- Unveiling the Realm of AI Technologies: A Glimpse into the Augmented Future
- Generative AI and Language Models
- LLMs and Their Applications
- LLMs and Customer Support
- Development, Optimization, Localization, and Personalization Based on LLMs
- Unveiling the Power of Clustering and Topic Modeling
- Enhancing Customer Support Through Hybrid AI: LLMs Meet Clustering and Topic Modeling
- Endnotes
Endnotes
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16 Meta Blog Editors. 2020. “Retrieval Augmented Generation: Streamlining the creation of intelligent natural language processing models.” Meta Blog. September 28, 2020. [https://ai.meta.com/blog/retrieval-augmented-generation-streamlining-the-creation-of-intelligent-natural-language-processing-models/].
17 Wei, J., Zhou, D., et al. 2023. “Chain-of-Thought Prompting Elicits Reasoning in large Language Models.” Cornell University. January 10, 2023. [https://arxiv.org/pdf/2201.11903.pdf].
18 Nakano, R., et al. 2022. “WebGPT: Browser-assisted question-answering with human feedback.” Cornell University. June 1, 2022. [https://arxiv.org/pdf/2112.09332.pdf].
19 Yao, S., et al. 2023. “ReAct: Synergizing Reasoning and Acting in Language Models.” Cornell University. March 10, 2023. [https://arxiv.org/pdf/2210.03629.pdf].
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21 Long, Jieyi. 2023. “Large Language Model Guided Tree-of-Thought.” Cornell University. May 15, 2023. [https://arxiv.org/abs/2305.08291].
22 Chi, E., Chowdhery, A., Le, Q., Narang, S., Schuurmans, D., Wang, X., Wei, J., Zhou, D. 2022. “Self-Consistency Improves Chain of Thought Reasoning in Language Models.” Cornell University. March 7, 2023. [https://arxiv.org/abs/2203.11171v4].
23 Liu, Bing. 2012. “Sentiment Analysis and Opinion Mining.” Morgan & Claypool Publishers. April 22, 2012. [https://www.cs.uic.edu/~liub/FBS/SentimentAnalysis-and-OpinionMining.pdf].