Least-to-Most Prompting
Least-to-most prompting is a problem-solving technique for LLMs designed for difficult reasoning problems that cannot be solved by simply generalizing from a few examples. The core strategy is to break down a complex problem into a progressive sequence of simpler sub-problems. These sub-problems are then solved sequentially, systematically leading to the final conclusion. This method provides a foundational framework for generating and solving sub-problems, which can be further enhanced with more advanced prompting techniques.
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Ch.3 Prompting - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
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Least-to-Most Prompting
A software team is tasked with creating a system that can solve complex, multi-step logic puzzles. They have access to a single, powerful, general-purpose Large Language Model. Their strategy is to first have the system break down a given puzzle into a series of simpler, solvable steps, and then solve each of those steps in sequence to arrive at the final answer.
Which of the following implementation plans best applies the principle of adapting a single model for the separate tasks of sub-problem generation and sub-problem solving?
Diagnosing and Improving an LLM-based Problem-Solving System
Adapting a Single LLM for Multi-Task Problem Solving
Learn After
Sub-problem Generation in Least-to-Most Prompting
Improving Least-to-Most Prompting with Advanced Techniques
Improving Problem Decomposition in Least-to-Most Prompting
An AI developer needs a large language model to solve a complex, multi-step logic puzzle that requires deducing a final answer from a series of interdependent clues. Initial attempts to solve the puzzle by providing the full puzzle and a few examples of other solved puzzles have consistently failed. Which of the following prompting strategies is the most effective next step, and why?
Analyzing a Problem-Solving Approach
A language model is tasked with solving the following logic puzzle: 'Sarah, David, and Emily are a doctor, a lawyer, and an engineer. The doctor is Emily's sister. David is not the lawyer.' To solve this complex problem, it is broken down into a series of simpler, sequential sub-problems. Arrange the following sub-problems in the correct logical order that builds towards the final solution.
Your team is rolling out an internal LLM assistant...
You’re building an internal LLM workflow to produc...
You’re building an internal LLM assistant to help ...
You’re leading an internal enablement team buildin...
Choosing and Justifying a Prompting Strategy Under Context and Quality Constraints
Designing a Prompting Workflow for a High-Stakes, Multi-Step Task
Diagnosing and Redesigning a Prompting Approach for a Decomposed Workflow
Stabilizing an LLM Workflow for Multi-Step Policy Compliance Decisions
Debugging a Multi-Step LLM Workflow for Contract Clause Risk Triage
Designing a Robust Prompting Workflow for Multi-Step Root-Cause Analysis with Limited Examples
Example of Final Problem Solving in Least-to-Most Prompting