Abstract:Despite exciting progress in large-scale language generation, the expressiveness of its representations is severely limited by the anisotropy issue where the hidden representations are distributed into a narrow cone in the vector space. To address this issue, we present CONTRAGEN, a novel contrastive learning framework to improve the representation with better uniformity and discrimination. We assess CONTRAGEN on a wide range of downstream tasks in natural and programming languages. We show that CONTRAGEN can … Show more
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