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Collateral facilitation in humans and language models (2211.05198v1)

Published 9 Nov 2022 in cs.CL and cs.AI

Abstract: Are the predictions of humans and LLMs affected by similar things? Research suggests that while comprehending language, humans make predictions about upcoming words, with more predictable words being processed more easily. However, evidence also shows that humans display a similar processing advantage for highly anomalous words when these words are semantically related to the preceding context or to the most probable continuation. Using stimuli from 3 psycholinguistic experiments, we find that this is also almost always also the case for 8 contemporary transformer LLMs (BERT, ALBERT, RoBERTa, XLM-R, GPT-2, GPT-Neo, GPT-J, and XGLM). We then discuss the implications of this phenomenon for our understanding of both human language comprehension and the predictions made by LLMs.

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Authors (2)
  1. James A. Michaelov (13 papers)
  2. Benjamin K. Bergen (31 papers)
Citations (11)

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