Direct Conclusion Generation with Hidden Reasoning

Single-Run Multi-Step Reasoning

Multi-Run Problem Decomposition for Complex Reasoning

Self-Refinement in LLMs

Predict-then-Verify Approaches in LLM Reasoning

Principle of Generating Longer Reasoning Paths

Modifying Decoding for Longer Reasoning Paths

Multi-Stage Generation for Incremental Reasoning

An engineer is building a system to solve complex logic puzzles. When a puzzle is submitted, the system sends a single, carefully crafted prompt to a large language model. The model's output is a complete, step-by-step explanation of how it solved the puzzle, followed by the final answer, all generated in one response. Which approach to multi-step reasoning does this system exemplify?

Prompting for a Reasoning Process to Mitigate Errors in Complex Tasks

Compositional Generalization in LLMs

Choosing a Reasoning Strategy for a Financial AI

You are designing systems that use a large language model to solve complex problems. Match each system description with the reasoning approach it employs.