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URSA: Chemistry-Aware Benchmark for Utilitarian Retrosynthesis Assessment

NeurIPS 2026 · Large language models › Agents, code and math · approach: LLMs for scientific discovery · 0 citations (OpenAlex)

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Introduces URSA, a route-level benchmark that scores stock-terminated retrosynthetic routes for chemical plausibility (Solv-0/1/2) using ChemCensor, and benchmarks conventional CASP tools and frontier/open LLMs on expert and drug target sets.

Problem

Standard retrosynthesis evaluation relies on solvability (reaching purchasable starting materials), which does not ensure that each reaction step is chemically plausible; existing benchmarks such as USPTO-190 are also weakly representative of prospective medicinal chemistry.

Approach

A route-level validity protocol that combines stock termination, structural/topological checks, and step-wise ChemCensor precedent-based plausibility scoring (Solv-2), applied uniformly to heterogeneous CASP tools and LLM planners, with a new expert-derived reaction plausibility benchmark used to justify ChemCensor over LLM judges.

Key results

Surprising findings

Limitations

Experimental setup

Datasets: USPTO-full Pistachio 2023Q4 Enamine building blocks ASKCOS buyables eMolecules building blocks URSA-expert-2026 URSA-drugs&clinicals-2026 USPTO-190

Benchmarks: URSA-expert-2026 URSA-drugs&clinicals-2026 USPTO-190 URSA-reaction-plausibility-bench-2026

Metrics: accuracy MCC Solv-0 Solv-1 Solv-2 CC*

Baselines: Retro* DirectMultiStep ASKCOS AiZynthFinder RetroChimera SynPlanner DreamRetroer TTLA SynLlama Gemini 3.1 Pro GPT 5.5 Claude Opus 4.8

Builds on: ChemCensor RetroCast Syntheseus PaRoutes USPTO-190

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