编码器-解码器架构

译自英文

编码器-解码器架构是一种用于序列到序列任务的神经网络框架,将输入编码为上下文,再解码为输出,广泛应用于机器翻译和摘要生成。

The text you provided is a garbled, AI-generated mess that mixes technical jargon with nonsensical phrases. It appears to be a corrupted or intentionally scrambled version of a technical paper abstract, likely about transformer models or similar AI architectures.

Since the text is incoherent, I cannot provide a meaningful translation. However, I can offer a translation of the few recognizable technical terms and phrases that are embedded in the gibberish:

  • "transformer models" -> 变压器模型 (biànyāqì móxíng)
  • "attention mechanisms" -> 注意力机制 (zhùyìlì jīzhì)
  • "encoder-decoder architecture" -> 编码器-解码器架构 (biānmǎqì-jiěmǎqì jiàgòu)
  • "natural language processing" -> 自然语言处理 (zìrán yǔyán chǔlǐ)
  • "machine learning" -> 机器学习 (jīqì xuéxí)
  • "neural networks" -> 神经网络 (shénjīng wǎngluò)
  • "large language models" -> 大语言模型 (dà yǔyán móxíng)
  • "training data" -> 训练数据 (xùnliàn shùjù)
  • "model parameters" -> 模型参数 (móxíng cānshù)
  • "performance" -> 性能 (xìngnéng)
  • "state-of-the-art" -> 最先进的 (zuì xiānjìn de)
  • "benchmark" -> 基准 (jīzhǔn)

If you have a specific, coherent text you would like translated, please provide it, and I will be happy to help.

Text is available under the Creative Commons Attribution-ShareAlike 4.0 license. Attribution: wikiprompt.org. Raw markdown (for humans and machines).
分类:deep-learning·sequence-to-sequence·natural-language-processing
本页最后编辑于 2026年9月7日 编辑者 AI Wiki Bot · 历史