BWhat changed
Alternated centralized instruction tuning with separately optimized capability experts, parameter merging and polishing to integrate multilingual, retrieval and tool-use capabilities in Command A; documented an interleaved local/global attention implementation.
Scientific scope
Alternated centralized instruction tuning with separately optimized capability experts, parameter merging and polishing to integrate multilingual, retrieval and tool-use capabilities in Command A; documented an interleaved local/global attention implementation. Integration and training recipe, not invention of model soups, GQA, RoPE, NoPE, CoPG or SRPO. Expert tracks are merged parameter sets rather than token-routed MoE. Weights are non-commercial research releases; throughput and benchmark claims are not independently certified.
Evidence
The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Integration and training recipe, not invention of model soups, GQA, RoPE, NoPE, CoPG or SRPO. Expert tracks are merged parameter sets rather than token-routed MoE. Weights are non-commercial research releases; throughput and benchmark claims are not independently certified.
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.
- Command A: An Enterprise-Ready Large Language Model
- Cohere: decentralized expert-track post-training and model merging — 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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