BWhat changed
Combined a human-maintained task/knowledge taxonomy, teacher-generated instructions with quality filtering and multi-phase tuning to add skills and knowledge to pretrained chat models; powered the collaborative InstructLab workflow.
Scientific scope
Combined a human-maintained task/knowledge taxonomy, teacher-generated instructions with quality filtering and multi-phase tuning to add skills and knowledge to pretrained chat models; powered the collaborative InstructLab workflow. Synthetic instruction generation, teacher models and progressive training have predecessors explicitly discussed in the report. The contribution is the taxonomy-guided generation/training integration, not invention of synthetic data or a universal guarantee against forgetting.
Evidence
The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Synthetic instruction generation, teacher models and progressive training have predecessors explicitly discussed in the report. The contribution is the taxonomy-guided generation/training integration, not invention of synthetic data or a universal guarantee against forgetting.
Contributors
- Source-listed authors and technical contributors · SCIENCE: Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
- LAB: Large-Scale Alignment for ChatBots
- Sudalairaj et al.: taxonomy-guided LAB synthetic instruction alignment — official research provenance
Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.
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