Datasets:

bzantium
/

LITM

license: apache-2.0
configs:
  - config_name: kv75
    data_files:
      - split: test
        path: data/kv75.jsonl
  - config_name: kv140
    data_files:
      - split: test
        path: data/kv140.jsonl
  - config_name: kv300
    data_files:
      - split: test
        path: data/kv300.jsonl
  - config_name: qa10
    data_files:
      - split: test
        path: data/qa10.jsonl
  - config_name: qa20
    data_files:
      - split: test
        path: data/qa20.jsonl
  - config_name: qa30
    data_files:
      - split: test
        path: data/qa30.jsonl
task_categories:
  - question-answering
tags:
  - lost-in-the-middle
size_categories:
  - n<1K

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")