•1 min read•from Machine Learning
Prompt-engineering paper accepted to ICML [R]
"Verbalized Sampling: How to Mitigate Mode Collapse and Unlock LLM Diversity"
This paper was accepted to ICML this year. Its main idea is a very simple prompt-engineering trick: "changing the prompt this way led to more diverse sampling". Naturally, it is difficult to provide a rigorous theoretical analysis for something like this.
Even if it works, I’m not sure this kind of prompt engineering belongs at a top-tier machine learning conference. Some people seems to call this kind of work “modern machine learning”, but I think it should be categorized as less technical venues.
How do you think? Am I being too rigid?
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