Encoding
prompt compression
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Description
Encoding methods compress long textual prompts into compact vector representations that are more accessible to LLMs and reduce inference costs. Techniques include tuning language models to generate summary vectors or 'nuggets' that capture essential semantic and contextual information while reducing length and complexity for efficient prompting.