9 citations · 23 across the 16 of their papers we have counts for
5 papers · 1 filter
Label Errors in the Tobacco3482 Dataset
Gordon Lim, Stefan Larson, Kevin Leach
Tobacco3482 is a widely used document classification benchmark dataset. However, our manual inspection of the entire dataset uncovers widespread ontological issues, especially larg…
Towards Fair Pay and Equal Work: Imposing View Time Limits in Crowdsourced Image Classification
Gordon Lim, Stefan Larson, Yu Huang +1
Crowdsourcing is a common approach to rapidly annotate large volumes of data in machine learning applications. Typically, crowd workers are compensated with a flat rate based on an…
Robust Testing for Deep Learning using Human Label Noise
Gordon Lim, Stefan Larson, Kevin Leach
In deep learning (DL) systems, label noise in training datasets often degrades model performance, as models may learn incorrect patterns from mislabeled data. The area of Learning…
Document Classification using File Names
Zhijian Li, Stefan Larson, Kevin Leach
Rapid document classification is critical in several time-sensitive applications like digital forensics and large-scale media classification. Traditional approaches that rely on he…
Generating Hard-Negative Out-of-Scope Data with ChatGPT for Intent Classification
Zhijian Li, Stefan Larson, Kevin Leach
Intent classifiers must be able to distinguish when a user's utterance does not belong to any supported intent to avoid producing incorrect and unrelated system responses. Although…