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cs.CL2021
All Bark and No Bite: Rogue Dimensions in Transformer Language Models Obscure Representational Quality
William Timkey, Marten van Schijndel
Similarity measures are a vital tool for understanding how language models represent and process language. Standard representational similarity measures such as cosine similarity a…
cs.CL2021
To Point or Not to Point: Understanding How Abstractive Summarizers Paraphrase Text
Matt Wilber, William Timkey, Marten Van Schijndel
Abstractive neural summarization models have seen great improvements in recent years, as shown by ROUGE scores of the generated summaries. But despite these improved metrics, there…
cs.CL2021
Uncovering Constraint-Based Behavior in Neural Models via Targeted Fine-Tuning
Forrest Davis, Marten van Schijndel
A growing body of literature has focused on detailing the linguistic knowledge embedded in large, pretrained language models. Existing work has shown that non-linguistic biases in…