103 citations · 179 across the 8 of their papers we have counts for
3 papers · 1 filter
A Cheap Verifier is Good Enough: LLM Post-training is Robust to Erroneous Rewards
Andreas Plesner, Curtis Northcutt, Francisco Guzmán +1
When post-training large language models on tasks with semi-verifiable rewards, there are many factors (training steps, base model size, training order, data quality, verifier accu…
DMLR: Data-centric Machine Learning Research -- Past, Present and Future
Luis Oala, Manil Maskey, Lilith Bat-Leah +35
Drawing from discussions at the inaugural DMLR workshop at ICML 2023 and meetings prior, in this report we outline the relevance of community engagement and infrastructure developm…
Identifying Incorrect Annotations in Multi-Label Classification Data
Aditya Thyagarajan, Elías Snorrason, Curtis Northcutt +1
In multi-label classification, each example in a dataset may be annotated as belonging to one or more classes (or none of the classes). Example applications include image (or docum…