update reference format

_posts/2024-11-31-service-as-a-software.md

@@ -420,39 +420,39 @@ making them valuable for various real-world applications.
 
 ## References
 
-1.Software & Information Industry Association, "Software as a Service: Strategic
-  Backgrounder February 2001".
-1.Sonya Huang, Pat Grady, and o1, "Generative AI’s Act o1 - The agentic
-  reasoning era begins",
+1. Software & Information Industry Association, "Software as a Service: Strategic
+   Backgrounder February 2001".
+1. Sonya Huang, Pat Grady, and o1, "Generative AI’s Act o1 - The agentic
+   reasoning era begins",
   [url](https://www.sequoiacap.com/article/generative-ais-act-o1/).
-1.Shukang Yin, *et al*, A Survey on Multimodal Large Language Models, 2023.
-1.Letta, The AI agents stack, 2024.
-1.Jiahao Tian, *et al*, MMREC: LLM Based Multi-Modal Recommender System, 2024.
-1.Jason Wei, *et al*, Chain-of-Thought Prompting Elicits Reasoning in Large
-  Language Models. IEEE TPAMI, 2022.
-1.Shunyu Yao, *et al*, `ReAct`: Synergizing Reasoning and Acting in Language
-  Models. 2022.
-1.Binfeng Xu, *et al*, `ReWOO`: Decoupling Reasoning from Observations for
-  Efficient Augmented Language Models. 2023.
-1.Noah Shinn, *et al*, Reflexion: Language Agents with Verbal Reinforcement
-  Learning. 2023.
-1.Lei Wang, *et al*, Plan-and-Solve Prompting: Improving Zero-Shot
-  Chain-of-Thought Reasoning by Large Language Models. 2023.
-1.Sehoon Kim *et al*, An LLM Compiler for Parallel Function Calling.
-1.Anthropic, Building effective agents, 2023.
-1.Akshay Paruchuri, *et al*, What Are the Odds? Language Models Are Capable of
-  Probabilistic Reasoning, EMNLP, 2024
-1.Aliakbar Nafar, *et al*, Probabilistic Reasoning in Generative Large Language
-  Models, 2024
+1. Shukang Yin, *et al*, A Survey on Multimodal Large Language Models, 2023.
+1. Letta, The AI agents stack, 2024.
+1. Jiahao Tian, *et al*, MMREC: LLM Based Multi-Modal Recommender System, 2024.
+1. Jason Wei, *et al*, Chain-of-Thought Prompting Elicits Reasoning in Large
+   Language Models. IEEE TPAMI, 2022.
+1. Shunyu Yao, *et al*, `ReAct`: Synergizing Reasoning and Acting in Language
+   Models. 2022.
+1. Binfeng Xu, *et al*, `ReWOO`: Decoupling Reasoning from Observations for
+   Efficient Augmented Language Models. 2023.
+1. Noah Shinn, *et al*, Reflexion: Language Agents with Verbal Reinforcement
+   Learning. 2023.
+1. Lei Wang, *et al*, Plan-and-Solve Prompting: Improving Zero-Shot
+   Chain-of-Thought Reasoning by Large Language Models. 2023.
+1. Sehoon Kim *et al*, An LLM Compiler for Parallel Function Calling.
+1. Anthropic, Building effective agents, 2023.
+1. Akshay Paruchuri, *et al*, What Are the Odds? Language Models Are Capable of
+   Probabilistic Reasoning, EMNLP, 2024
+1. Aliakbar Nafar, *et al*, Probabilistic Reasoning in Generative Large Language
+   Models, 2024
 1. Dongsheng Li, *et al*, Recommender Systems: Frontiers and Practices, Springer
    Nature, 2024. 
-1.Le Zhang, Ubiquitous language for domain-driven development, Thinkloud, 2023.
-1.Steven Okamoto, *et al*, The Impact of Vertical Specialization on Hierarchical
-  Multi-Agent Systems, AAAI, 2008
-1.Haoyi Xiong *et al*, Natural Language based Context Modeling and Reasoning for
-  Ubiquitous Computing with Large Language Models: A Tutorial, 2023
-1.Martin Kleppmann, Designing Data-Intensive Applications: The Big Ideas Behind
-  Reliable, Scalable, and Maintainable Systems.
+1. Le Zhang, Ubiquitous language for domain-driven development, Thinkloud, 2023.
+1. Steven Okamoto, *et al*, The Impact of Vertical Specialization on Hierarchical
+   Multi-Agent Systems, AAAI, 2008
+1. Haoyi Xiong *et al*, Natural Language based Context Modeling and Reasoning for
+   Ubiquitous Computing with Large Language Models: A Tutorial, 2023
+1. Martin Kleppmann, Designing Data-Intensive Applications: The Big Ideas Behind
+   Reliable, Scalable, and Maintainable Systems.
 
 ## Citation