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PhysNLU: A Language Resource for Evaluating Natural Language Understanding and Explanation Coherence in Physics. (arXiv:2201.04275v1 [cs.CL])
Jan. 13, 2022, 2:10 a.m. | Jordan Meadows, Zili Zhou, Andre Freitas
cs.CL updates on arXiv.org arxiv.org
In order for language models to aid physics research, they must first encode
representations of mathematical and natural language discourse which lead to
coherent explanations, with correct ordering and relevance of statements. We
present a collection of datasets developed to evaluate the performance of
language models in this regard, which measure capabilities with respect to
sentence ordering, position, section prediction, and discourse coherence.
Analysis of the data reveals equations and sub-disciplines which are most
common in physics discourse, as well …
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