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VCDM: Leveraging Variational Bi-encoding and Deep Contextualized Word Representations for Improved Definition Modeling
Machel Reid, Edison Marrese-Taylor, Yutaka Matsuo
In this paper, we tackle the task of definition modeling, where the goal is to learn to generate definitions of words and phrases. Existing approaches for this task are discriminat…
Combining Pretrained High-Resource Embeddings and Subword Representations for Low-Resource Languages
Machel Reid, Edison Marrese-Taylor, Yutaka Matsuo
The contrast between the need for large amounts of data for current Natural Language Processing (NLP) techniques, and the lack thereof, is accentuated in the case of African langua…
Variational Inference for Learning Representations of Natural Language Edits
Edison Marrese-Taylor, Machel Reid, Yutaka Matsuo
Document editing has become a pervasive component of the production of information, with version control systems enabling edits to be efficiently stored and applied. In light of th…