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Talking about large language models. Preprint at https:\/\/arxiv.org\/abs\/2212.03551 (2023). This paper cautions against the use of anthropomorphic terms to describe the behaviour of large language models.","DOI":"10.1038\/s41586-023-06647-8"},{"key":"6647_CR2","doi-asserted-by":"crossref","unstructured":"Andreas, J. Language models as agent models. In Findings of the Association for Computational Linguistics: EMNLP 2022 5769\u20135779 (Association for Computational Linguistics, 2022). This paper hypothesizes that LLMs can be understood as modelling the beliefs, desires and (communicative) intentions of an agent, and presents preliminary evidence for this in the case of GPT-3.","DOI":"10.18653\/v1\/2022.findings-emnlp.423"},{"key":"6647_CR3","doi-asserted-by":"crossref","unstructured":"Park, J. S. et al. Generative agents: interactive simulacra of human behavior. Preprint at https:\/\/arxiv.org\/abs\/2304.03442 (2023).","DOI":"10.1145\/3586183.3606763"},{"key":"6647_CR4","unstructured":"Janus. Simulators. LessWrong Online Forum https:\/\/www.lesswrong.com\/posts\/vJFdjigzmcXMhNTsx\/ (2022). This blog post introduced the idea that a large language model maintains a set of simulated characters in superposition."},{"key":"6647_CR5","unstructured":"Wei, J. et al. Emergent abilities of large language models. Trans. Mach. Learn. Res. https:\/\/openreview.net\/forum?id=yzkSU5zdwD (2022)."},{"key":"6647_CR6","unstructured":"Vaswani, A. et al. Attention is all you need. Adv. Neural Inf. Process. Syst. 30, 5998\u20136008 (2017)."},{"key":"6647_CR7","unstructured":"Radford, A. et al. Language models are unsupervised multitask learners. Preprint at OpenAI https:\/\/cdn.openai.com\/better-language-models\/language_models_are_unsupervised_multitask_learners.pdf (2019)."},{"key":"6647_CR8","unstructured":"Brown, T. et al. Language models are few-shot learners. Adv. Neural Inf. Process. Syst. 33, 1877\u20131901 (2020)."},{"key":"6647_CR9","unstructured":"Rae, J. W. et al. Scaling language models: methods, analysis & insights from training Gopher. Preprint at https:\/\/arxiv.org\/abs\/2112.11446 (2021)."},{"key":"6647_CR10","unstructured":"Chowdhery, A. et al. PaLM: scaling language modeling with pathways. Preprint at https:\/\/arxiv.org\/abs\/2204.02311 (2022)."},{"key":"6647_CR11","unstructured":"Thoppilan, R. et al. LaMDA: language models for dialog applications. Preprint at https:\/\/arxiv.org\/abs\/2201.08239 (2022)."},{"key":"6647_CR12","unstructured":"OpenAI. GPT-4 technical report. Preprint at https:\/\/arxiv.org\/abs\/2303.08774 (2023)."},{"key":"6647_CR13","unstructured":"Touvron, H. et al. Llama 2: open foundation and fine-tuned chat models. Meta AI https:\/\/ai.meta.com\/research\/publications\/llama-2-open-foundation-and-fine-tuned-chat-models\/ (2023)."},{"key":"6647_CR14","unstructured":"Roose, K. Bing\u2019s A.I. chat: \u2018I want to be alive\u2019. New York Times (26 February 2023); https:\/\/www.nytimes.com\/2023\/02\/16\/technology\/bing-chatbot-transcript.html."},{"key":"6647_CR15","unstructured":"Willison, S. Bing: \u201cI will not harm you unless you harm me first\u201d. Simon Willison\u2019s Weblog https:\/\/simonwillison.net\/2023\/Feb\/15\/bing\/ (2023)."},{"key":"6647_CR16","unstructured":"Ruane, E., Birhane, A. & Ventresque, A. Conversational AI: social and ethical considerations. In Proc. 27th AIAI Irish Conference on Artificial Intelligence and Cognitive Science (eds Curry, E., Keane, M. T., Ojo, A. & Salwala, D.) 104\u2013115 (2019)."},{"key":"6647_CR17","unstructured":"Nardo, C. Want to predict\/explain\/control the output of GPT-4? Then learn about the world, not about transformers. LessWrong Online Forum https:\/\/www.lesswrong.com\/posts\/G3tuxF4X5R5BY7fut\/want-to-predict-explain-control-the-output-of-gpt-4-then (2023)."},{"key":"6647_CR18","unstructured":"Reynolds, L. & McDonell, K. Multiversal views on language models. In Joint Proc. ACM IUI 2021 Workshops (eds Glowacka, D. & Krishnamurthy, V. R.) https:\/\/ceur-ws.org\/Vol-2903\/IUI21WS-HAIGEN-11.pdf (2021)."},{"key":"6647_CR19","unstructured":"Glaese, A. et al. Improving alignment of dialogue agents via targeted human judgements. Preprint at https:\/\/arxiv.org\/abs\/2209.14375 (2022)."},{"key":"6647_CR20","unstructured":"Bai, Y. et al. Constitutional AI: harmlessness from AI feedback. Preprint at https:\/\/arxiv.org\/abs\/2212.08073 (2022)."},{"key":"6647_CR21","doi-asserted-by":"crossref","unstructured":"Bender, E., Gebru, T., McMillan-Major, A. & Shmitchell, S. On the dangers of stochastic parrots: can language models be too big? 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