Analysis methods in neural language processing: A survey
The field of natural language processing has seen impressive progress in recent years, with
neural network models replacing many of the traditional systems. A plethora of new models …
neural network models replacing many of the traditional systems. A plethora of new models …
Intrinsic bias metrics do not correlate with application bias
Natural Language Processing (NLP) systems learn harmful societal biases that cause them
to amplify inequality as they are deployed in more and more situations. To guide efforts at …
to amplify inequality as they are deployed in more and more situations. To guide efforts at …
From word to sense embeddings: A survey on vector representations of meaning
Over the past years, distributed semantic representations have proved to be effective and
flexible keepers of prior knowledge to be integrated into downstream applications. This …
flexible keepers of prior knowledge to be integrated into downstream applications. This …
Interpreting pretrained contextualized representations via reductions to static embeddings
Contextualized representations (eg ELMo, BERT) have become the default pretrained
representations for downstream NLP applications. In some settings, this transition has …
representations for downstream NLP applications. In some settings, this transition has …