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