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arxiv:2610.20459

MolLean: A Process-Verifiable Language for Chemical Reasoning

Published on Oct 14
· Submitted by
Jiatong LI
on Oct 23
Authors:

Abstract

MolLean introduces a verifiable chemical reasoning framework with explicit molecular states, Lean-based verification, and interactive tool feedback to reduce hallucinations across generation and reaction tasks.

Chemical chain-of-thought can contain hallucinated structural and property claims. We thereby introduce MolLean, a process-verifiable language that grounds chemical reasoning in an explicit molecular state. A layered Lean-based kernel checks state transitions and assertions over molecular readouts, from primitive graph edits to compound transformations. Meanwhile, a typed witness protocol separates native structural checks from externally supplied measurements. We further introduce MolLean-MCP, a stateful tool interface that exposes these transitions, checks, and readouts during generation: the model receives feedback to decide its next action, and rejected actions leave the state unchanged. MolLean supports one-pass trace execution, whole-trace refinement, and interactive reasoning through MolLean-MCP. We evaluate these three modes with direct chain-of-thought on 8,800 matched examples across 12 tasks spanning molecular generation, editing, optimization, and reactions. With Qwen3.6-27B, whole-trace refinement outperforms direct chain-of-thought on all 12 tasks. MolLean-MCP complements whole-trace refinement with stepwise verification feedback, reaching better performance in reaction tasks. Together, these results highlight an executable foundation for chemical reasoning, in which explicit chemical commitments can be checked and revised rather than remaining solely in free-form explanations.

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MolLean turns chemical reasoning into executable, checked steps. Direct chain-of-thought can miscount atoms, invent functional groups, or claim a property improved without measuring it. MolLean ties declared edits and claims to an explicit molecular state.

The video illustrates four examples from the paper: ethanol-to-1-propanol editing, an exact 25-carbon constraint, QED optimization with measured feedback, and an interactive MolLean-MCP episode where a rejected phenyl attachment leaves the molecule unchanged and guides the next successful action.

Across 8,800 matched examples covering 12 chemical task types, whole-trace refinement improves over direct CoT on all 12 with Qwen3.6-27B.

Paper: https://arxiv.org/abs/2610.20459
Project preview: https://github.com/phenixace/Open-MolLean
Code release is planned.

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