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Ariadne is a decoder-only route generator for retrosynthetic planning that frames the target, optional constraints, and route as a prompt-completion sequence, achieving superior performance with much less computation compared to traditional search-based planners.
This paper presents ConRetroBert, a dual encoder framework for template-based single-step retrosynthesis that uses contrastive pretraining and listwise ranking to improve template prediction accuracy, achieving up to 75.4% top-1 accuracy on the USPTO-50k benchmark while maintaining interpretability.
EPFL researchers developed Synthegy, an AI framework that uses large language models to guide chemical retrosynthesis and reaction mechanism analysis through natural language instructions, significantly improving strategic planning for chemists.