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. |
Prerequisites 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.
Agenda
| Date | Session | Materials |
