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README.md
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# exHarmony: Authorship and Citations for Benchmarking the Reviewer Assignment Problem
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The **exHarmony** dataset is designed for benchmarking the **Reviewer Assignment Problem (RAP)**, formulated as a **text retrieval** task. Given a paper (query), the goal is to retrieve relevant authors (documents) who are most suitable as reviewers.
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## Dataset Summary
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* **Collection split**: A large set of scientific papers used for indexing.
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* **Test split**: Papers held out for evaluation.
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* **Authors' works mapping**: Links each author to their published works.
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* **Authors' information**: Includes metadata such as citation counts, institutional affiliation, and years of experience.
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## Citation
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If you use this resource, please cite our paper:
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# exHarmony: Authorship and Citations for Benchmarking the Reviewer Assignment Problem
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## Dataset Summary
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**exHarmony** is a large-scale benchmark dataset for the **Reviewer Assignment Problem (RAP)**, reframing reviewer recommendation as an **information retrieval** task.
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It leverages publication metadata from **OpenAlex** to construct a collection of papers, their authors, citation links, and multiple **qrel definitions** for evaluation.
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The dataset allows researchers to systematically study reviewer recommendation under different assumptions of reviewer expertise (e.g., authorship, citation networks, and similarity-filtered citations).
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exHarmony was introduced in the paper:
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> *exHarmony: Authorship and Citations for Benchmarking the Reviewer Assignment Problem*
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> Ebrahimi, Salamat, Arabzadeh, Bashari, Bagheri (ECIR 2025)
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* **Collection split**: A large set of scientific papers used for indexing.
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* **Test split**: Papers held out for evaluation.
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* **Authors' works mapping**: Links each author to their published works.
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* **Authors' information**: Includes metadata such as citation counts, institutional affiliation, and years of experience.
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## Usage
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```python
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from datasets import load_dataset
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dataset = load_dataset("Reviewerly/exHarmony")
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# Example: Access paper collection
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papers = dataset["papers_collection"]
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print(papers[0])
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```
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## Dataset Structure
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### Data Files
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| Description | File Name | File Size | Num Records | Format |
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| ---------------------- | ------------------------------------ | --------- | ----------- | ------------------------------------------------------------------ |
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| Collection | `papers_collection.jsonl` | 1.6 GB | 1,204,150 | paper\_id, title, abstract |
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| Test | `papers_test.jsonl` | 15 MB | 9,771 | paper\_id, title, abstract |
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| Test (judgable) | `papers_test_judgable.jsonl` | 14 MB | 7,944 | paper\_id, title, abstract |
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| Authors’ Works Mapping | `authors_works_collection_ids.jsonl` | 222 MB | 1,589,723 | author\_id, list\_of\_authors\_papers |
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| Authors’ Information | `authors_info.jsonl` | 225 MB | 1,589,723 | author\_id, citation, works\_count, experience\_years, institution |
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**Format:** JSON Lines (`.jsonl`), one JSON object per record.
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### Example Records
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**Paper record:**
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```json
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{"id": "https://openalex.org/W4323317762", "title": "Sharding-Based Proof-of-Stake Blockchain Protocols: Key Components & Probabilistic Security Analysis", "abstract": "Blockchain technology has been gaining great interest from a variety of sectors including healthcare, supply chain, and cryptocurrencies..."}
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```
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**Author works mapping:**
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```json
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{"id": "https://openalex.org/A5083262615", "works": ["https://openalex.org/W4323317762", "https://openalex.org/W4285189682"]}
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```
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**Author information:**
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```json
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{"id": "https://openalex.org/A5083262615", "citations": 238, "works_count": 14, "experience_years": 5, "institution": "Université de Montréal"}
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```
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## Qrel Files
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exHarmony provides **multiple qrels** to evaluate RAP under different assumptions:
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| Qrel Set | Description |
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| --------------------- | --------------------------------------------------------------------------------------------------------------------------------- |
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| **exHarmony-Authors** | Assumes the best reviewers are the **authors of the paper**. Includes `all-authors` and `established-authors` (≥15 publications). |
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| **exHarmony-Cite** | Considers **authors of cited papers** as reviewers. Includes both `all-authors` and `established-authors`. |
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| **exHarmony-SimCite** | Restricts citation-based relevance to **top-10 most similar cited papers** (using SPECTER embeddings). Includes both subsets. |
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## Citation
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If you use this resource, please cite our paper:
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