This research introduces a novel retrieval model that enhances LLM capabilities in knowledge-intensive domains by incorporating causal relationships rather than just semantic matching.

• Addresses critical limitations in current retrieval systems for medical, legal, and security applications
• Proposes a new approach that considers causal connections between queries and relevant documents
• Improves accuracy in domains where precision is essential, such as biomedical question answering
• Enables more reliable and trustworthy AI responses in specialized knowledge areas

For medical applications, this advancement means more accurate information retrieval for clinical decision support, research analysis, and patient-facing AI systems—ultimately improving healthcare outcomes through more reliable AI assistance.

Causal Retrieval with Semantic Consideration