Building Reactive Large Language Model Pipelines with Motion

Author:

Shankar Shreya1ORCID,Parameswaran Aditya G.1ORCID

Affiliation:

1. UC Berkeley, Berkeley, CA, USA

Funder

National Defense Science and Engineering Graduate

National Science Foundation

Publisher

ACM

Reference10 articles.

1. Mahyar Abbasian Iman Azimi Amir M. Rahmani and Ramesh Jain. 2024. Conversational Health Agents: A Personalized LLM-Powered Agent Framework. arxiv: 2310.02374 [cs.CL]

2. Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al. 2023. Gpt-4 technical report. arXiv preprint arXiv:2303.08774 (2023).

3. Phillip Carter. 2023. All the hard stuff nobody talks about when building products with llms. https://www.honeycomb.io/blog/hard-stuff-nobody-talks-about-llm

4. Zui Chen, Zihui Gu, Lei Cao, Ju Fan, Sam Madden, and Nan Tang. 2023. Symphony: Towards natural language query answering over multi-modal data lakes. In Conference on Innovative Data Systems Research, CIDR. 8--151.

5. Qingxiu Dong, Lei Li, Damai Dai, Ce Zheng, Zhiyong Wu, Baobao Chang, Xu Sun, Jingjing Xu, and Zhifang Sui. 2022. A survey for in-context learning. arXiv preprint arXiv:2301.00234 (2022).

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