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Found 6 papers, 3 papers with code
Code Llama: Open Foundation Models for Code
We release Code Llama, a family of large language models for code based on Llama 2 providing state-of-the-art performance among open models, infilling capabilities, support for large input contexts, and zero-shot instruction following ability for programming tasks.
Ranked #26 on
Code Generation
on MBPP
Adversarial Text Normalization
Additionally, the process to retrain a model is time and resource intensive, creating a need for a lightweight, reusable defense.
AugLy: Data Augmentations for Robustness
We introduce AugLy, a data augmentation library with a focus on adversarial robustness.
Towards Measuring Fairness in AI: the Casual Conversations Dataset
The videos were recorded in multiple U. S. states with a diverse set of adults in various age, gender and apparent skin tone groups.
Adversarial Threats to DeepFake Detection: A Practical Perspective
We perform our evaluations on the winning entries of the DeepFake Detection Challenge (DFDC) and demonstrate that they can be easily bypassed in a practical attack scenario by designing transferable and accessible adversarial attacks.
The DeepFake Detection Challenge (DFDC) Dataset
In addition to Deepfakes, a variety of GAN-based face swapping methods have also been published with accompanying code.
