1. Google Cloud. (2024). Introduction to prompt design. Generative AI Documentation. In the "Prompt techniques" section
under the subsection "Chaining
" it states: "Chaining is the technique of breaking a single
large task into a series of smaller
interconnected sub-tasks... The output of one prompt is used in the input of a subsequent prompt."
2. Microsoft. (2024). Introduction to prompt engineering. Azure AI services documentation. In the "Prompt engineering techniques" section
under the subsection "Chaining
" it describes the technique as: "Chaining involves breaking down a large task into a series of smaller
connected prompts. The output of one prompt becomes the input for the next."
3. Wei
J.
Wang
X.
Schuurmans
D.
Bosma
M.
Chi
E.
Le
Q.
& Zhou
D. (2022). Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. Advances in Neural Information Processing Systems
35
24824-24837. The paper's core concept (Section 2
"Chain-of-Thought Prompting") is a specific implementation of sequential prompting where intermediate reasoning steps are generated
demonstrating the principle of breaking down a problem sequentially.
4. Zhao
W. X.
Zhou
K.
Li
J.
Tang
T.
Wang
X.
Hou
Y.
... & Wen
J. R. (2023). A Survey of Large Language Models. arXiv preprint arXiv:2303.18223. Section 4.2.2
"Chain-of-Thought (CoT) Prompting
" describes this method as generating "a sequence of intermediate reasoning steps
" which is a foundational concept for prompt chaining. (DOI: https://doi.org/10.48550/arXiv.2303.18223)
