Towards Assurance of LLM Adversarial Robustness using Ontology-Driven Argumentation
- Tomas Bueno Momcilovic
- Beat Buesser
- et al.
- 2024
- xAI 2024
Workshop paper
Publications
84 results for AI Testing
Exploring Vulnerabilities in LLMs: A Red Teaming Approach to Evaluate Social Bias
- Yuya Jeremy Ong
- Jay Pankaj Gala
- et al.
- 2024
- IEEE CISOSE 2024
Conference paperNavigating the Modern Evaluation Landscape: Considerations in Benchmarks and Frameworks for Large Language Models (LLMs)
- Leshem Choshen
- Ariel Gera
- et al.
- 2024
- LREC-COLING 2024
TutorialRing-A-Bell! How Reliable are Concept Removal Methods For Diffusion Models?
- Yu-Lin Tsai
- Chia-yi Hsu
- et al.
- 2024
- ICLR 2024
Conference paperCan LLMs Fix Issues with Reasoning Models? Towards More Likely Models for AI Planning
- Turgay Caglar
- Sirine Belhaj
- et al.
- 2024
- AAAI 2024
Conference paperHuman Evaluation of the Usefulness of Fine-Tuned English Translators for the Guarani Mbya and Nheengatu Indigenous Languages
- Claudio Santos Pinhanez
- Paulo Rodrigo Cavalin
- et al.
- 2024
- PROPOR 2024
Workshop paperWorkshop version: How hard are computer vision datasets? Calibrating dataset difficulty to viewing time
- David Mayo
- Jesse Cummings
- et al.
- 2023
- NeurIPS 2023
Workshop paperUnveiling Safety Vulnerabilities of Large Language Models
- 2023
- EMNLP 2023
Workshop paperURET: Universal Robustness Evaluation Toolkit (for Evasion)
- Kevin Eykholt
- Taesung Lee
- et al.
- 2023
- USENIX Security 2023
Conference paperDetAIL: A Tool to Automatically Detect and Analyze Drift In Language
- Nishtha Madaan
- Adithya Manjunatha
- et al.
- 2023
- IAAI 2023
Conference paper