There is a growing concern that generative AI models will generate outputs closely
resembling the copyrighted materials for which they are trained. This worry has intensified …

Large language models (LLMs) have significantly transformed the landscape of Natural
Language Processing (NLP). Their impact extends across a diverse spectrum of tasks …

While large language models (LLMs) are still being adopted to new domains and utilized in
novel applications, we are experiencing an influx of the new generation of foundation …

Memorization in language models is typically treated as a homogenous phenomenon,
neglecting the specifics of the memorized data. We instead model memorization as the effect …

Extensive research exists on the performance of large language models on logic-based
tasks, whereas relatively little has been done on their ability to generate creative solutions …

The primate brain and artificial intelligence (AI) can both be conceptualized as information
processing systems, each with its own distinct biological and computational architectures …

Data contamination has garnered increased attention in the era of large language models
(LLMs) due to the reliance on extensive internet-derived training corpora. The issue of …

Visual diffusion models have revolutionized the field of creative AI, producing high-quality
and diverse content. However, they inevitably memorize training images or videos …

Large Generative AI (GAI) models have the unparalleled ability to generate text, images,
audio, and other forms of media that are increasingly indistinguishable from human …

Can we localize the weights and mechanisms used by a language model to memorize and
recite entire paragraphs of its training data? In this paper, we show that while memorization …