The researchers identified three feasible prompting techniques for LLMs: 1) zero-shot prompting, where the task is based on natural language and entered in a single description at the time of inference without examples; 2) few-shot prompting, where task examples including context and results are provided to support the LLM; and 3) chain-of-thought prompting, where examples of the underlying thought process are provided to guide the model through reasoning steps.

Authors

• Person: Benedikt Reitemeyer, Hans-Georg Fill Organization: arXiv
  Applying Large Language Models in Knowledge Graph-based ...

Sources

• Applying Large Language Models in Knowledge Graph-based ... arxiv.org Benedikt Reitemeyer, Hans-Georg Fill · arXiv via serper

Referenced by nodes (1)

• chain-of-thought concept