Margin-calibrated classifier guidance via Sequence Completion Ranking raises multi-step retrosynthesis solve rates from 16.8% to 95.3% on USPTO-190 and unlocks previously unsolvable targets.
Retrogfn: Diverse and feasible retrosynthesis using gflownets
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2026 3verdicts
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MMORF provides a modular multi-agent framework for multi-objective retrosynthesis planning, with MASIL and RFAS systems showing strong safety, cost, and success metrics on a new 218-task benchmark.
RETROSPECT reports 55.00% top-1 and 86.18% top-10 accuracy on USPTO-50K with a ChemAlign Transformer plus LambdaMART reranker reaching 59.4% top-1 on candidate pools using proposal scores and template statistics.
citing papers explorer
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Margin-calibrated Classifier Guidance for Property-driven Synthesis Planning
Margin-calibrated classifier guidance via Sequence Completion Ranking raises multi-step retrosynthesis solve rates from 16.8% to 95.3% on USPTO-190 and unlocks previously unsolvable targets.
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MMORF: A Multi-agent Framework for Designing Multi-objective Retrosynthesis Planning Systems
MMORF provides a modular multi-agent framework for multi-objective retrosynthesis planning, with MASIL and RFAS systems showing strong safety, cost, and success metrics on a new 218-task benchmark.
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RETROSPECT: RETROsynthesis via Sequential Prediction, and Chemically Transformed-ranking
RETROSPECT reports 55.00% top-1 and 86.18% top-10 accuracy on USPTO-50K with a ChemAlign Transformer plus LambdaMART reranker reaching 59.4% top-1 on candidate pools using proposal scores and template statistics.