|
|
--- |
|
|
dataset_info: |
|
|
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|
features: |
|
|
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|
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|
|
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|
|
dataset_size: 6852636 |
|
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|
|
features: |
|
|
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|
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|
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|
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- config_name: combined_main_aspects |
|
|
features: |
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- name: grounding_specificity |
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struct: |
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struct: |
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struct: |
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splits: |
|
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|
|
download_size: 1682108 |
|
|
dataset_size: 3854198 |
|
|
- config_name: context_experiment_with_paper_text |
|
|
features: |
|
|
- name: review_point |
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dtype: string |
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|
- name: paper_word_count |
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dtype: string |
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splits: |
|
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num_examples: 100 |
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download_size: 1842203 |
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- config_name: professional_tone |
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struct: |
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sequence: string |
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dtype: string |
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dtype: string |
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download_size: 3316675 |
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dataset_size: 6806370 |
|
|
- config_name: valid_point |
|
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features: |
|
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- name: review_point |
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dtype: string |
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dtype: string |
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- name: batch |
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dtype: int64 |
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|
- name: valid_point |
|
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struct: |
|
|
- name: annotators |
|
|
sequence: string |
|
|
- name: labels |
|
|
sequence: string |
|
|
- name: valid_point_label |
|
|
dtype: string |
|
|
- name: valid_point_label_type |
|
|
dtype: string |
|
|
- name: id |
|
|
dtype: int64 |
|
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splits: |
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num_examples: 198 |
|
|
- name: full |
|
|
num_bytes: 3273727 |
|
|
num_examples: 1382 |
|
|
download_size: 3214375 |
|
|
dataset_size: 6547454 |
|
|
- config_name: verifiability |
|
|
features: |
|
|
- name: review_point |
|
|
dtype: string |
|
|
- name: paper_id |
|
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dtype: string |
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- name: venue |
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- name: focused_review |
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dtype: string |
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- name: batch |
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dtype: int64 |
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- name: verifiability |
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struct: |
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- name: annotators |
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sequence: string |
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- name: labels |
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sequence: string |
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- name: verifiability_label |
|
|
dtype: string |
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- name: verifiability_label_type |
|
|
dtype: string |
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|
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dtype: int64 |
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|
|
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|
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- name: hard |
|
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num_examples: 407 |
|
|
- name: full |
|
|
num_bytes: 3420708 |
|
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num_examples: 1430 |
|
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download_size: 3367607 |
|
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dataset_size: 6841416 |
|
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configs: |
|
|
- config_name: actionability |
|
|
data_files: |
|
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- split: gold |
|
|
path: actionability/gold-* |
|
|
- split: silver |
|
|
path: actionability/silver-* |
|
|
- split: hard |
|
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path: actionability/hard-* |
|
|
- split: full |
|
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path: actionability/full-* |
|
|
- config_name: addressed_to_author |
|
|
data_files: |
|
|
- split: gold |
|
|
path: addressed_to_author/gold-* |
|
|
- split: silver |
|
|
path: addressed_to_author/silver-* |
|
|
- split: full |
|
|
path: addressed_to_author/full-* |
|
|
- config_name: combined_main_aspects |
|
|
data_files: |
|
|
- split: full |
|
|
path: combined_main_aspects/full-* |
|
|
- config_name: context_experiment_with_paper_text |
|
|
data_files: |
|
|
- split: full |
|
|
path: context_experiment_with_paper_text/full-* |
|
|
- config_name: grounding_specificity |
|
|
data_files: |
|
|
- split: gold |
|
|
path: grounding_specificity/gold-* |
|
|
- split: silver |
|
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path: grounding_specificity/silver-* |
|
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- split: hard |
|
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path: grounding_specificity/hard-* |
|
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- split: full |
|
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path: grounding_specificity/full-* |
|
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- config_name: helpfulness |
|
|
data_files: |
|
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- split: gold |
|
|
path: helpfulness/gold-* |
|
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- split: silver |
|
|
path: helpfulness/silver-* |
|
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- split: hard |
|
|
path: helpfulness/hard-* |
|
|
- split: full |
|
|
path: helpfulness/full-* |
|
|
- config_name: professional_tone |
|
|
data_files: |
|
|
- split: gold |
|
|
path: professional_tone/gold-* |
|
|
- split: silver |
|
|
path: professional_tone/silver-* |
|
|
- split: full |
|
|
path: professional_tone/full-* |
|
|
- config_name: valid_point |
|
|
data_files: |
|
|
- split: gold |
|
|
path: valid_point/gold-* |
|
|
- split: silver |
|
|
path: valid_point/silver-* |
|
|
- split: full |
|
|
path: valid_point/full-* |
|
|
- config_name: verifiability |
|
|
data_files: |
|
|
- split: gold |
|
|
path: verifiability/gold-* |
|
|
- split: silver |
|
|
path: verifiability/silver-* |
|
|
- split: hard |
|
|
path: verifiability/hard-* |
|
|
- split: full |
|
|
path: verifiability/full-* |
|
|
license: cc-by-nc-sa-4.0 |
|
|
task_categories: |
|
|
- text-classification |
|
|
language: |
|
|
- en |
|
|
size_categories: |
|
|
- 1K<n<10K |
|
|
--- |
|
|
|
|
|
|
|
|
# RevUtil: Measuring the Utility of Peer Reviews for Authors |
|
|
|
|
|
[📄 Paper](https://aclanthology.org/2025.emnlp-main.1476/) |
|
|
[💻 GitHub Repository](https://github.com/bodasadallah/RevUtil) |
|
|
|
|
|
--- |
|
|
|
|
|
## 📚 Overview |
|
|
|
|
|
Providing **constructive feedback** to authors is a key goal of peer review. To support research on evaluating and generating useful peer review comments, we introduce **RevUtil**, a dataset for measuring the utility of peer review feedback. |
|
|
|
|
|
RevUtil focuses on four main aspects of review comments: |
|
|
|
|
|
- **Actionability** – Can the author act on the comment? |
|
|
- **Grounding & Specificity** – Is the comment concrete and tied to the paper? |
|
|
- **Verifiability** – Can the statement be checked against the paper? |
|
|
- **Helpfulness** – Does the comment assist the author in improving their work? |
|
|
|
|
|
--- |
|
|
|
|
|
## 🧑🔬 RevUtil Human |
|
|
|
|
|
- **1,430** review comments from real peer reviews. |
|
|
- Each comment is annotated independently by **three human raters**. |
|
|
- Labels are provided as `"gold"` (3/3 agreement), `"silver"` (2/3), or `"none"` (no agreement). |
|
|
|
|
|
**Key columns:** |
|
|
|
|
|
| Column | Description | |
|
|
| ------------------- | --------------------------------------------------------------------------- | |
|
|
| `paper_id` | ID of the reviewed paper | |
|
|
| `venue` | Conference or journal name | |
|
|
| `focused_review` | Full review (weakness + suggestion sections) | |
|
|
| `review_point` | Individual review comment being evaluated | |
|
|
| `id` | Unique ID for the review point | |
|
|
| `batch` | Annotation batch/study identifier | |
|
|
| `ASPECT` | Dictionary with annotators and their labels | |
|
|
| `ASPECT_label` | Majority label (if available) | |
|
|
| `ASPECT_label_type` | `"gold"`, `"silver"`, or `"none"` | |
|
|
|
|
|
--- |
|
|
|
|
|
## 🚀 Usage |
|
|
|
|
|
You can load the datasets directly via 🤗 Datasets: |
|
|
|
|
|
```python |
|
|
from datasets import load_dataset |
|
|
|
|
|
# Human annotations |
|
|
human = load_dataset("boda/RevUtil_human") |
|
|
|
|
|
# Synthetic annotations |
|
|
synthetic = load_dataset("boda/RevUtil_synthetic") |
|
|
``` |
|
|
|
|
|
|
|
|
|
|
|
## 📎 Citation |
|
|
``` |
|
|
@inproceedings{sadallah-etal-2025-good, |
|
|
title = "The Good, the Bad and the Constructive: Automatically Measuring Peer Review{'}s Utility for Authors", |
|
|
author = {Sadallah, Abdelrahman and |
|
|
Baumg{\"a}rtner, Tim and |
|
|
Gurevych, Iryna and |
|
|
Briscoe, Ted}, |
|
|
editor = "Christodoulopoulos, Christos and |
|
|
Chakraborty, Tanmoy and |
|
|
Rose, Carolyn and |
|
|
Peng, Violet", |
|
|
booktitle = "Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing", |
|
|
month = nov, |
|
|
year = "2025", |
|
|
address = "Suzhou, China", |
|
|
publisher = "Association for Computational Linguistics", |
|
|
url = "https://aclanthology.org/2025.emnlp-main.1476/", |
|
|
doi = "10.18653/v1/2025.emnlp-main.1476", |
|
|
pages = "28979--29009", |
|
|
ISBN = "979-8-89176-332-6" |
|
|
} |
|
|
``` |
