quiz bu lëkkale ak tegtal · Dëgër Niveau

XLNet XLNet

Saytu factorisasioŋ permutasioŋ, bàyyi xel ci ñaari yoon, Transformer-XL baamtu, ak ni réclamasioŋ benchmark di aju ci jekkal yuñ mëna méngale.

Yooni njiit yu jëm ciModelu weccitu Xlnet
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Lan mooy mébetu tàggat-yaram bi XLNet di jëfandikoo?

Xoolaatal laaj bu nekk8 laaj

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

  1. Lan mooy mébetu tàggat-yaram bi XLNet di jëfandikoo?
    • Modelu làkku permutasioŋ
    • Modeling làkk buñ maske
    • ñu wecci gis-gis token
    • Prediction frase bi ci topp
  2. Ban ñakk kattan ci BERT lañu jagleel XLNet ngir saafara?
    • BERT daa tuuti lool
    • Jeton [MASK] bi moo waral ab pretrain/fine-tune bu jaarul yoon ba noppi dafay xalaat moomel sa bopp bu jeton maske
    • BERT mënul jëfandikoo frase yu gàtt
    • BERT amul enkodaasu posisioŋ
  3. Lan mooy tàqale XLNet ci ñaari xeeti bàyyi xel ci sa bopp?
    • Encodeur ak decodeur
    • Graafiku tàggat ak jël doggal
    • Benn ëmbiit ak benn laajte
    • Token ak tegtal
  4. Ndax XLNet dafay jaxase kàddu yi ci santaane?
    • Waaw, dafay raññe jeton yi ci anam wu mucc
    • Waaw, waaye ci diiru ajustement
    • Dédeet, musul soppi benn komànd
    • Dédeet, dafay soppi doxalinu faktorisasioŋ bi jëfandikoo masku bàyyi xel ci di tëye position yi
  5. Ban architecture mooy nekk yaxu ndigg ci XLNet ci wàllu sori?
    • Transformatër-XL
    • LSTM
    • Transformatëru vanille bu dëggu
    • Reseau convolutionnel
  6. How does XLNet combine bidirectional context with autoregressive prediction?
    • It predicts all tokens independently with no attention mask
    • It predicts in sampled factorization orders without inserting a [MASK] input token, using attention masks
    • It physically shuffles the sentence before every prediction
    • It replaces autoregressive prediction with a denoising autoencoder
  7. For a token sequence A B C, suppose a sampled factorization order predicts C before A and B. What context is available when predicting C?
    • The tokens A and B must always be provided first
    • Only the next sentence is available
    • No earlier tokens in that sampled order, although C remains at its original input position
    • The input sequence is physically reordered to C A B
  8. How does XLNet prevent the target token from leaking into its own prediction query?
    • It removes the target from the entire training sequence
    • It uses the target’s label as an input embedding
    • It replaces the token with a [MASK] symbol
    • The query stream represents the target position without its token content