Abstract: Despite the impressive results of deep learning models, modern large-scale systems are required to be trained using massive amounts of manually annotated or freely…
Abstract: Large language models (LLMs) have significantly extended the boundaries of NLP's potential applications, partially because of their increased ability to do complex reasoning. However,…
Abstract: Hidden Markov models are a popular class of time series models where the observation process depends on a latent state process taken to evolve…
Abstract: Quantum computing capabilities are evolving rapidly. With that increasing are the security risks especially to the public key ciphersuites widely used in day-today lives…
Abstract: A majority of existing research in large language models and generative AI systems focuses on scaling and engineering. In this talk, I argue that…
Abstract: Today, access to high-quality data has become the key bottleneck to deploying machine learning. Often, the data that is most valuable is locked away…
Abstract: As babies, we begin to grasp the world through spontaneous observations, gradually developing generalized knowledge about the world. This foundational knowledge enables humans to…
Abstract: We consider the problem of sorting a set of items having an unknown total order by doing binary comparisons of the items, given the…
Abstract: In the United States, racial capitalism has facilitated the organized abandonment of minoritized communities through the removal of resources, the expansion of carceral and…
Abstract: AI has revolutionized the way we interact online. Despite this, it hasn't quite made the leap when it comes to tasks like cooking dinner…
Abstract: The emergence of powerful, ever more universal models such as ChatGPT, and stable Diffusion, made generative modeling (GM) undoubtedly a focal point for modern…
Abstract: Large language models (LLMs) have soared in popularity in recent years, thanks to their ability to generate well-formed natural language answers for a myriad…