> For the complete documentation index, see [llms.txt](https://lus-organization.gitbook.io/lu_paper_reading/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://lus-organization.gitbook.io/lu_paper_reading/llm/what-can-large-language-models-tell-us-about-time-series-analysis.md).

# What Can Large Language Models Tell Us about Time Series Analysis

**Link:**<https://arxiv.org/pdf/2402.02713.pdf#page=9&zoom=100,384,533>

## Abstract

LLM can get involved in time series analysis.

## LLM Background

```
- Pro: 0 shot 
- Con: Primary for Text sequence
```

Idea: time series and textual information provide essential contexts, LLMs contribute internal knowledge and reasoning capabilities, and pre-trained time series models offer fundamental pattern recognition assurances

Time series data modality:

* Univariate: X = {x1, x2, · · · , xT } ∈ R^T
* Multivariate: X = {x1, x2, · · · , xT } ∈ R^(N\*T)