readme update

README.md

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-license: mit
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+---
+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))
+* 🧪 Evaluated using automatic (e.g., NLI-based entailment) and human metrics
+
+---
+
+**Languages**
+
+* English
+
+---
+
+**Dataset Structure**
+Each entry includes:
+
+* A time series (`x_i`)
+* One or more paired natural language descriptions (`d_i`)