ReasonIR: Synthetic Examples for Training the ReasonIR-8B Model

Synthetic examples used to train the ReasonIR-8B model, as described in a paper from April 2025. The dataset is hosted by the 'reasonir' author on Hugging Face and was last updated on 2025-05-07. It includes varied-length data, with a processing script provided to download and merge original documents.

Use Cases

• Training information retrieval models based on synthetic query-document examples.
• Benchmarking model reasoning performance based on the described varied-length data.
• Studying the effectiveness of synthetic data for model training as referenced in the associated paper.

Strengths

• Associated with a specific, named model (ReasonIR-8B) and a research paper from April 2025.
• Provides a data processing script to reconstruct the full dataset, indicating a reproducible methodology.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count and file formats are unknown, which may limit suitability assessment.

Provenance

Source

reasonir (likely associated with Facebook Research, based on the linked GitHub repository).

Collection Method

Synthetically generated for model training.

Freshness

Last updated 2025-05-07 11:17:46; freshness should be verified.