Initial commit: Add NeurIPS papers dataset with reviews and rebuttals

.gitattributes

@@ -0,0 +1 @@
+*.csv filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,80 @@
+---
+license: mit
+---
+
+# NeurIPS Papers Dataset
+
+This dataset contains information about NeurIPS conference paper submissions including peer reviews, author rebuttals, and decision outcomes across multiple years.
+
+## Files
+
+- `merged_neurips_dataset.csv`: Main dataset file containing all paper submission data
+
+## Dataset Structure
+
+The CSV file contains the following columns:
+
+- `title`: Paper title
+- `paper_decision`: Decision outcome (Accept/Reject with specific categories)
+- `review_1`, `review_2`, etc.: Peer reviews from different reviewers
+- `rebuttals_1`, `rebuttals_2`, etc.: Author rebuttals responding to reviews
+- `global_rebuttals`: Overall author responses
+- `dataset_source`: Source of the data
+- `conference_year`: Year of the conference
+
+## Usage
+
+```python
+import pandas as pd
+
+# Load the dataset
+df = pd.read_csv('merged_neurips_dataset.csv')
+
+# Example: Print first paper title
+print(df['title'].iloc[0])
+
+# Example: Filter accepted papers
+accepted_papers = df[df['paper_decision'].str.contains('Accept', na=False)]
+print(f"Number of accepted papers: {len(accepted_papers)}")
+
+# Example: Analyze decision distribution
+decision_counts = df['paper_decision'].value_counts()
+print(decision_counts)
+```
+
+## Sample Data Structure
+
+Each row represents a paper submission with associated reviews and rebuttals:
+
+```
+title: "Stress-Testing Capability Elicitation With Password-Locked Models"
+paper_decision: "Accept (poster)"
+review_1: "Summary: The paper studies whether fine-tuning can elicit..."
+rebuttals_1: "Rebuttal 1: Thanks for the review! We are glad you found..."
+...
+```
+
+## Data Statistics
+
+- **File size**: ~287MB
+- **Format**: CSV with comma-separated values
+- **Encoding**: UTF-8
+- **Contains**: Paper reviews, rebuttals, and metadata from NeurIPS conferences
+
+## Use Cases
+
+This dataset is valuable for:
+
+- **Peer review analysis**: Study patterns in academic peer review
+- **Natural language processing**: Train models on academic text
+- **Research evaluation**: Analyze correlation between reviews and acceptance
+- **Academic writing**: Understand successful paper characteristics
+- **Sentiment analysis**: Analyze reviewer sentiment and author responses
+
+## Citation
+
+If you use this dataset in your research, please cite appropriately and ensure compliance with NeurIPS terms of service.
+
+## License
+
+This dataset is released under the MIT License. Please ensure you have appropriate permissions to use this data and comply with NeurIPS's terms of service.

merged_neurips_dataset.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c79db0ab18e6e6b490f739632d27edcd76e195f5430b28cbc57be592687a4c19
+size 300768926