Maswali ya Miundo ya Usambazaji Fiche

Majibu na maelezo huonekana unapojibu maswali.

1. Je, ni uvumbuzi gani mkuu wa mifano fiche ya usambaaji ikilinganishwa na uenezaji wa nafasi ya pixel?
   • Huendesha mchakato wa uenezaji katika nafasi fiche iliyobanwa badala ya saizi mbichi
   • Wanaondoa hitaji la mtandao wowote wa neva
   • Wanafanya kazi tu kwenye picha nyeusi-na-nyeupe
   • Hazihitaji data ya mafunzo hata kidogo
2. In latent diffusion, what does the first-stage autoencoder do?
   • Predicts text tokens without processing images
   • Encodes an image into a latent representation and decodes latents back into images
   • Replaces the diffusion model at every denoising step
   • Classifies a prompt as safe or unsafe
3. Maandishi kawaida huingizwaje kwenye U-Net ya denoising katika uenezaji wa siri?
   • Kwa kuunganisha mfuatano wa maandishi ghafi kwa picha
   • Kwa kuhariri pikseli mwenyewe
   • Kupitia tabaka za usikivu mtambuka kwa kutumia upachikaji wa maandishi
   • Maandishi hayawezi kutumika hata kidogo
4. Why can denoising in a latent diffusion model reduce computation compared with pixel-space diffusion?
   • The model skips all image decoding
   • The diffusion network uses no neural layers
   • The model removes every denoising step
   • The denoiser operates on a smaller spatial latent grid, though decoding is still needed at the end
5. Which first-stage autoencoder regularization variants does the original latent diffusion paper investigate?
   • KL-regularized and vector-quantized autoencoders
   • Only a classifier-free guidance model
   • Only a causal language model
   • A decoder that has no learned parameters
6. Mtindo wa uenezaji hujifunza kufanya nini wakati wa mafunzo?
   • Kuainisha picha katika kategoria
   • Kugeuza mchakato wa kelele polepole na kutoa sauti kwa hatua
   • Ili kubana maandishi kuwa sauti
   • Ili kutafsiri lugha
7. In the paper’s f=8 autoencoder configuration, what does the downsampling factor describe?
   • The model uses eight separate text encoders
   • Every input is reduced to exactly eight pixels
   • Each spatial dimension of the latent grid is reduced by a factor of eight
   • The diffusion model performs eight total training updates
8. How does the latent diffusion paper inject spatial conditions such as semantic layouts into the denoiser?
   • It converts the layout into an English sentence only
   • It removes spatial coordinates before denoising
   • It uses the condition only after decoding to pixels
   • It concatenates the spatial condition with the latent representation along channels