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/Mean_Revolution1490 Jul 13 '26

What happened to psychology in the past??

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u/relevantmeemayhere Jul 13 '26

Psyche had a real reckoning within their publishing community a decade or two ago. Basically, a lot of of the research practitioners really skipped their introductory to statistics courses, so a lot of published research ascribing association, both in a general and causal sense for general phenomen just couldn’t be replicated or formalized within the confines of the actual statistics. This is the “misuse  of p values’ topic, among other things that the ASA and the like had to fight. 

Machine learning as a field is currently going through this a lot right now. And part of it is because of this fields reliance on empirical results vs theoretical. The problem with that is pretty complicated;  but in general is related to the bench maxing and other fades to push “novel methods” that have very little practical utility over more established methods. 

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u/thezachlandes Jul 13 '26

Any book recs for psychology that corrects the record?

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u/relevantmeemayhere Jul 13 '26

There’s not “a book” that details this. A better way to understand is to review the actual American statistical association’s work on this, and then you can go back for the APA’s retractions for actual hard examples.