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Recently, computer-aided retrosynthesis is finding renewed interest from both chemistry and computer science communities. Most existing approaches rely on template-based models that define subgraph matching rules, but whether or not a chemical reaction can proceed is not defined by hard decision rules. In this work, we propose a new approach to this task using the Conditional Graph Logic Network, a conditional graphical model built upon graph neural networks that learns when rules from reaction templates should be applied, implicitly considering whether the resulting reaction would be both chemically feasible and strategic. We also propose an efficient hierarchical sampling to alleviate the computation cost. While achieving a significant improvement of $8.1\\%$ over current state-of-the-art methods on the benchmark dataset, our model also offers interpretations for the prediction.","url_abs":"https://arxiv.org/abs/2001.01408v1","url_pdf":"https://arxiv.org/pdf/2001.01408v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"retrosynthesis-prediction-with-conditional-1","repo_url":"https://github.com/Hanjun-Dai/GLN","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"prediction","task_name":"Prediction"},{"task_slug":"retrosynthesis","task_name":"Retrosynthesis"},{"task_slug":"single-step-retrosynthesis","task_name":"Single-step retrosynthesis"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/single-step-retrosynthesis-on-uspto-50k","task":"Single-step retrosynthesis","dataset":"USPTO-50k","model":"GLN","rank_in_archive_order":27,"of":35,"metrics":{"Top-1 accuracy":"52.5","Top-10 accuracy":"83.7","Top-20 accuracy":"89","Top-3 accuracy":"69","Top-5 accuracy":"75.6","Top-50 accuracy":"92.4"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2001.01408","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2001.01408"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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