Mol-Debate: Multi-Agent Debate Improves Structural Reasoning in Molecular Design

• URL: http://arxiv.org/abs/2604.20254v1
• Date: Wed, 22 Apr 2026 07:03:25 GMT
• Title: Mol-Debate: Multi-Agent Debate Improves Structural Reasoning in Molecular Design
• Abstract summary: Mol-Debate is a generation paradigm that enables dynamic reasoning through an iterative generate-debate-refine loop.<n> Experiments demonstrate that Mol-Debate achieves state-of-the-art performance against strong general and chemical baselines.
• Score: 13.985773177895476
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Text-guided molecular design is a key capability for AI-driven drug discovery, yet it remains challenging to map sequential natural-language instructions with non-linear molecular structures under strict chemical constraints. Most existing approaches, including RAG, CoT prompting, and fine-tuning or RL, emphasize a small set of ad-hoc reasoning perspectives implemented in a largely one-shot generation pipeline. In contrast, real-world drug discovery relies on dynamic, multi-perspective critique and iterative refinement to reconcile semantic intent with structural feasibility. Motivated by this, we propose Mol-Debate, a generation paradigm that enables such dynamic reasoning through an iterative generate-debate-refine loop. We further characterize key challenges in this paradigm and address them through perspective-oriented orchestration, including developer-debater conflict, global-local structural reasoning, and static-dynamic integration. Experiments demonstrate that Mol-Debate achieves state-of-the-art performance against strong general and chemical baselines, reaching 59.82% exact match on ChEBI-20 and 50.52% weighted success rate on S$^2$-Bench. Our code is available at https://github.com/wyuzh/Mol-Debate.

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