The public summary of the draft says the amendment adds an entry on transformer architecture and algorithm at 6.5.3.2.9. It describes encoder-decoder structures and self-attention, and explains that the architecture allows a high degree of parallel processing in training and deployment of large language models. It distinguishes encoder-only models, used for representation and embeddings, from decoder-only models, used for generative tasks such as summarisation and question answering. The final wording is not held and this page does not reproduce it. What the public record establishes is narrower and still useful: the framework now has a place to describe a transformer, and that place separates the two ways the family is used.
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