William Jurayj

@williamjurayj.bsky.social

PhD student at Johns Hopkins CLSP (@jhuclsp.bsky.social). Researching natural and formal language processing. williamjurayj.com

JHU computer scientists including @williamjurayj.bsky.social propose a method that allows #AI models to spend more time thinking through problems & uses a confidence score to determine when the AI should say "I don't know" rather than risking a wrong answer, which is crucial for high-stakes domains.

Teaching AI to admit uncertainty

Johns Hopkins researchers show how different "odds" can teach AI models to admit when they're not confident enough in an answer

hub.jhu.edu

You can't just be right, you have to know you're right. Good advice for LLMs, according to new Johns Hopkins research. Sometimes no answer is better than a wrong one - life or death choices in medicine, for example, or big financial decisions. 🧵

a 3D graph with the X axis of compute budget, Y axis of accuracy, and Z axis of confidence threshold. The chart shows that accuracy increases with higher compute and confidence thresholds, though the trade-off tends to be fewer questions answered overall.

I noticed a lot of starter packs skewed towards faculty/industry, so I made one of just NLP & ML students: go.bsky.app/vju2ux Students do different research, go on the job market, and recruit other students. Ping me and I'll add you!

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