4 papers
Learning the Koopman Operator using Attention Free Transformers
Mohammed Nagdi, Evangelos-Marios Nikolados, Alexey Yermakov +3
Learning Koopman operators with autoencoders enables linear prediction in a latent space, but long-horizon rollouts often drift off the learned manifold, leading to phase and ampli…
Reinforcement Learning for Clinical Reasoning: Aligning LLMs with ACR Imaging Appropriateness Criteria
Anni Tziakouri, Filippo Menolascina
Medical imaging has revolutionized diagnosis, yet unnecessary procedures are rising, exposing patients to radiation and stress, limiting equitable access, and straining healthcare…
Bridging Clinical Narratives and ACR Appropriateness Guidelines: A Multi-Agent RAG System for Medical Imaging Decisions
Satrio Pambudi, Filippo Menolascina
The selection of appropriate medical imaging procedures is a critical and complex clinical decision, guided by extensive evidence-based standards such as the ACR Appropriateness Cr…
ModernBERT + ColBERT: Enhancing biomedical RAG through an advanced re-ranking retriever
Eduardo MartÃnez Rivera, Filippo Menolascina
Retrieval-Augmented Generation (RAG) is a powerful technique for enriching Large Language Models (LLMs) with external knowledge, allowing for factually grounded responses, a critic…