Quiz ci xeetu diffusion yu nëbbu

Sooy def quiz bi, tontu yi ak leeral yi dañuy feeñ.

1. Lan mooy xeetu diffusion bu nëbbu bi gëna am solo buñu ko méngale ak diffusion pixel-espace?
   • Dañuy doxal diffusion bi ci barab bu nëbbu buñ komprime, du ci pixel yu ñor
   • Dañu baña soxla benn reso neuronal
   • Dañuy liggéey ci nataal yu weex ak yu ñuul
   • Duñu soxla benn done tàggat
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. naka lañuy dugal mbind ci biir U-Net biy dindi bruit ci diffusion bu nëbbu?
   • Soo boole chaîne text bu ñor bi ak nataal bi
   • Sooy soppali pixel yi ak sa loxo
   • Jaaraleko ci diisaayi bàyyi xel ci jëfandikoo mbind yuñ samp
   • Mënu ñu jëfandikoo mbind
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. Lan la modelu diffusion bi di jàng def ci diiru tàggat yaram?
   • Ngir xaaj nataal yi ci kategori
   • ngir dindi bruit bu bari ak dindi bruit jéego par jéego
   • Ngir kompresse mbind ci audio
   • Ngir tekki làkk yi
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