Ruprecht-Karls-Universität Heidelberg
Institut für Computerlinguistik

Bilder vom Neuenheimer Feld, Heidelberg und der Universität Heidelberg

Multimodal Large Language Models for Time Series

Module Description

Course Module Abbreviation Credit Points
BA-2010[100%|75%] CS-CL 6 LP
BA-2010[50%] BS-CL 6 LP
BA-2010[25%] BS-AC 4 LP
BA-2010 AS-CL 8 LP
Master SS-CL-TAC 8 LP
Lecturer Michael Staniek
Module Type Proseminar / Hauptseminar
Language English
First Session 14.10.2024
Time and Place Mo, 13:15 - 14:45, SR 26 / INF 329
Commitment Period tbd.

Prerequisite for Participation

  • Neural Networks
  • Statistical Methods

Assessment

  • Presentation
  • Second Presentation OR Project OR Term Paper

Content

Large Language Models are the current State of the Art in many tasks. Multimodality for LLMs is an area with active research, like including images, pdfs and more into LLMs. An area that has not gotten as much focus is the usage of LLMs for Time Series. Including Time Series in LLMs to generate better text, or using LLMs as encoders for tasks like time series forecasting.
We will take a look at current works that combine LLMs with Time Series.

Module Overview

Agenda

Date Session Materials

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