14 citations · 14 across the 2 of their papers we have counts for
3 papers
Eliciting and Learning with Soft Labels from Every Annotator
Katherine M. Collins, Umang Bhatt, Adrian Weller
The labels used to train machine learning (ML) models are of paramount importance. Typically for ML classification tasks, datasets contain hard labels, yet learning using soft labe…
Structured, flexible, and robust: benchmarking and improving large language models towards more human-like behavior in out-of-distribution reasoning tasks
Katherine M. Collins, Catherine Wong, Jiahai Feng +2
Human language offers a powerful window into our thoughts -- we tell stories, give explanations, and express our beliefs and goals through words. Abundant evidence also suggests th…
Hybrid Memoised Wake-Sleep: Approximate Inference at the Discrete-Continuous Interface
Tuan Anh Le, Katherine M. Collins, Luke Hewitt +4
Modeling complex phenomena typically involves the use of both discrete and continuous variables. Such a setting applies across a wide range of problems, from identifying trends in…