Llm self defense: By self examination, llms know they are being tricked A Helbling, M Phute, M Hull, DH Chau arXiv preprint arXiv:2308.07308, 2023 | 58 | 2023 |
Robust principles: Architectural design principles for adversarially robust cnns SY Peng, W Xu, C Cornelius, M Hull, K Li, R Duggal, M Phute, J Martin, ... arXiv preprint arXiv:2308.16258, 2023 | 24 | 2023 |
Llm self defense: By self examination, llms know they are being tricked M Phute, A Helbling, MD Hull, SY Peng, S Szyller, C Cornelius, DH Chau The Second Tiny Papers Track at ICLR 2024, 2023 | 13 | 2023 |
Argo lite: Open-source interactive graph exploration and visualization in browsers S Li, Z Zhou, A Upadhayay, O Shaikh, S Freitas, H Park, ZJ Wang, ... Proceedings of the 29th ACM International Conference on Information …, 2020 | 9 | 2020 |
DetectorDetective: Investigating the effects of adversarial examples on object detectors S Vellaichamy, M Hull, ZJ Wang, N Das, SY Peng, H Park, DHP Chau Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 4 | 2022 |
Towards automatic grading of d3. js visualizations M Hull, C Guerin, J Chen, S Routray, DH Chau arXiv preprint arXiv:2110.11227, 2021 | 2 | 2021 |
Navigating the Safety Landscape: Measuring Risks in Finetuning Large Language Models SY Peng, PY Chen, M Hull, DH Chau arXiv preprint arXiv:2405.17374, 2024 | 1 | 2024 |
VISGRADER: Automatic Grading of D3 Visualizations M Hull, V Pednekar, H Murray, N Roy, E Tung, S Routray, C Guerin, ... IEEE Transactions on Visualization and Computer Graphics, 2023 | 1 | 2023 |
REVAMP: Automated Simulations of Adversarial Attacks on Arbitrary Objects in Realistic Scenes M Hull, ZJ Wang, DH Chau arXiv preprint arXiv:2310.12243, 2023 | | 2023 |