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South-Central Minzu University
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TRCGL-Net achieves a remarkable tail-class mAP of 0.4904, setting a new benchmark for rare disease recognition in chest X-ray classification.
GGATN achieves reliable full event sequence generation with zero hallucinations, outperforming traditional LLMs by integrating structured process graphs into its architecture.
