Details of Think-and-Execute That You Don’t Want to Miss

We highlight some components of code prompt that would be helpful in describing the underlying reasoning logic.


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Abstract and 1. Introduction

2 Think-and-Execute

3 Experimental Setup

4 Results

5 Analysis

6 Related Work

7 Limitations and Discussion

8 Conclusion and References

\ A Experimental Details

B Details of Think-and-Execute

C Prompts Used in Our Experiments

D Human-written Pseudocode Prompts

E Generated Analyses

F Generated Pseudocode Prompts

G Qualitative Analysis

B Details of THINK-AND-EXECUTE

B.1 Human-annotation on the Tasks in the Task Pool

Please see Appendix D for human-written pseudocode prompts.

B.2 Components of a Pseudocode Prompt

We highlight some components of code prompt that would be helpful in describing the underlying reasoning logic.

\ • Conditional branch: To allow the reasoning model to take different reasoning paths based on the condition, we use if and else statement to describe the logic.

\ • Loop: We can efficiently present repetitive instructions that iterate over a list of items by using loops, such as for and while loop.

\ • Abstraction: In programming, we can encapsulate a complex logic into a single function. Focusing on this, we adopt modular design in constructing pseudocode prompts by encapsulating complex and repetitive process into an abstract function.

\ • Variables: Variables are essential in programming languages as they store data values to execute instructions. Similarly, in reasoning, keeping track of variables is crucial for maintaining state, passing data, and for general data manipulation tasks.

\ • Comments and docstrings: As human programmers can rely on the assistance of comments to better understand codes, we provide more detailed explanations on the intent of code via comments. Also, comments and docstrings can compensate the limitation when some semantics cannot be directly expressed with programming language.

B.3 Comparison to Related Work

Table 6 summarizes some related approaches to ours.

\ Table 6: A comparison of THINK-AND-EXECUTE to closely related prior approaches.

\

:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license.

:::

:::info Authors:

(1) Hyungjoo Chae, Yonsei University;

(2) Yeonghyeon Kim, Yonsei University;

(3) Seungone Kim, KAIST AI;

(4) Kai Tzu-iunn Ong, Yonsei University;

(5) Beong-woo Kwak, Yonsei University;

(6) Moohyeon Kim, Yonsei University;

(7) Seonghwan Kim, Yonsei University;

(8) Taeyoon Kwon, Yonsei University;

(9) Jiwan Chung, Yonsei University;

(10) Youngjae Yu, Yonsei University;

(11) Jinyoung Yeo, Yonsei University.

:::

\


This content originally appeared on HackerNoon and was authored by Transcompiler: Learn How to Translate Code


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