|
|
--- |
|
|
license: mit |
|
|
--- |
|
|
|
|
|
|
|
|
# BEDTime: Benchmark for Evaluating Descriptions of Time Series in Multi-Modal Language Models |
|
|
|
|
|
**Dataset Summary** |
|
|
BEDTime is a unified benchmark for evaluating large language and vision-language models on the task of describing time series data. While there are few existing datasets specifically created for time series-to-text generation, many datasets with paired time series and natural language descriptions can be reformulated to fit this purpose. BEDTime does exactly that — harmonizing four existing datasets into a cohesive benchmark. |
|
|
|
|
|
BEDTime contains a total of **10,175 time series** with corresponding natural language descriptions drawn from four sources: |
|
|
|
|
|
1. **TRUCE-Stock**: |
|
|
|
|
|
* Real-world stock data collected via the Google Finance API |
|
|
* 5,687 time series, each 12 time steps long |
|
|
* 3 human-written crowd-sourced descriptions per series |
|
|
* Descriptions (≤ 9 words) focus on **trends, volatility, and relative change** |
|
|
|
|
|
2. **TRUCE-Synthetic**: |
|
|
|
|
|
* 1,677 synthetic time series |
|
|
* Each constructed to exhibit **exactly one** of six predefined patterns (e.g., increase-in-beginning) |
|
|
* 3 crowd-sourced descriptions per series (2–8 words) |
|
|
* Small noise added for realism |
|
|
|
|
|
3. **SUSHI-Tiny**: |
|
|
|
|
|
* 1,400 synthetic time series |
|
|
* Generated with combinations of **trends, periodicities**, and **fluctuation types** |
|
|
* Descriptions are **synthetically generated** based on known generation properties |
|
|
|
|
|
4. **TaxoSynth**: |
|
|
|
|
|
* 1,400 synthetic time series |
|
|
* Lengths range from 24 to 150 time steps |
|
|
* Annotated using **attribute-based taxonomy** and **template-based text generation** |
|
|
* Descriptions are 5 to 40 words long |
|
|
|
|
|
--- |
|
|
|
|
|
**Supported Tasks and Leaderboards** |
|
|
|
|
|
* **Time Series Captioning** (open-generation) |
|
|
* **Time Series Understanding** (true/false(recognition), multiple choice(differentiation)) |
|
|
|
|
|
--- |
|
|
|
|
|
**Languages** |
|
|
|
|
|
* English |
|
|
|
|
|
--- |
|
|
|
|
|
**Dataset Structure** |
|
|
Each entry includes: |
|
|
|
|
|
* A time series \( x<sub>i</sub> \) |
|
|
* One or more paired natural language descriptions \( d<sub>i</sub> \) |
|
|
|
|
|
|
