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Encodeurs croisés vs Bi-encodeurs
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Architecture encodeur-décodeur
Encoder-decoder architectures map an input sequence to an output sequence that may differ in length.
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Résumé
The encoder builds source representations, and the decoder generates target elements conditioned on those representations.
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Early seq2seq models used recurrent encoders and decoders. Bahdanau attention addressed the fixed-vector bottleneck by computing a source context for each decoder step. The Transformer replaces recurrence with self-attention and cross-attention. BART pretrains a denoising encoder-decoder, while T5 casts many language tasks as text-to-text. These papers evaluate specific models and tasks; the architecture alone does not guarantee quality.
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A neural translation encoder represents a source sentence while a decoder generates a translated sentence.
Bahdanau attention lets each decoder step focus on different encoder states.
The Transformer uses encoder-decoder attention and masked decoder self-attention.
BART and T5 use encoder-decoder architectures for denoising or text-to-text tasks.
Ëlëgu arsitektir enkodeer-dekodeer
Choose an encoder-decoder when a task naturally maps one sequence to another, and compare it with alternatives on the target data and latency. Track input-length behavior and output quality. The cited work does not establish that this architecture is best for every language task.
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What is Encoder-Decoder Architectures?
Encoder-decoder architectures map an input sequence to an output sequence that may differ in length. The encoder builds source representations, and the decoder generates target elements conditioned on those representations.
Lan mooy liggéey bi gëna am solo ci encoder ci xeetu encoder-decoder?
Encoder bi dafay lekk limu dugal yépp ba noppi defar ay vecteur contextuel yuy jàpp li muy tekki, decoder bi daal di koy jëfandikoo.
Lu tax dekodeer bi di jëfandikoo maske (causal) bàyyi xel ci boppam?
Maskering dafay fexe ba position bu nekk ci genn gi nekk ci position yi ko jiitu rek, ba noppi baña yàq doxalinu generation autoregressive bu cammoñ bi dem ci ndijoor ji.
Ban mekaniism mooy boole dekodeer bi ak misaali enkodeer bi?
Cross-attention dafay may bépp couche decodeur mu laaj stade yu nëbbu yi ci encodeur bi, muy lëkkale xam-xam bi ci dugal ak defar ci génne gi.
Ci xeetu architecture yii, yan ci ñoom mooy architecture encodeur-decodeur (toppal-ci-toppal)?
T5 (ak BART) ay xeetu encoder-decoder yu yàgg lañu yuy kaadre liggéey yi ni bind-ci-bind. BERT encodeur kese la, GPT-3 decodeur kese la.
Lan moo waral jëmmu encoder-decoder bi méngoo bu baax ak tekki làkk?
Tekki làkk dafay méngale benn toppalante ak beneen bu wuute, kon jàng source bi yépp (encoder) ak defar target bu bees (decoder) mën nañu ko méngale bu baax.
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