Kediska Moodooyinka Faafinta Daahsoon

Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.

1. Waa maxay hal-abuurnimada ugu weyn ee moodooyinka fidinta daahsoon marka la barbar dhigo fidinta-meel-afeedka pixel?
   • Waxay ku socodsiiyaan habka fidinta meel qarsoon oo ciriiri ah halkii ay ka ahaan lahaayeen pixels cayriin
   • Waxay meesha ka saaraan baahida shabakad kasta oo neerfaha ah
   • Waxay kaliya ku shaqeeyaan sawirada madow iyo caddaanka
   • Wax xog tababar ah uma baahna haba yaraatee
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. Sidee baa qoraalka caadiga ah loogu duraa U-Net-ka been abuurka ah ee faafin qarsoon?
   • Adigoo isku dhejinaya xargaha qoraalka ceeriin ee sawirka
   • Adigoo gacanta ku tafatiraya pixels
   • Iyada oo loo marayo lakabyo-feejignaan isdhaafsi ah iyadoo la adeegsanayo qoraallada ku dhejinta
   • Qoraalka gabi ahaanba lama isticmaali karo
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. Muxuu qaabka fidinta u bartaa inuu sameeyo inta lagu jiro tababarka?
   • Si loo kala saaro sawirada qaybo
   • Si loo beddelo habka qaylada tartiib-tartiib ah loona diido tallaabo-tallaabo
   • Si aad qoraalka ugu dhejiso maqal
   • Si loo turjumo luqadaha
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