Feb. 27, 2024, 5:50 a.m. | Julia Witte Zimmerman, Denis Hudon, Kathryn Cramer, Jonathan St. Onge, Mikaela Fudolig, Milo Z. Trujillo, Christopher M. Danforth, Peter Sheridan Dodd

cs.CL updates on arXiv.org arxiv.org

arXiv:2306.06794v2 Announce Type: replace
Abstract: Large Language Models (LLMs) like ChatGPT reflect profound changes in the field of Artificial Intelligence, achieving a linguistic fluency that is impressively, even shockingly, human-like. The extent of their current and potential capabilities is an active area of investigation by no means limited to scientific researchers. It is common for people to frame the training data for LLMs as "text" or even "language". We examine the details of this framing using ideas from several areas, …

abstract artificial artificial intelligence arxiv blind blind spot capabilities chatgpt cs.ai cs.cl current human human-like information intelligence investigation language language models large language large language models llms spot type

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