11. Reference
- Eliza: A Web3 friendly AI Agent Operating System, 2025,[ https://arxiv.org/pdf/2501.06781 ](https://arxiv.org/pdf/2501.06781
- Virtuals Protocol, 2024, https://whitepaper.virtuals.io
- Kinds.ai, 2024, https://whitepaper.kinds.ai
- Delysium, 2024, https://delysium.gitbook.io/whitepaper
- Shafran, I., Cao, Y. et al., 2022, ReAct: Synergizing Reasoning and Acting in Language Models
- Wei, J., Wang, X. et al., 2023, Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
- Wang, X. et al., 2022, Self-Consistency Improves Chain of Thought Reasoning in Language Models
- Diao, S. et al., 2023, Active Prompting with Chain-of-Thought for Large Language Models
- Zhang, H. et al., 2023, Multimodal Chain-of-Thought Reasoning in Language Models
- Yao, S. et al., 2023, Tree of Thoughts: Deliberate Problem Solving with Large Language Models
- Long, X., 2023, Large Language Model Guided Tree-of-Thought
- Google, Google Gemini Application
- Xie, M., 2022, How does in-context learning work? A framework for understanding the differences from traditional supervised learning
- Google Research, ScaNN (Scalable Nearest Neighbors)
- Semantic Kernel, https://learn.microsoft.com/en-us/semantic-kernel
- LangChain, https://www.langchain.com
- LangGraph, https://www.langchain.com/langgraph
- Crewai, https://www.crewai.com