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ORCIDAISafety@IJCAI 2024: Jeju, Korea
- Gabriel Pedroza, Xiaowei Huang, Xin Cynthia Chen, Fabio Arnez, Huáscar Espinoza, José Hernández-Orallo, Mauricio Castillo-Effen, Richard Mallah, John A. McDermid, Andreas Theodorou:
Proceedings of the IJCAI 2024 Workshop on Artificial Intelligence Safety (AISafety 2024) co-located with the 33rd International Joint Conference on Artificial Intelligence (IJCAI 2024), Jeju, Korea, August 4, 2024. CEUR Workshop Proceedings 3856, CEUR-WS.org 2024
Session 1: AI Safety Assessment: Validation Methods and Techniques
- Anita Raja, Nan Jia, Raffi Khatchadourian:
ReLESS: A Framework for Assessing Safety in Deep Learning Systems. - Qiang Wen, Júlio Mendonça, Fumio Machida, Marcus Völp:
Enhancing Autonomous Vehicle Safety through N-version Machine Learning Systems.
Session 2: AI Robustness: Adversarial Learning and Security/Privacy
- Pedro Mendes, Paolo Romano, David Garlan:
Hyper-parameter Tuning for Adversarially Robust Models. - Ke Lin, Yasir Glani, Ping Luo:
Low-Latency Privacy-Preserving Deep Learning Design via Secure MPC.
Session 3: Safety of Generative AI: OoD and Human vs Machine Generative Detection
- Andres Pollano, Anupam Chaudhuri, Anj Simmons:
Detecting out-of-distribution text using topological features of transformer-based language models. - Kouichi Sakurai, Kaito Taguchi, Yujie Gu:
The Impact of Prompts on Zero-Shot Detection of AI-Generated Text.
Session 4: AI Robustness: Resilience to Noise and Soft Errors
- Syed Sha Qutub, Michael Paulitsch, Karthik Pattabiraman, Korbinian Hagn, Fabian Oboril, Cornelius Bürkle, Kay-Ulrich Scholl, Gereon Hinz, Alois Knoll:
Global Clipper: Enhancing Safety and Reliability of Transformer-based Object Detection Models. - Hyounguk Shon, Seunghee Koh, Yunho Jeon, Junmo Kim:
Neural Vicinal Risk Minimization: Noise-robust Distillation for Noisy Labels.
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