9 citations · 23 across the 16 of their papers we have counts for
5 papers · 1 filter
Evaluating Out-of-Distribution Performance on Document Image Classifiers
Stefan Larson, Gordon Lim, Yutong Ai +2
The ability of a document classifier to handle inputs that are drawn from a distribution different from the training distribution is crucial for robust deployment and generalizabil…
Augraphy: A Data Augmentation Library for Document Images
Alexander Groleau, Kok Wei Chee, Stefan Larson +2
This paper introduces Augraphy, a Python library for constructing data augmentation pipelines which produce distortions commonly seen in real-world document image datasets. Augraph…
K-ASTRO: Structure-Aware Adaptation of LLMs for Code Vulnerability Detection
Yifan Zhang, Michael Sandborn, Stefan Larson +2
Large Language Models (LLMs) are transforming software engineering tasks, including code vulnerability detection-a critical area of software security. However, existing methods oft…
A Survey of Intent Classification and Slot-Filling Datasets for Task-Oriented Dialog
Stefan Larson, Kevin Leach
Interest in dialog systems has grown substantially in the past decade. By extension, so too has interest in developing and improving intent classification and slot-filling models,…
Redwood: Using Collision Detection to Grow a Large-Scale Intent Classification Dataset
Stefan Larson, Kevin Leach
Dialog systems must be capable of incorporating new skills via updates over time in order to reflect new use cases or deployment scenarios. Similarly, developers of such ML-driven…