Zhenjiang and Ani presented a poster with their work on chain-of-thought confidence with signal temporal logic at the Annual Nelms IoT Conference. The core idea of this research is to find patterns in LLM confidence that tend to correlate with correct and incorrect answers. Then, these patterns can be used to determine the confidence, i.e., the chance of the LLM providing the correct answer.
They were awarded the Most Innovative Poster Award by UF Innovate, which included a $500 cash prize. Congratulations!
In the meantime, a couple of other fun events happened around that time:
