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Achieving accurate material decomposition in sparse-view DECT could revolutionize medical imaging by enabling safer, lower-radiation scans without sacrificing detail.
Autonomous agents are driving millions of daily transactions, yet their growth is shackled by a fragile infrastructure that threatens the Web4 economy's sustainability.
GUMP-Net achieves superior pelvic segmentation accuracy while providing interpretable insights into deep learning processes, even with small datasets.
Forget scaling laws: high-quality training data lets smaller LLMs crush larger ones at agentic coding tasks.
Forget hand-coding DNN accelerator simulators – LLMs can now generate cycle-accurate, faster simulators directly from natural language, slashing development time.
