onurkeles/econ_paper_abstracts

---
license: mit
task_categories:
- text-classification
- question-answering
- text-generation
language:
- en
pretty_name: e
size_categories:
- 1K<n<10K
---
# Dataset Card for Economics Paper Dataset

## Dataset Summary

The Economics Research Paper Dataset was designed to support the development of the LLaMA-2-Econ models, with a focus on Title Generation, Abstract Classification, and Question & Answer (Q&A) tasks. It comprises abstracts and titles of economics research papers, along with synthetic Q&A pairs derived from the abstracts, to facilitate training of large language models for economics-specific applications.

## Dataset Description

**Content:** The dataset includes:
- Economics paper abstracts and titles.

**Source:** The data was collected using the arXiv API, with papers selected from the categories Econometrics (ec.EM), General Economics (ec.GN), and Theoretical Economics (ec.TH).

**Volume:**
- Total abstracts and titles: 6362

## Intended Uses

This dataset is intended for training and evaluating language models specialized in:
- Generating titles for economics research papers.
- Classifying abstracts into sub-fields of economics.
- Answering questions based on economics paper abstracts.

## Dataset Creation

### Curation Rationale

The dataset was curated to address the lack of specialized tools and datasets for enhancing research within the economics domain, leveraging the potential of language models like LLaMA-2.

### Source Data

#### Initial Data Collection and Normalization

Data was collected through the arXiv API, targeting papers within specified categories of economics. Titles and abstracts were extracted, and synthetic Q&A pairs were generated using a process that involved the GPT-3.5 Turbo model for contextual dialogue creation.

### Licensing Information

The dataset is derived from arXiv papers. Users are advised to adhere to arXiv's terms of use.

原始信息汇总

Economics Research Paper Dataset 概述

数据集概要

该数据集名为“Economics Research Paper Dataset”，旨在支持LLaMA-2-Econ模型的开发，专注于经济学研究论文的标题生成、摘要分类和问答任务。数据集包含经济学研究论文的摘要和标题，以及从摘要中衍生的合成问答对，用于训练大型语言模型以应用于经济学领域。

数据集描述

内容：

• 包含经济学论文的摘要和标题。

来源：

• 数据通过arXiv API收集，选取了Econometrics (ec.EM)、General Economics (ec.GN)和Theoretical Economics (ec.TH)类别的论文。

容量：

• 总摘要和标题数量：6362

预期用途

该数据集主要用于：

• 生成经济学研究论文的标题。
• 将摘要分类到经济学的子领域。
• 基于经济学论文摘要回答问题。

数据集创建

筛选理由

数据集的筛选旨在解决经济学领域内缺乏专门工具和数据集的问题，利用LLaMA-2等语言模型的潜力提升研究质量。

原始数据

初始数据收集和标准化

• 数据通过arXiv API收集，特别关注经济学相关类别的论文。
• 提取标题和摘要，并使用GPT-3.5 Turbo模型生成合成的问答对。

许可信息

• 数据集源自arXiv论文，用户需遵守arXiv的使用条款。