3 citations · 8 across the 5 of their papers we have counts for
5 papers
To Believe or Not to Believe Your LLM
Yasin Abbasi Yadkori, Ilja Kuzborskij, András György +1
We explore uncertainty quantification in large language models (LLMs), with the goal to identify when uncertainty in responses given a query is large. We simultaneously consider bo…
Mitigating LLM Hallucinations via Conformal Abstention
Yasin Abbasi Yadkori, Ilja Kuzborskij, David Stutz +9
We develop a principled procedure for determining when a large language model (LLM) should abstain from responding (e.g., by saying "I don't know") in a general domain, instead of…
Better-than-KL PAC-Bayes Bounds
Ilja Kuzborskij, Kwang-Sung Jun, Yulian Wu +2
Let be a sequence of random elements, where is a fixed scalar function, are independent random variables (data), and i…
Mixture Weight Estimation and Model Prediction in Multi-source Multi-target Domain Adaptation
Yuyang Deng, Ilja Kuzborskij, Mehrdad Mahdavi
We consider the problem of learning a model from multiple heterogeneous sources with the goal of performing well on a new target distribution. The goal of learner is to mix these d…
Tighter PAC-Bayes Bounds Through Coin-Betting
Kyoungseok Jang, Kwang-Sung Jun, Ilja Kuzborskij +1
We consider the problem of estimating the mean of a sequence of random elements where is a fixed scalar function, ar…