The evaluation of word embeddings has received a considerable amount of attention in
recent years, but there have been some debates about whether intrinsic measures can …

Research into semantic similarity has a long history in lexical semantics, and it has
applications in many natural language processing (NLP) tasks like word sense …

Distributional semantics in the form of word embeddings are an essential ingredient to many
modern natural language processing systems. The quantification of semantic similarity …

因為能夠反應社會上的價值觀, 再加上其性別化的訊息, 還有新聞性的本質, 流行雜誌時常是性別
研究的研究對象. 先前的研究表明, 詞嵌入模型能夠揭示媒體中性別之間的微妙偏見 …

隨著大型語言模型的能力愈發強健, 多輪對話式規章問答任務的主軸也從如何理解文句間的蘊含
關係(entailment), 如何訓練模型產生自然語言的回覆或反問, 轉變為如何使用大型語言模型提供 …

Word embedding is a modern distributed word representations approach widely used in
many natural language processing tasks. Converting the vocabulary in a legal document …

Viele Methoden wurden in dieser Arbeit vorgestellt, die sich mit dem Hauptziel der
automatischen Dokumentenanalyse auf semantischer Ebene befassen. Um das Hauptziel …

Multilingual word embeddings are the elements of a vector space that represents the
meanings of words across different languages. The applications of the multilingual word …

Applying natural language processing-related algorithms is currently a popular project in
legal applications, for instance, document classification of legal documents, contract review …

Word analogy tasks have tended to be handcrafted, involving permutations of hundreds of
words with dozens of relations, mostly morphological relations and named entities. Here, we …