Data-driven Discovery Benchmark from the paper: "DiscoveryBench: Towards Data-Driven Discovery with Large Language Models"

  🔭 Overview

DiscoveryBench is designed to systematically assess current model capabilities in data-driven discovery tasks and provide a useful resource for improving them. Each DiscoveryBench task consists of a goal and dataset(s). Solving the task requires both statistical analysis and semantic reasoning. A faceted evaluation allows open-ended… See the full description on the dataset page: https://huggingface.co/datasets/allenai/discoverybench.

DiscoveryBench - Alias

A reformatted version of the original DiscoveryBench dataset for easier usage.

🤗 Original Dataset on HF
💻 GitHub Repository
📄 Paper (arXiv)

  📁 Dataset Structure

The dataset consists of real and synthetic subsets: Real Splits:

real_train real_test

Synthetic Splits:

synth_train synth_dev synth_test

Each split contains a list of tasks with references to associated CSV datasets needed to answer the query. LLMs are expected to use the… See the full description on the dataset page: https://huggingface.co/datasets/nhop/discoverybench.