论文标题
反义嵌入的直观对比图
Intuitive Contrasting Map for Antonym Embeddings
论文作者
论文摘要
本文表明，尽管相应的向量之间的相似之处很小，但现代单词嵌入式包含区分同义词和反义词的信息。该信息是在嵌入式的几何形状中编码的，可以通过直接和直观的流形学习过程或对比映射提取。这样的地图是在数据的一个小标记子集上训练的，可以产生新的嵌入，以明确强调单词的特定语义属性。该地图产生的新嵌入量被证明可以改善下游任务的性能。
This paper shows that, modern word embeddings contain information that distinguishes synonyms and antonyms despite small cosine similarities between corresponding vectors. This information is encoded in the geometry of the embeddings and could be extracted with a straight-forward and intuitive manifold learning procedure or a contrasting map. Such a map is trained on a small labeled subset of the data and can produce new embeddings that explicitly highlight specific semantic attributes of the word. The new embeddings produced by the map are shown to improve the performance on downstream tasks.
