Some algorithms perform unstably across different runs, thus the average among several runsisamorestablemeasure. Using a unified measure is convenient, concise, and space-saving for ablation study and parameteranalysis. HereH = hand W = w,but to be clear,let'sdenote them differently. Then in Eq. (7), GMP is applied along the last dimension ofhw elements, resulting in a vector of sizeHW. Third, the proposed method has already considered the efficiency,with itssimplified decoder and balanced parameter selection, and thus it is the most efficient one in cross-matching Transformers as shown in Table 2 of the main paper.

Thelatter improves the performance, but it is still limited. This implies that the attention mechanism inTransformers isprimarily designed forglobal feature aggregation, which is not naturally suitable for image matching.

Afterpre-processing methodsin [are 16,087 samples, and 1, 668, 738 featuresinthedataset.

Computerized adaptive testing (CA T), as a tool that can efficiently measure student's ability, has been widely used in various standardized tests (e.g., GMA T and

Output: Anappropriateexposuretime t. /* Initialization */ 1 n 0; // Initialize the number of iterations 2 l 0; // Initialize the lower bound of the search space 3 u 1; // Initialize the upper bound of the search space /* Start the binary search */ 4 whilec

Inreinforcement learning, option models (Sutton, Precup & Singh, 1999; Precup, 2000) provide the framework for this kind of temporally abstract prediction and reasoning. Natural intelligent agents are also able to focus their attention on courses of action that are relevant or feasible in agiven situation, sometimes termed affordable actions.

This parameter prompting, 5. Tobe t, instruction I: {Ii}n,It intoate{Ii}n refers in-conte It denotes wherethe54], we I into 6

The goal of data attribution for text-to-image models is to identify the training images that most influence the generation of a new image.