license:apache-2.0 size_categories:100K<n<1M format:json modality:text library:datasets library:dask library:mlcroissant region:us
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license: apache-2.0
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# Data Collection and Classification for Citation Generation Dataset

## 1. Classification Criteria
The dataset is classified based on two standards:

1. **Topic Classification (15 categories)** from the TNews dataset, which is referenced in related academic papers.
2. **Five Categories**:
    - Numbers
    - People
    - Locations
    - Time
    - Positions

## 2. Data Collection
Data is collected from two main sources:
- **Xinhua News Agency**: News articles sourced from their press releases.
- **New Language System (XinYu)**: Answers from the online citation-based question-answering system.

## 3. Data Construction
The collected data from Step 2 is processed using a large model (GPT-4-O). The data is then classified according to the two classification criteria mentioned in Step 1. The resulting dataset is a categorized citation generation dataset.
# Citation Statistics for the Dataset

## Citation Count by Category

Below are the citation counts for each category:

| Category                          | Quantity |
|-----------------------------------|----------|
| Education                         | 1199     |
| Finance                           | 2899     |
| Health                            | 1446     |
| Technology                        | 1474     |
| Agriculture, Rural Areas, Farmers | 1790     |
| Real Estate                       | 1629     |
| International                     | 1726     |
| Law                               | 1588     |
| Culture                           | 890      |
| Lifestyle                         | 1149     |
| Weather                           | 1661     |
| Politics                          | 1630     |
| Tourism                           | 1538     |
| Sports                            | 1063     |
| Food                              | 1237     |
| Military                          | 1424     |
| Automobiles                       | 1403     |
| Fashion                           | 1358     |
| Gaming                            | 1098     |
| Entertainment                     | 1128     |

### Total Citations
The total number of citations in the dataset is: 29,330

# Project Directory Structure Overview

This document explains the structure and contents of the project directories.

## Ablation_data
The `Ablation_data` directory contains the experimental data and statistical results from the ablation studies. The subdirectories within it correspond to different variations of the ablation experiments:

- **ref_deleted**: Data for experiments where references are removed (ablation of references).
- **ref_order**: Data for experiments testing the effect of reference order (whether the references are provided in a specific order).
- **ref_reverse_order**: Data for experiments where references are provided in reverse order.
- **single_sentence**: Data for experiments involving a single sentence as input, to assess its impact.

## Leaderboard_data
The `Leaderboard_data` directory contains the main experimental data related to the leaderboard models and their citation capabilities. The subdirectories are:

- **main_data**: Data on the experiments conducted with 16 models, evaluating their ability to handle citations in a concatenated model setup.
- **main_stats**: Statistical results from the above experiments.
- **manual_label**: Data from experiments where manual labeling was used to evaluate the models' performance.
- **post_mounted_format**: Results from experiments where models were labeled in a post-mounted format.
- **xml_format**: Results from experiments using the XML format for model outputs.

According to the directory introduction, you can select the experimental data directory you want to view and download.

# Dataset Loading Instructions

This document explains how to load different subsets of the `lmc12345678/ACL2025_LMCBench_dataset` using the Hugging Face `datasets` library.

## Loading the Dataset

You can load the data from different parts of the dataset by specifying the correct `data_dir` and dataset split.

```python
from datasets import load_dataset
# Load the whole Ablation_data dataset
ablation_data = load_dataset('lmc12345678/ACL2025_LMCBench_dataset', data_dir='Ablation_data')
# Load a specific subdirectory within Ablation_data, e.g., ref_deleted
ablation_ref_deleted = load_dataset('lmc12345678/ACL2025_LMCBench_dataset', data_dir='Ablation_data/ref_deleted')
# Load the entire Leaderboard_data dataset
leaderboard_data = load_dataset('lmc12345678/ACL2025_LMCBench_dataset', data_dir='Leaderboard_data')
# Load a specific subdirectory within Leaderboard_data, e.g., main_data
leaderboard_main_data = load_dataset('lmc12345678/ACL2025_LMCBench_dataset', data_dir='Leaderboard_data/main_data')

Ensure that you have the datasets library installed and that your environment has access to the dataset repository (lmc12345678/ACL2025_LMCBench_dataset). If you encounter issues, make sure the directory paths match your dataset structure.
```
# License

The `ACL2025_LMCBench_dataset` and its associated materials are released under the **Apache License 2.0**.
# Contact

The original author hosts the code for applying this dataset on GitHub:https://anonymous.4open.science/r/ACL2025_LMCBench-73A4