Abstract Large language models (LLMs) have demonstrated incredible power, but they also possess vulnerabilities that can lead to misuse and potential attacks. In this presentation, we will address two fundamental questions regarding the responsible utilization[...]

Abstract The arms race to build increasingly larger, powerful language models (LMs) in the past year has been remarkable. Yet incorporating LMs effectively into practical applications that facilitate manual workflows remains challenging. I will discuss[...]

Abstract Embedding text sequences is a widespread requirement in modern language understanding. Existing approaches focus largely on constant-size representations. This is problematic, as the amount of information contained in text often varies with the length[...]

Abstract The growing power in computing and AI promises a near-term future of human-machine teamwork. In this talk, I will present my research group’s efforts in understanding the complex dynamics of human-machine interaction and designing[...]

Abstract The use of NLP in the realm of financial technology is broad and complex, with applications ranging from sentiment analysis and named entity recognition to question answering. Large Language Models (LLMs) have been shown[...]

Abstract Visually rich documents (scanned or digital) remain important for many consumer and business use cases. During this talk we will share recent work from our team in the Document Intelligence Lab of Adobe Research[...]