bzantium/LITM

Datasets for Lost In The Middle

This repository contains datasets used in the paper "Lost in the Middle: How Language Models Use Long Contexts", focusing on multi-document question answering and key-value retrieval tasks.

Datasets Overview

The datasets provided are as follows:

• Key-Value Retrieval Datasets

  • kv75: Key-Value pairs with 75 keys.
  • kv140: Key-Value pairs with 140 keys.
  • kv300: Key-Value pairs with 300 keys.

• Multi-Document Question Answering Datasets

  • qa10: Questions with answers derived from 10 documents.
  • qa20: Questions with answers derived from 20 documents.
  • qa30: Questions with answers derived from 30 documents.

Loading the Data

You can load these datasets using the Hugging Face datasets library:

from datasets import load_dataset

### Example for loading the kv75 dataset
dataset = load_dataset("bzantium/LITM", "kv75")

### Example for loading the qa20 dataset
dataset = load_dataset("bzantium/LITM", "qa20")