在预训练阶段使用 Language Modeling Loss 是因为模型需要学习生成连贯的文本。而在指令调优（instruction tuning）阶段，使用 Sequence-to-Sequence Loss 是因为这个阶段的目标是将输入的指令转换为相应的输出，这与预训练阶段的目标有所不同。
其通过具有instruction简单的seq-to-seq学习框架统一了任务,包括理解和生成,例如:image generation、visual grounding、visual question answering、image captioning、image classification、language modeling。 实验结果显示OFA在多模态基准上实现了新的SOTA,包括:image captioning、text-to-image generation、VQA、SNLI-VE等;...
Sequence to sequence text generation is the most efficient approach for automatically converting the script of a word from a source sequence to a target sequence. Text generation is the application of natural language generation which is useful in sequence modeling like t...
这个想法由voice cloning 发展而来,有可能从one-to-one推广到many-to-many conversion。voice cloning 是text-to-speech,利用一些speech sample生成unseen speaker speech。 C. Sequence-to-sequence learning for voice conversion 【31】第一次使用带有attention的seq2seq的转换,但是他不能使用自己的预测产生实值...
Modeling units Sequence-to-sequenceTransformerSequence-to-sequence attention-based models have recently shown very promising results on automatic speech recognition (ASR) tasks, which integrate an acoustic, pronunciation and language model into a single neural network. In these models, the Transformer, a...
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Such context-aware query reformulation problem lends itself to sequence to sequence modeling. We present a large scale open domain dataset of conversational queries and various sequence to sequence models that are learned from this dataset. The best model correctly reformulates over half ...
Language Modeling with Gated Convolutional Networks (Dauphin et al., 2017) Convolutional Sequence to Sequence Learning (Gehring et al., 2017) Classical Structured Prediction Losses for Sequence to Sequence Learning (Edunov et al., 2018) Hierarchical Neural Story Generation (Fan et al., 2018) ...
In this paper, we formulate Chinese sign language recognition (SLR) as a sequence to sequence problem and propose an encoder-decoder based framework to handle it. The proposed framework is based on the convolutional neural network (CNN) and recurrent neu
原文链接:Language Modeling with Gated Convolutional Networks Convolutional Block Structure# 编码器与解码器都是由多个卷积层构成的(原文中称为block,实际上就是layer),每一层包含一个1维卷积核以及一个门控线性单元(Gated linear units, GLU)。假设单词数即输入长度为mm,kernel大小为kk,pad为pp,那么计算输出sequ...