3 accepted papers
The manifold hypothesis presumes that high-dimensional data lies on or near a low-dimensional manifold. While the utility of encoding geometric structure has been demonstrated empirically, rigorous analysis of its impact on the learnability of neural networks is largely missing. Several recent resu…
Recent work has shown that Large Language Models (LLMs) can unintentionally leak sensitive information present in their training data. In this paper, we present Model Perturbations (MoPe), a new method to identify with high confidence if a given text is in the training data of a pre-trained languag…
Jokes are intentionally written to be funny, but not all jokes are created the same. While recent work has shown impressive results on humor detection in text, we instead investigate the more nuanced task of detecting humor subtypes, especially of the more adult variety. To that end, we introduce a…