| --- |
| dataset_info: |
| features: |
| - name: forum_id |
| dtype: string |
| - name: forum_title |
| dtype: string |
| - name: forum_authors |
| sequence: string |
| - name: forum_abstract |
| dtype: string |
| - name: forum_keywords |
| sequence: string |
| - name: forum_pdf_url |
| dtype: string |
| - name: forum_url |
| dtype: string |
| - name: note_id |
| dtype: string |
| - name: note_type |
| dtype: string |
| - name: note_created |
| dtype: int64 |
| - name: note_replyto |
| dtype: string |
| - name: note_readers |
| sequence: string |
| - name: note_signatures |
| sequence: string |
| - name: venue |
| dtype: string |
| - name: year |
| dtype: string |
| - name: note_text |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 2565679898 |
| num_examples: 626430 |
| download_size: 758998779 |
| dataset_size: 2565679898 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| license: odc-by |
| language: |
| - en |
| tags: |
| - peer-review |
| - openreview |
| - scientific-reviews |
| size_categories: |
| - 100K<n<1M |
| --- |
| |
| # OpenReview Raw |
|
|
| Raw peer review data from OpenReview, covering major ML/AI venues (ICLR, NeurIPS, EMNLP, COLM, ACM MM, and more). Includes reviews, official comments, meta-reviews, and decisions for 49,023 unique papers. |
|
|
| Originally from [`sumukshashidhar-archive/openreview_raw`](https://huggingface.co/datasets/sumukshashidhar-archive/openreview_raw). |
|
|
| This dataset is a compilation of publicly available data from OpenReview. All original content and data rights belong to OpenReview. This compilation is made available under the Open Data Commons Attribution License (ODC-By). Users must attribute both this compilation and the original source (OpenReview) in any use of this dataset. |
|
|
| ## Dataset Statistics |
|
|
| | Statistic | Value | |
| |-----------|-------| |
| | Total rows | 626,430 | |
| | Unique papers | 49,023 | |
| | Unique venues | 349 | |
| | Year range | 2013–2025 | |
|
|
| ### Note Types |
|
|
| | Type | Count | % | |
| |------|-------|---| |
| | official_comment | 349,653 | 55.8% | |
| | official_review | 186,462 | 29.8% | |
| | decision | 31,450 | 5.0% | |
| | review | 28,616 | 4.6% | |
| | comment | 16,753 | 2.7% | |
| | meta_review | 13,496 | 2.2% | |
| |
| ### Top Venues |
| |
| | Venue | Count | |
| |-------|-------| |
| | ICLR 2025 | 198,960 | |
| | ICLR 2024 | 110,570 | |
| | NeurIPS 2024 | 75,555 | |
| | NeurIPS 2023 | 64,562 | |
| | EMNLP 2023 | 22,742 | |
| | NeurIPS 2022 | 16,278 | |
| | ICLR 2022 | 14,593 | |
| | NeurIPS 2021 | 13,605 | |
| | ICLR 2021 | 12,275 | |
| | ICLR 2019 | 11,916 | |
| |
| ### Year Distribution |
| |
| | Year | Count | |
| |------|-------| |
| | 2013 | 373 | |
| | 2014 | 651 | |
| | 2016 | 295 | |
| | 2017 | 626 | |
| | 2018 | 1,158 | |
| | 2019 | 14,284 | |
| | 2020 | 12,979 | |
| | 2021 | 35,943 | |
| | 2022 | 44,621 | |
| | 2023 | 96,525 | |
| | 2024 | 219,635 | |
| | 2025 | 199,340 | |
| |
| ### Note Text Length (characters) |
| |
| | Statistic | Value | |
| |-----------|-------| |
| | Mean | 2,268 | |
| | Median | 2,023 | |
| | Min | 10 | |
| | Max | 56,453 | |
| |
| ## Schema |
| |
| - **forum_id** — OpenReview forum identifier (one per paper) |
| - **forum_title** — Paper title |
| - **forum_authors** — List of paper authors |
| - **forum_abstract** — Paper abstract |
| - **forum_keywords** — Paper keywords |
| - **forum_pdf_url** — Link to PDF on OpenReview |
| - **forum_url** — Link to forum on OpenReview |
| - **note_id** — Unique identifier for this note (review/comment/decision) |
| - **note_type** — One of: `official_review`, `official_comment`, `decision`, `review`, `comment`, `meta_review` |
| - **note_created** — Unix timestamp (milliseconds) of note creation |
| - **note_replyto** — ID of the note this is replying to |
| - **note_readers** — List of reader groups with access |
| - **note_signatures** — List of note author signatures |
| - **venue** — Conference/venue identifier |
| - **year** — Publication year |
| - **note_text** — Full text content of the note |
| |
