DeepReviewer-13K captures a human-like deep thinking process for peer review. The dataset contains structured annotations and intermediate reasoning steps, curated by WestlakeNLP. It was last updated on March 18, 2025.
Use Cases
- Train LLMs for generating academic reviews based on structured annotations.
- Benchmark automated review systems based on intermediate reasoning steps.
- Study the structure of peer review feedback based on the dataset's curated format.
Strengths
- Dataset is curated specifically for LLM training in academic review.
- Contains structured annotations and intermediate reasoning steps.
- Last updated on March 18, 2025.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- Description metadata is limited; actual data quality requires manual inspection after download.
Provenance
- Source
- WestlakeNLP
- Freshness
- Last updated 2025-03-18 18:00:51