intermediate~3h
Verbalized Sampling: Fixing LLM Mode Collapse
A training-free prompting technique that restores an aligned LLM's response diversity by asking it to verbalize a probability distribution over several answers instead of committing to one.
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▶📚 Prerequisites(1)
🎓 Learning objectives
- •Explain why RLHF-aligned models suffer from mode collapse and how typicality bias causes it
- •Apply the Verbalized Sampling prompt pattern to recover pre-trained response diversity
- •Quantify the diversity/quality tradeoff using reported benchmark results
- •Combine Verbalized Sampling with temperature and top-p for further diversity gains
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