Градиенттік түсу

In this paper, we develop a novel semi-supervised learning algorithm called hybrid deep be- lief networks (HDBN), to address the semi-supervised sentiment classification problem with deep learning. First, we construct …...

We propose NEURAL ENQUIRER — a neu- ral network architecture for answering natural language (NL) questions given a knowledge base (KB) table. Unlike previous work on end-to-end training of semantic …...

AbstractNeural Networks trained with gradient descent are known to be susceptible to catastrophic forgetting caused by parameter shift during the training process. In the context of Neural Machine Translation (NMT) …...

AbstractCurrent state-of-the-art neural dialogue models learn from human conversations following the data-driven paradigm. As such, a reliable training corpus is the crux of building a robust and well-behaved dialogue model. …...

AbstractAlthough pretrained language models can be fine-tuned to produce state-of-the-art results for a very wide range of language understanding tasks, the dynamics of this process are not well understood, especially …...

AbstractAdversarial training is one of the most powerful methods to improve the robustness of pre-trained language models (PLMs). However, this approach is typically more expensive than traditional fine-tuning because of …...