Papers with large scale language modelling tasks
Learning with Noise-Contrastive Estimation: Easing training by learning to scale (C18-1)
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| Challenge: | Neural language models have recently shown great improvement, but they share a common issue: large output vocabulary, computational time, and high dimensional space. |
| Approach: | They propose to make scaling factor a trainable parameter and use noise distribution to initialize output bias. |
| Outcome: | The proposed training strategies yield stable and competitive performances in small and large scale language modelling tasks. |