Designing queries or instructions to optimize LLM or VLM performance in multimodal tasks.
Prompt engineering involves crafting queries or instructions to guide large language models (LLMs) or vision-language models (VLMs) in generating desired outputs. This process optimizes model performance by providing clear and contextually relevant prompts.
Effective prompt engineering requires understanding model behavior and capabilities. Techniques include using specific keywords, providing context, and iteratively refining prompts to achieve optimal results.
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