David Shriver

According to our database, David Shriver authored at least 19 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Concept-ROT: Poisoning Concepts in Large Language Models with Model Editing.

Keltin Grimes, Marco Christiani, David Shriver, Marissa Connor

CoRR, 2024

The SaTML '24 CNN Interpretability Competition: New Innovations for Concept-Level Interpretability.

Stephen Casper, Jieun Yun, Joonhyuk Baek, Yeseong Jung, Minhwan Kim, Kiwan Kwon, Saerom Park, Hayden Moore, David Shriver, Marissa Connor, Keltin Grimes, Angus Nicolson, Arush Tagade, Jessica Rumbelow, Hieu Minh Nguyen, Dylan Hadfield-Menell

CoRR, 2024

2023

DeepManeuver: Adversarial Test Generation for Trajectory Manipulation of Autonomous Vehicles.

Meriel von Stein, David Shriver, Sebastian G. Elbaum

IEEE Trans. Software Eng., October, 2023

Deeper Notions of Correctness in Image-Based DNNs: Lifting Properties from Pixel to Entities.

Felipe Toledo, David Shriver, Sebastian G. Elbaum, Matthew B. Dwyer

Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2023

2021

Distribution Models for Falsification and Verification of DNNs.

Felipe Toledo, David Shriver, Sebastian G. Elbaum, Matthew B. Dwyer

Dataset, August, 2021

Distribution Models for Falsification and Verification of DNNs.

Felipe Toledo, David Shriver, Sebastian G. Elbaum, Matthew B. Dwyer

Dataset, July, 2021

Distribution Models for Falsification and Verification of DNNs.

Felipe Toledo, David Shriver, Sebastian G. Elbaum, Matthew Dwyer

Dataset, July, 2021

Artifact for DNNV: A Framework for Deep Neural Network Verification.

David Shriver, Sebastian G. Elbaum, Matthew B. Dwyer

Dataset, April, 2021

Artifact for DNNV: A Framework for Deep Neural Network Verification.

David Shriver, Sebastian G. Elbaum, Matthew B. Dwyer

Dataset, April, 2021

Reducing DNN Properties to Enable Falsification with Adversarial Attacks.

David Shriver, Sebastian G. Elbaum, Matthew Dwyer

Dataset, January, 2021

Distribution Models for Falsification and Verification of DNNs.

Felipe Toledo, David Shriver, Sebastian G. Elbaum, Matthew B. Dwyer

Proceedings of the 36th IEEE/ACM International Conference on Automated Software Engineering, 2021

Artifact: Reducing DNN Properties to Enable Falsification with Adversarial Attacks.

David Shriver, Sebastian G. Elbaum, Matthew B. Dwyer

Proceedings of the 43rd IEEE/ACM International Conference on Software Engineering: Companion Proceedings, 2021

Reducing DNN Properties to Enable Falsification with Adversarial Attacks.

David Shriver, Sebastian G. Elbaum, Matthew B. Dwyer

Proceedings of the 43rd IEEE/ACM International Conference on Software Engineering, 2021

DNNV: A Framework for Deep Neural Network Verification.

David Shriver, Sebastian G. Elbaum, Matthew B. Dwyer

Proceedings of the Computer Aided Verification - 33rd International Conference, 2021

2020

Systematic Generation of Diverse Benchmarks for DNN Verification.

Dong Xu, David Shriver, Matthew B. Dwyer, Sebastian G. Elbaum

Proceedings of the Computer Aided Verification - 32nd International Conference, 2020

2019

Refactoring Neural Networks for Verification.

David Shriver, Dong Xu, Sebastian G. Elbaum, Matthew B. Dwyer

CoRR, 2019

Evaluating Recommender System Stability with Influence-Guided Fuzzing.

David Shriver, Sebastian G. Elbaum, Matthew B. Dwyer, David S. Rosenblum

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Toward the development of richer properties for recommender systems.

David Shriver

Proceedings of the 40th International Conference on Software Engineering: Companion Proceeedings, 2018

2017

At the End of Synthesis: Narrowing Program Candidates.

David Shriver, Sebastian G. Elbaum, Kathryn T. Stolee

Proceedings of the 39th IEEE/ACM International Conference on Software Engineering: New Ideas and Emerging Technologies Results Track, 2017