{"slug": "fine-tuning-a-multimodal-large-language-model-for-clinician-grade-autism-scoring", "title": "Fine-tuning a multimodal large language model for clinician-grade autism behavioral scoring from short home videos", "summary": "Researchers fine-tuned Gemini 2.5 Pro on 400 clinician-rated home videos to score 30 behavioral features for autism assessment, improving inter-rater reliability with clinicians by 40% and boosting zero-shot ASD diagnosis F1 by 53%. The model achieved 77% accuracy and 86% AUC on held-out children, matching or exceeding clinician performance, suggesting scalable autism screening from short home videos.", "body_md": "arXiv:2606.27484v1 Announce Type: new\nAbstract: Autism spectrum disorder (ASD) affects 1 in 31 US children, yet median age at diagnosis exceeds four years. Artificial intelligence pipelines that provide quantified diagnosis using easy to access observational data (e.g., home videos) could help with earlier diagnosis, and timely delivery of early treatments. We fine-tuned Gemini 2.5 Pro on 400 clinician-rated home videos with low-rank adaptation, training only on 30 behavioral features previously validated to produce reliable predictions when passed to various ML models. On 99 held-out children (49 ASD, 50 neurotypical), inter-rater reliability with clinicians (per-feature weighted Cohen's kappa) improved by 40% (p<0.001), with 27 of 28 evaluable features improving. As an emergent zero-shot capability, direct ASD diagnosis F1 improved by 53% (p<0.001), matching or exceeding clinician outcomes. Classifier-assisted pipelines using fine-tuned LLM-derived behavioral features matched clinician-scored inputs across all tested pathways and achieved 77% accuracy (95% CI: 68-85%) and an AUC of 86% (95% CI: 78-92%). Fine-tuned multimodal LLMs can serve as scalable behavioral feature extractors for use in autism assessment and diagnosis.", "url": "https://wpnews.pro/news/fine-tuning-a-multimodal-large-language-model-for-clinician-grade-autism-scoring", "canonical_source": "https://arxiv.org/abs/2606.27484", "published_at": "2026-06-29 04:00:00+00:00", "updated_at": "2026-06-29 04:02:26.816137+00:00", "lang": "en", "topics": ["large-language-models", "computer-vision", "ai-research", "ai-products"], "entities": ["Gemini 2.5 Pro", "ASD", "autism spectrum disorder"], "alternates": {"html": "https://wpnews.pro/news/fine-tuning-a-multimodal-large-language-model-for-clinician-grade-autism-scoring", "markdown": "https://wpnews.pro/news/fine-tuning-a-multimodal-large-language-model-for-clinician-grade-autism-scoring.md", "text": "https://wpnews.pro/news/fine-tuning-a-multimodal-large-language-model-for-clinician-grade-autism-scoring.txt", "jsonld": "https://wpnews.pro/news/fine-tuning-a-multimodal-large-language-model-for-clinician-grade-autism-scoring.jsonld"}}