DebiasRAG uses a three-stage RAG process to generate and rerank query-specific debiasing contexts that act as fairness constraints for LLM outputs.
arXiv preprint arXiv:2401.06775 , year=
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UNVERDICTED 3representative citing papers
A knowledge graph and LLM system for automating FDA regulatory compliance and classification of medical devices.
UniReason-Med introduces a unified framework for 2D and 3D medical VQA with shared grounded reasoning, trained on a 220K dataset, claiming that joint 2D+3D supervision improves 3D performance over 3D-only training.
citing papers explorer
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DebiasRAG: A Tuning-Free Path to Fair Generation in Large Language Models through Retrieval-Augmented Generation
DebiasRAG uses a three-stage RAG process to generate and rerank query-specific debiasing contexts that act as fairness constraints for LLM outputs.
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LLM based Knowledge Graph Approach to Automating Medical Device Regulatory Compliance
A knowledge graph and LLM system for automating FDA regulatory compliance and classification of medical devices.
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UniReason-Med: A Shared Grounded Reasoning Interface for 2D-to-3D Transfer in Medical VQA
UniReason-Med introduces a unified framework for 2D and 3D medical VQA with shared grounded reasoning, trained on a 220K dataset, claiming that joint 2D+3D supervision improves 3D performance over 3D-only training.