RAD3D-Prefix is a diagnostic-prior conditioning framework for 3D CT report generation that integrates image embeddings with multi-label classification logits, showing that freezing larger LLMs and training only projection layers outperforms fine-tuning across scales.
Ct-agrg: Automated abnormality-guided report generation from 3d chest ct volumes.arXiv preprint arXiv:2408.11965, 2024
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Revisiting LLM Adaptation for 3D CT Report Generation: A Study of Scaling and Diagnostic Priors
RAD3D-Prefix is a diagnostic-prior conditioning framework for 3D CT report generation that integrates image embeddings with multi-label classification logits, showing that freezing larger LLMs and training only projection layers outperforms fine-tuning across scales.