{"ID":2896789,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2507.07328","arxiv_id":"2507.07328","title":"Bridging the Plausibility-Validity Gap by Fine-Tuning a Reasoning-Enhanced LLM for Chemical Synthesis and Discovery","abstract":"Large Language Models frequently generate outputs that appear scientifically reasonable yet violate fundamental principles--a phenomenon we characterize as the \"plausibility-validity gap.\" This challenge proves especially acute in chemistry, where superficial correctness masks deeper errors in molecular structure, reaction mechanisms, and synthetic pathways. We present a systematic approach combining a reasoning-centric model architecture (Magistral Small) with Low-Rank Adaptation fine-tuning on a dual-domain dataset covering molecular properties and chemical transformations. Evaluation reveals substantial improvements: the fine-tuned system achieves 96.3% format adherence, 97.4% chemical validity, and 74.4% synthesis feasibility. Comparative analysis shows our approach outperforms specialized translation models like MolT5 (97.4% vs 77.2% validity) while achieving performance comparable to complex tool-augmented systems like ChemCrow (9.0/10 vs 9.24/10 expert rating) through a more transparent, efficient methodology. Results demonstrate a learning hierarchy where syntactic correctness develops before chemical understanding, which precedes synthetic planning capability. This work establishes a reproducible framework for transforming generalist language models into dependable scientific tools while identifying critical areas including stereochemical precision, knowledge currency, and computational accessibility as key challenges for future advancement.","short_abstract":"Large Language Models frequently generate outputs that appear scientifically reasonable yet violate fundamental principles--a phenomenon we characterize as the \"plausibility-validity gap.\" This challenge proves especially acute in chemistry, where superficial correctness masks deeper errors in molecular structure, reac...","url_abs":"https://arxiv.org/abs/2507.07328","url_pdf":"https://arxiv.org/pdf/2507.07328v2","authors":"[\"Malikussaid\",\"Hilal Hudan Nuha\",\"Isman Kurniawan\"]","published":"2025-07-09T23:05:23Z","proceeding":"cs.LG","tasks":"[\"cs.LG\",\"cs.AI\",\"cs.CE\",\"physics.chem-ph\"]","methods":"[\"Large Language Model\",\"Language Model\"]","has_code":false}