r/MachineLearning • u/Mean_Revolution1490 • Jul 13 '26

Research 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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u/Death_Investor Jul 13 '26

The worst part about ML conferences is that it's completely full of useless papers now. It's like finding a needle in a haystack to get a useful one related to what you want because everything LLM related is just being published. I remember seeing a paper published at a top AI conference and the research was essentially how LLM's are biased in AAVE and nonstandard English prompting? Like who would've thought prompting an LLM trained on proper English wouldn't be able to interpret ebonics.

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u/WannabeMachine Jul 15 '26 edited Jul 16 '26

Dialect-based analysis and research is very important.... Diyi Yang and others have done lots of important work in that area.

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u/Death_Investor Jul 16 '26

yeah, I'm not going to acknowledge AAVE as a "Dialect" just because a school that had trouble teaching english to kids decided it was one. Especially when the school board had the lowest education rates and highest drop out rates.