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Leveraging Large (Visual) Language Models for Robot 3D Scene Understanding
William Chen, Siyi Hu, Rajat Talak +1
Abstract semantic 3D scene understanding is a problem of critical importance in robotics. As robots still lack the common-sense knowledge about household objects and locations of a…
Problems with Cosine as a Measure of Embedding Similarity for High Frequency Words
Kaitlyn Zhou, Kawin Ethayarajh, Dallas Card +1
Cosine similarity of contextual embeddings is used in many NLP tasks (e.g., QA, IR, MT) and metrics (e.g., BERTScore). Here, we uncover systematic ways in which word similarities e…
Modular Domain Adaptation
Junshen K. Chen, Dallas Card, Dan Jurafsky
Off-the-shelf models are widely used by computational social science researchers to measure properties of text, such as sentiment. However, without access to source data it is diff…
Whose Language Counts as High Quality? Measuring Language Ideologies in Text Data Selection
Suchin Gururangan, Dallas Card, Sarah K. Dreier +5
Language models increasingly rely on massive web dumps for diverse text data. However, these sources are rife with undesirable content. As such, resources like Wikipedia, books, an…