67 citations · 182 across the 30 of their papers we have counts for
13 papers · 1 filter
Cross-Modal Similarity-Based Curriculum Learning for Image Captioning
Hongkuan Zhang, Saku Sugawara, Akiko Aizawa +3
Image captioning models require the high-level generalization ability to describe the contents of various images in words. Most existing approaches treat the image-caption pairs eq…
Which Shortcut Solution Do Question Answering Models Prefer to Learn?
Kazutoshi Shinoda, Saku Sugawara, Akiko Aizawa
Question answering (QA) models for reading comprehension tend to learn shortcut solutions rather than the solutions intended by QA datasets. QA models that have learned shortcut so…
Penalizing Confident Predictions on Largely Perturbed Inputs Does Not Improve Out-of-Distribution Generalization in Question Answering
Kazutoshi Shinoda, Saku Sugawara, Akiko Aizawa
Question answering (QA) models are shown to be insensitive to large perturbations to inputs; that is, they make correct and confident predictions even when given largely perturbed…
Caching and Reproducibility: Making Data Science experiments faster and FAIRer
Moritz Schubotz, Ankit Satpute, Andre Greiner-Petter +2
Small to medium-scale data science experiments often rely on research software developed ad-hoc by individual scientists or small teams. Often there is no time to make the research…
Exploiting Transformer-based Multitask Learning for the Detection of Media Bias in News Articles
Timo Spinde, Jan-David Krieger, Terry Ruas +4
Media has a substantial impact on the public perception of events. A one-sided or polarizing perspective on any topic is usually described as media bias. One of the ways how bias i…
Debiasing Masks: A New Framework for Shortcut Mitigation in NLU
Johannes Mario Meissner, Saku Sugawara, Akiko Aizawa
Debiasing language models from unwanted behaviors in Natural Language Understanding tasks is a topic with rapidly increasing interest in the NLP community. Spurious statistical cor…