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Proceedings of the AAAI Conference on Artificial Intelligence

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RTMol: Rethinking Molecule-text Alignment in a Round-trip...
Letian Chen, · 2026-03-14 · via Proceedings of the AAAI Conference on Artificial Intelligence

Authors

  • Letian Chen Shanghai Innovation Institute Shanghai Jiao Tong University
  • Runhan Shi Shanghai Jiao Tong University
  • Gufeng Yu Shanghai Jiao Tong University
  • Yang Yang Shanghai Jiao Tong University

DOI:

https://doi.org/10.1609/aaai.v40i1.36966

Abstract

Aligning molecular sequence representations (e.g., SMILES notations) with textual descriptions is critical for applications spanning drug discovery, materials design, and automated chemical literature analysis. Existing methodologies typically treat molecular captioning (molecule-to-text) and text-based molecular design (text-to-molecule) as separate tasks, relying on supervised fine-tuning or contrastive learning pipelines. These approaches face three key limitations: (i) conventional metrics like BLEU prioritize linguistic fluency over chemical accuracy, (ii) training datasets frequently contain chemically ambiguous narratives with incomplete specifications, and (iii) independent optimization of generation directions leads to bidirectional inconsistency. To address these issues, we propose RTMol, a bidirectional alignment framework that unifies molecular captioning and text-to-SMILES generation through self-supervised round-trip learning. The framework introduces novel round-trip evaluation metrics and enables unsupervised training for molecular captioning without requiring paired molecule-text corpora. Experiments demonstrate that RTMol enhances bidirectional alignment performance by up to 47% across various LLMs, establishing an effective paradigm for joint molecule-text understanding and generation.

How to Cite

Chen, L., Shi, R., Yu, G., & Yang, Y. (2026). RTMol: Rethinking Molecule-text Alignment in a Round-trip View. Proceedings of the AAAI Conference on Artificial Intelligence, 40(1), 75–82. https://doi.org/10.1609/aaai.v40i1.36966

Issue

Section

AAAI Technical Track on Application Domains I

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