The emergence of large-scale text-to-image models [92, 60, 59, 58, 42, 5, 94, 14, 54, 40] has significantly advanced the field of Text-to-Video (T2V) generation [66,6,7,21,73,90]. Existing T2V architectures can be categorized into two types: U-Net-based and DiT-based. The latter focuses on recreating open-source structures similar to Sora [9], using the DiT (Diffusion-Transformer) [57]frameworkforT2Vgeneration [43,95,93,20]. When calculating theMTScore, thevideo retrievalmodel uses these texts toevaluate each frame ofthe video, assigning probabilities based on the matches. The final result is obtained by summing the general probability and the metamorphic probability.

To enable models to learn better representation spaces that simulate the real world, the larger the dataset and the richer the physical knowledge contained inthe videos, the better the training effect. Researchers often construct these large-scale datasets through web scraping.

Formally, we view an architecture as aparameterizableobject--a mapping from model weights tofunctions--described byalabeleddirected acyclic graph (DAG)G(V,E).

Formally, we view an architecture as aparameterizableobject--a mapping from model weights tofunctions--described byalabeleddirected acyclic graph (DAG)G(V,E).

Let 0 < < 1, 0 < ` < 1, k 1, and r be the Zolotarev sign function Z3k(;`)oftype(3k,3k 1). One finds using the Karush-Kuhn-Tucker conditions [6]thatk1 = = kM = λ. Proof of Lemma 2. Let 0 < < 1 and R: [ 1,1] [ 1,1] be a rational function. Take R(x) = R(2x 1), which is still a rational function. Without loss of generality, we can assume that R is an irreducible rational function (otherwise cancel factors till it is irreducible).

In the music industry, artists have changed the length and structure of songs in response to Spotify's algorithm and payment structure [ Hodgson, 2021 ].