Do We Need Large Language Models for Time Series? - Understanding LLMs' Limitations in Time Series Analysis

Join a research seminar where Vinayak Gupta from Lawrence Livermore National Laboratory explores the intersection of Large Language Models (LLMs) and time-series data analysis. Discover insights from a groundbreaking benchmark study that evaluates LLMs' ability to understand and process time-series data - a crucial format for finance and healthcare applications. Learn about the limitations of current approaches claiming LLM effectiveness in forecasting, and understand why simpler solutions, such as basic attention layers, often outperform complex language models in time-series applications. Gain valuable perspectives from Gupta's extensive research experience at prestigious institutions including IBM Research and the University of Washington, as he challenges conventional wisdom about the necessity of LLMs in time-series analysis.