Search Results for author:
Found 4 papers, 1 papers with code
Bypassing the Safety Training of Open-Source LLMs with Priming Attacks
With the recent surge in popularity of LLMs has come an ever-increasing need for LLM safety training.
Robust Universal Adversarial Perturbations
We further show that by using a set of primitive transformations our method can generalize well to unseen transformations such as fog, JPEG compression, etc.
A novel sentence embedding based topic detection method for micro-blog
We use an unsupervised neural sentence embedding model to map the blogs to an embedding space.
A Simple and Effective Approach to Coverage-Aware Neural Machine Translation
We offer a simple and effective method to seek a better balance between model confidence and length preference for Neural Machine Translation (NMT).
Cannot find the paper you are looking for? You can
Submit a new open access paper.
