---
language: [en]
pretty_name: MemoryCD
size_categories: [100K<n<1M]
task_categories: [text-generation]
tags:
  - amazon-reviews
  - cross-domain
  - recommendation
  - memory
  - llm
  - evaluation
configs:
  - config_name: users_interactions
    data_files:
      - split: test
        path: "users/cross_domain_users_sampled.jsonl.gz"
    default: true
  - config_name: meta_personal_care
    data_files:
      - split: test
        path: "meta/Beauty_and_Personal_Care.jsonl.gz"
  - config_name: meta_books
    data_files:
      - split: test
        path: "meta/Books.jsonl.gz"
  - config_name: meta_electronics
    data_files:
      - split: test
        path: "meta/Electronics.jsonl.gz"
  - config_name: meta_home
    data_files:
      - split: test
        path: "meta/Home_and_Kitchen.jsonl.gz"
---

# MemoryCD

Filtered cross-domain subset of Amazon Reviews 2023 for memory-augmented LLM
evaluation. All configs expose a single `test` split (evaluation only).

## Contents

| Config | Records |
|---|---:|
| `users_interactions` | 323 users |
| `meta_personal_care` | 33,475 items |
| `meta_books` | 48,054 items |
| `meta_electronics` | 25,441 items |
| `meta_home` | 60,900 items |

The 4 meta files contain exactly the items referenced by the 323 users
(167,870 unique `parent_asin`, 100% coverage). The `price` field is
normalized to `float | null` across all meta files.

## Quick start

```python
from datasets import load_dataset
users = load_dataset("WZDavid/MemoryCD", "users_interactions", split="test")
books = load_dataset("WZDavid/MemoryCD", "meta_books", split="test")
```

## Source

Derived from [McAuley-Lab/Amazon-Reviews-2023](https://huggingface.co/datasets/McAuley-Lab/Amazon-Reviews-2023).