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---
dataset_info:
features:
- name: doi/arxiv_id
dtype: string
- name: title
dtype: string
- name: paper_category
dtype: string
- name: error_category
dtype: string
- name: error_location
dtype: string
- name: error_severity
dtype: string
- name: error_annotation
dtype: string
- name: paper_content
list:
- name: image_url
struct:
- name: url
dtype: string
- name: text
dtype: string
- name: type
dtype: string
- name: error_local_content
list:
- name: image_url
struct:
- name: url
dtype: string
- name: text
dtype: string
- name: type
dtype: string
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 58231756
num_examples: 68
download_size: 55816319
dataset_size: 58231756
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: cc-by-4.0
language:
- en
size_categories:
- n<1K
---
---
# SPOT
> Preprocessed Contents of **Scientific Paper ErrOr DeTection** (SPOT)
> *SPOT contains 83 papers and 91 human-validated errors to test academic verification capabilities.*
> *This repo contains preprocessed contents of 62 manuscripts with share-permissive licenses.*
## 📖 Overview
This repository holds the **full paper files** (parsed Markdown, and base64 encodings of extracted figures) for the subset of SPOT manuscripts that are openly licensed. Combined with the annotations in [SPOT-MetaData](https://github.com/<org>/SPOT-MetaData), you can run end-to-end evaluations of LLMs on multi-modal academic error detection.
> **Benchmark at a glance**
>
> * **83** published manuscripts
> * **91** confirmed errors (errata or retractions)
> * **10** scientific domains (Math, Physics, Biology, …)
> * **6** error types (Equation/Proof, Fig-duplication, Data inconsistency, …)
> * Average paper length: \~12 000 tokens & 18 figures
> **Included**
> - **62** open-access papers (CC-BY or equivalent)
> - High-fidelity **Markdown** conversions of each PDF
> - **base64 encoding** of every figure, table, and equation
> - All in **openai api** format.
> **Excluded**
> - Paywalled or proprietary manuscripts (cannot be redistributed)
## 📋 Column Descriptions
Each row in `annotations/errors.csv` contains the following fields:
* **`doi/arxiv_id`**:
The paper’s DOI (journal) or arXiv identifier.
* **`title`**:
Full title of the manuscript.
* **`paper_category`**:
Scientific domain of the paper, one of:
Mathematics, Physics, Biology, Chemistry, Materials Science, Medicine, Environmental Science, Engineering, Computer Science, Multidisciplinary.
* **`error_category`**:
Type of error, one of:
* `Equation/Proof`
* `Figure duplication`
* `Data inconsistency`
* `Experiment setup`
* `Reagent identity`
* `Statistical reporting`
* **`error_location`**:
Where the error appears (e.g., Figure 2, Equation (5), Section 3.1, Table 4).
* **`error_severity`**:
Indicates whether the issue led to an `Erratum` correction or a `Retraction`.
* **`error_annotation`**:
Written summary describing the error.
* **`paper_content`**:
Processed content of the full paper (text in markdown, images in base64 encodings).
* **`error_local_content`**:
Extracted snippet around the error—paragraph, caption, or equation block used in experiments in Appendix B.1.
## 📜 License & Copyright
> SPOT code: CC-BY-4.0
> Individual papers & Processed Contents: distributed under their original licenses.
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