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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
Related
Divide-and-Conquer Paradigm
Example of a Classification Task for LLMs: Identifying AI Risks in a Document
Approaches to Multi-Step Reasoning in LLMs
Two-Step Problem Decomposition
Dynamic Problem Decomposition for Complex Reasoning
Compositionality in NLP
Outlining as a Method of Problem Decomposition for Generative Tasks
General Framework of Problem Decomposition
Evaluating a Problem Decomposition Strategy for Multi-Hop QA
Illustrating the Need for Decomposition in Generative Tasks
Complex Reasoning Problems
Multi-hop Question Answering
A development team is building several applications powered by a large language model. Match each application's primary task with the most suitable strategy for breaking down the problem.
Debugging a Decomposition-Based LLM Workflow Using Recursive Sub-Problems and Contextual QA Pairs
Evaluating and Redesigning a Decomposition Workflow Under Context and Cost Constraints
Designing a Decomposition-and-QA-Pair Workflow for Contract Review with Recursive Escalation
Stabilizing a Decomposition-Based LLM Workflow for a Regulated Customer-Email Triage System
Designing a Decomposition Workflow for Root-Cause Analysis of a Production Incident
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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
Psychological Perspective on Problem Decomposition
Tool Use as Problem Decomposition in LLMs
Beyond computer science, the paradigm of problem decomposition has also been extensively explored in the field of ___.
Order the progression of problem decomposition when addressing an overall objective.
According to the general definition of problem decomposition, what is the primary operational benefit of breaking complex challenges into simpler sub-problems?
In the context of Natural Language Processing, what specific mechanism does problem decomposition enable Large Language Models to design in order to solve complex tasks?
Explain the paradigm of problem decomposition and its significance in Natural Language Processing. In your response, define the core approach of problem decomposition, identify the two academic disciplines that have extensively explored it, and describe how it is applied to enhance Large Language Models.
Decomposing a Complex Planning Task
A language model is tasked with generating a comprehensive report on the impact of remote work on employee productivity and well-being. Which of the following sets of sub-problems represents the most effective initial breakdown of this complex task to ensure a well-structured and complete final output?
Evaluating a Generated Problem Breakdown
You are building an internal LLM assistant to answ...
You are designing an internal LLM workflow to answ...
You’re building an internal LLM workflow to answer...
Evaluating and Redesigning a Decomposition Workflow Under Context and Cost Constraints
Debugging a Decomposition-Based LLM Workflow Using Recursive Sub-Problems and Contextual QA Pairs
Designing a Decomposition Workflow for Root-Cause Analysis of a Production Incident
Designing a Decomposition-and-QA-Pair Workflow for Contract Review with Recursive Escalation
Stabilizing a Decomposition-Based LLM Workflow for a Regulated Customer-Email Triage System
Dynamic Sub-Problem Generation