Testuggine, Davide

The hateful memes challenge: Detecting hate speech in multimodal memes

Kiela, D., Firooz, H., Mohan, A., Goswami, V., Singh, A., Ringshia, P., & Testuggine, D. (2020) · arXiv

Hate Speech and Cyberbullying DetectionSentiment Analysis and Opinion Mining

Cited by 352

Are Multimodal Transformers Robust to Missing Modality?

Ma, M., Ren, J., Zhao, L., Testuggine, D., & Peng, X. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 198

Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations

Inan, H., Upasani, K., Chi, J., Rungta, R., Iyer, K., Mao, Y., Tontchev, M., Hu, Q., Fuller, B., Testuggine, D., et al. (2023) · arXiv

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 56

Introducing v0.5 of the AI Safety Benchmark from MLCommons

Vidgen, B., Agrawal, A., Ahmed, A. M., Akinwande, V., Al-Nuaimi, N., Alfaraj, N., Alhajjar, E., Aroyo, L., Bavalatti, T., Bartolo, M., et al. (2024) · arXiv

Ethics and Social Impacts of AIAdversarial Robustness in Machine Learning

Cited by 5