Large Language Models Seem Miraculous, but Science Abhors Miracles-Reference-Cited by-同舟云学术

Large Language Models Seem Miraculous, but Science Abhors Miracles

Published:2024-05-23 Issue:6 Volume:1 Page:
ISSN:2836-9386
Container-title:NEJM AI
language:en
Short-container-title:NEJM AI

Author:

Szolovits Peter¹^ORCID

Affiliation:

1. Massachusetts Institute of Technology, Cambridge

Publisher

Massachusetts Medical Society

Reference8 articles.

1. Sergeeva E Sergeeva A Tang H Bongard-Blanchy K Szolovits P. Right no matter why: AI fact-checking and AI authority in health-related inquiry settings. October 22 2023 (http://arxiv.org/abs/2310.14358). Preprint.

2. Assessing the potential of GPT-4 to perpetuate racial and gender biases in health care: a model evaluation study

3. Lehman E Hernandez E Mahajan D et al. Do we still need clinical language models? February 16 2023 (http://arxiv.org/abs/2302.08091). Preprint.

4. Lewis P Perez E Piktus A et al. Retrieval-augmented generation for knowledge-intensive NLP tasks. Paper presented at the 34th Conference on Neural Information Processing Systems (NeurIPS 2020) Vancouver BC Canada December 6–12 2020.

5. Räuker T Ho A Casper S Hadfield-Menell D. Toward transparent AI: a survey on interpreting the inner structures of deep neural networks. August 18 2023 (http://arxiv.org/abs/2207.13243). Preprint.

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