10,000 recent papers on machine learning and deep learning, including abstracts. The dataset covers publications from 2020 to 2026. The original author and organization are unknown.
Use Cases
- Analyze research trends in machine learning based on paper abstracts
- Train NLP models for scientific text classification based on paper abstracts
- Perform keyword extraction or topic modeling on AI research literature
Strengths
- 10,000 papers provide a substantial corpus for analysis
- Includes abstracts, which provide textual content for NLP tasks
- Covers a recent time range from 2020 to 2026
Limitations
- Column-level documentation is absent; field semantics must be inferred after download
- Row count is unknown, which may limit suitability assessment
- Data may reflect temporal or source bias inherent to Kaggle
Provenance
- Time Range
- 2020-2026