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The standard train/test split contains strong semantic clustering and substantial similarity between training and test images within the same MS COCO categories. This can inflate apparent reconstruction performance (see Shirakawa et al., 2025). For reconstruction studies it is advisable to create alternative splits where test stimuli contain categories not present during training, or where semantic and visual overlap between training and test images is minimized.
，这一点在Feiyi中也有详细论述
在企业外部，也需要云厂商、智能体厂商等技术供应商的深度合作：“不是有了锤子找钉子，而是有了明确的业务痛点然后去造适合自己的锤子。”
minor impact and it would be overly hard or even impossible to have
LiDAR is the most common smart mapping tech, and its navigational efficiency gets even better with the help of AI. During the initial mapping run, AI fills in the furniture arrangements in each room for more agile cleaning. All AI robot vacuums that I've tested know that a toilet is a toilet and that a TV stand is a TV stand. Many models have even pinpointed my cat tree and automatic litter box with their own little icons, automatically triggering more detailed cleaning in areas with high pet traffic.