PETAR: AI that writes localized PET/CT findings
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LiDAR lets cars "see" the world, but low-cost sensors often produce sparse, blurry 3D points. This study introduces FLASH, a method that turns low-res scans into high-detail 3D—fast enough for real-time use. How it works * Two domains, one model: FLASH looks at data in space and in
TL;DR LoGo lets large language models pick and blend the right LoRA adapters for each input—no extra training, labels, or task setup. * Training-free: uses signals from a single forward pass to select and weight adapters. * Instance-level: decisions happen on-the-fly for every query. * Practical: keeps inference throughput while handling
Lowering CT radiation keeps patients safer—but it can make images noisy and blurry. LMM-IQA is an AI that judges low‑dose CT quality and explains what went wrong. * Gives a quality score plus short, plain‑English notes on noise, blur, and contrast loss. * Works without task‑specific training and
Lightning Grasp: faster robot gripping Finding a good grip on everyday, irregular tools is still hard for robot hands. Lightning Grasp changes that: it generates diverse, realistic grasps in real time—without training data, delicate parameter tuning, or lucky starting guesses. The trick is a simple Contact Field: a lightweight