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Dynamic language model representations for multi-objective reaction optimisation
Optimising chemical reactions across multiple objectives, such as yield, selectivity, and safety, is central to chemical synthesis, and model-driven approaches depend critically on how reaction components are represented. Established featurisations are either chemically uninformative, as with one-hot encodings, or, as with molecular descriptors, do not readily extend across chemically distinct components. For structurally and functionally diverse components, it is therefore unclear what a shared representation should contain. Constructing such a representation is itself a challenging research
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-10T16:43:08.000Z
First collected: 2026-09-20T19:02:05.452Z. This is not the publication date.