedural analysis.
Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation, 2014

On abstraction refinement for program analyses in Datalog.
Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation, 2014

A Correspondence between Two Approaches to Interprocedural Analysis in the Presence of Join.
Proceedings of the Programming Languages and Systems, 2014


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