Year: 2024
Type: dissertation
Abstract: Time series are critical data which drive countless decisions in finance, healthcare, and science. However, multimodal NLP research has mostly focused on images and video. Here I enumerate barriers towards such models and describe my work towards mitigating them. I detail new multimodal NLP tasks for reasoning about time series, describe an LLM-powered agent that can answer questions about time series, and present methods for pretraining time series encoders. I also share work on using language models for code generation to assist scientists.
Author: Merrill, Mike A.
Institution: University of Washington
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7126783933