{"slug": "improving-molecular-property-prediction-in-small-language-models-using-graph", "title": "Improving Molecular Property Prediction in Small Language Models Using Graph-based Tools", "summary": "Researchers propose a Context-Augmented Prompting framework that uses graph neural network tools to improve molecular property prediction in small language models. The method yields accuracy gains of up to 74% on Tox21 and over 25% on MUTAG, though a gap remains compared to specialized GNN models.", "body_md": "arXiv:2607.13115v1 Announce Type: new\nAbstract: Small language models (SLMs) have shown promise for zero-shot molecular property prediction from SMILES strings, yet they often suffer from structural blindness because sequence representations under-specify key graph-topological cues. We propose a modular Context-Augmented Prompting framework that enables agentic tool use at inference time: a trained GNN expert model provides a predictive hint with confidence, and a GNN extracts an instance-specific explanatory subgraph (e.g., a subgraph SMILES and an accompanying explanatory paragraph). We evaluate three commonly used SLMs on MUTAG and Tox21 under five prompting configurations ranging from SMILES-only to using all available tools at hand. Across two datasets, enriching prompts with graph-derived context yields substantial accuracy gains, often exceeding 25% relative improvement and up to 74% on Tox21. We further validate the functional relevance of the extracted motifs via a necessity-based edge-drop intervention. Despite the observed gains, a persistent gap remains to specialized GNN models, highlighting both the value and limits of text-conditioned reasoning for molecular structure.", "url": "https://wpnews.pro/news/improving-molecular-property-prediction-in-small-language-models-using-graph", "canonical_source": "https://arxiv.org/abs/2607.13115", "published_at": "2026-07-16 04:00:00+00:00", "updated_at": "2026-07-16 04:30:45.389869+00:00", "lang": "en", "topics": ["artificial-intelligence", "machine-learning", "large-language-models", "ai-research"], "entities": ["MUTAG", "Tox21"], "alternates": {"html": "https://wpnews.pro/news/improving-molecular-property-prediction-in-small-language-models-using-graph", "markdown": "https://wpnews.pro/news/improving-molecular-property-prediction-in-small-language-models-using-graph.md", "text": "https://wpnews.pro/news/improving-molecular-property-prediction-in-small-language-models-using-graph.txt", "jsonld": "https://wpnews.pro/news/improving-molecular-property-prediction-in-small-language-models-using-graph.jsonld"}}