arXiv：cs.AI· Ye Rin Kim, Yongjun Jeong, Seongjun Yun, Hanbum Ko, Soohyun Oh, Sungbin Lim, Sungwoong Kim·· 16 小时前
RetroPlanner：面向 LLM 逆合成规划的多路线扩展与多目标推理
RetroPlanner: Multi-Route Expansion and Multi-Objective Reasoning for LLM-Based Retrosynthesis Planning
AI 导读
LLM 逆合成规划器 RetroPlanner 通过同时比较多条路线，将搜索导向反应合理性、往返一致性和起始原料价格综合更优的方向，而非只优化单条路线的可解性。在多步逆合成基准上，它比此前的 LLM 规划器找回更多备选路线，同时提升路线质量并保持高成功率。
正文
Abstract:Multi-step retrosynthesis planning is often considered solved once a route to purchasable starting materials is found, but such a route should also be practical in real-world chemistry. Recent LLM-based planners formulate this process as sequential decision-making over an AND-OR graph, yet typically expand a single molecule per turn and are optimized for solvability alone, leaving alternative routes uncompared across the multiple objectives that determine practicality before the search budget is committed. We introduce RetroPlanner, an LLM-based planner that jointly compares multiple routes to steer the search toward higher synthesizability, as measured by reaction plausibility, round-trip consistency, and starting-material price. RetroPlanner is trained to reason over chemical evidence: structural progress from the target molecule, bond changes and reaction classes, where candidate routes diverge from one another, and how they rank across multiple objectives. Experiments on multi-step retrosynthesis benchmarks demonstrate that RetroPlanner recovers more alternative routes than prior LLM-based planners while improving synthetic route quality and maintaining a high success rate.
| Subjects: | Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Machine Learning (cs.LG) |
| Cite as: | arXiv:2610.16391 [cs.AI] |
| (or arXiv:2610.16391v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2610.16391 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Yerin Kim [view email]
[v1]
Mon, 12 Oct 2026 08:37:43 UTC (989 KB)
来源：arXiv：cs.AI · arxiv.org