UltraInteract SFT: Large-Scale Alignment Data for Complex Reasoning

UltraInteract SFT is a large-scale, high-quality alignment dataset designed for complex reasoning tasks. The dataset, created by openbmb, includes preference trees with reasoning chains, multi-turn interaction trajectories, and pairwise data for preference learning. It was last updated on April 5,我们发现了一个问题，在生成 summary 时，我使用了

Use Cases

• Training models for complex reasoning based on the diverse planning strategies mentioned in the description
• Fine-tuning language models for multi-turn interaction based on the described interaction trajectories with environment and critique
• Conducting preference learning experiments based on the included pairwise data

Strengths

• Designed specifically for complex reasoning tasks, indicating a targeted application
• Includes a preference tree structure with multiple reasoning components as described
• Last updated on 2024-04-05 14:29:52, suggesting recent maintenance

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 is unknown, which may limit suitability assessment

Provenance

Source

openbmb

Collection Method

Likely constructed for alignment and instruction tuning, as described.

Time Range

null

Freshness

Last updated 2024-04-05 14:29:52

Geography

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