长短期记忆（1997）[pdf]
本文由 Hochreiter 和 Schmidhuber 于 1997 年发表，提出了长短期记忆（LSTM）网络，这是一种特殊的循环神经网络（RNN）架构。LSTM 通过引入记忆单元和门控机制（输入门、遗忘门、输出门），有效解决了传统 RNN 在处理长序列数据时面临的梯度消失和梯度爆炸问题，从而能够学习长期依赖关系。该论文是深度学习领域的奠基性工作之一，对自然语言处理、语音识别和时间序列预测等众多领域产生了深远影响。
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