论文解读：On The Alignment Problem In Multi-Head Attention-Based Neural Machine Translation
论文解读：On The Alignment Problem In Multi-Head Attention-Based Neural Machine Translation 机器翻译是自然语言处理的任务之一。基于transformer和multi-head attention在机器翻译中的应用十分广泛。注意力机制在神经机器翻译（NMT）模型中通常扮演着统计机器翻译（SMT）中的对齐机制（Ali
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相关文章
- 1. 【论文阅读】Addressing the RareWord Problem in NeuralMachine Translation
- 2. 【论文】on the properties of neural machine translation :Encoder-decoder approaches 阅读笔记
- 3. 论文阅读——Toward Making the Most of Context in Neural Machine Translation
- 4. 论文解读：Selective Attention for Context-aware Neural Machine Translation
- 5. 论文阅读：ByteNet, Neural Machine Translation in Linear Time
- 6. Neural machine translation by jointly learning to align and translate论文阅读笔记
- 7. attention model--Neural machine translation by jointly learning to align and translate论文解读
- 8. 论文解读：Multimodal Machine Translation with Embedding Prediction
- 9. Paper：Effective Approaches to Attention-based Neural Machine Translation
- 10. 【论文阅读】Neural Machine Translation by Jointly Learning to Align and Translate