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Jinyuan Fang · Zaiqiao Meng · Craig Macdonald
Adaptive retrieval-augmented generation (RAG) models offer an effective approach for integrating external knowledge. However, existing methods either rely on frozen large language models (LLMs) without explicit supervision or require costly LLM finetuning. Therefore, we propose SPARKLE, a structu...
Meiru Zhang · Zaiqiao Meng · Nigel Collier
Despite scaling to massive context windows, Large Language Models (LLMs) struggle with multi-hop reasoning due to inherent position bias, which causes them to overlook information at certain positions. Whether these failures stem from an inability to locate evidence (recognition failure) or integ...
Xi Zhang · Zaiqiao Meng · Jake Lever · Edmond S. L. Ho
Multimodal large language models (MLLMs) have recently achieved remarkable progress in radiology by integrating visual perception with natural language understanding. However, they often generate clinically unsupported descriptions, known as medical hallucinations, which pose serious risks in med...