开源OncoAgent肿瘤学Agent实现56倍训练加速
名为oncoagent的隐私保护肿瘤支持代理在amd mi300x硬件上仅用50分钟完成训练，相比api方法实现了56倍的速度提升。
the oncoagent research group published a technical preprint for oncoagent, a multi-agent framework designed for privacy-preserving oncology support. the system routes queries to 9b or 27b models fine-tuned via qdora on amd instinct mi300x hardware, processing 266,854 real and synthetic cases. hardware-specific optimizations enabled full dataset training in approximately 50 minutes, marking a 56× improvement over api-based generation. the architecture utilizes a four-stage corrective rag pipeline with 100% grading success and a reflexion safety validator to ensure data sovereignty.