2 citations · 2 across the 2 of their papers we have counts for
2 papers
stat.ML2024
Conformalized Credal Regions for Classification with Ambiguous Ground Truth
Michele Caprio, David Stutz, Shuo Li +1
An open question in \emph{Imprecise Probabilistic Machine Learning} is how to empirically derive a credal region (i.e., a closed and convex family of probabilities on the output sp…
cs.LG2024★ 2 cited
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…