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Found 5 papers, 0 papers with code
The Role of Protected Class Word Lists in Bias Identification of Contextualized Word Representations
Systemic bias in word embeddings has been widely reported and studied, and efforts made to debias them; however, new contextualized embeddings such as ELMo and BERT are only now being similarly studied.
ChatEval: A Tool for Chatbot Evaluation
We introduce a unified framework for human evaluation of chatbots that augments existing tools and provides a web-based hub for researchers to share and compare their dialog systems.
Semantic Word Clusters Using Signed Spectral Clustering
For spectral clustering using such word embeddings, words are points in a vector space where synonyms are linked with positive weights, while antonyms are linked with negative weights.
Predicting Emotional Word Ratings using Distributional Representations and Signed Clustering
Inferring the emotional content of words is important for text-based sentiment analysis, dialogue systems and psycholinguistics, but word ratings are expensive to collect at scale and across languages or domains.
