19 citations · 37 across the 7 of their papers we have counts for
19 papers
Does Typological Blinding Impede Cross-Lingual Sharing?
Johannes Bjerva, Isabelle Augenstein
Bridging the performance gap between high- and low-resource languages has been the focus of much previous work. Typological features from databases such as the World Atlas of Langu…
SIGTYP 2020 Shared Task: Prediction of Typological Features
Johannes Bjerva, Elizabeth Salesky, Sabrina J. Mielke +6
Typological knowledge bases (KBs) such as WALS (Dryer and Haspelmath, 2013) contain information about linguistic properties of the world's languages. They have been shown to be use…
Unsupervised Evaluation for Question Answering with Transformers
Lukas Muttenthaler, Isabelle Augenstein, Johannes Bjerva
It is challenging to automatically evaluate the answer of a QA model at inference time. Although many models provide confidence scores, and simple heuristics can go a long way towa…
SubjQA: A Dataset for Subjectivity and Review Comprehension
Johannes Bjerva, Nikita Bhutani, Behzad Golshan +2
Subjectivity is the expression of internal opinions or beliefs which cannot be objectively observed or verified, and has been shown to be important for sentiment analysis and word-…
Zero-Shot Cross-Lingual Transfer with Meta Learning
Farhad Nooralahzadeh, Giannis Bekoulis, Johannes Bjerva +1
Learning what to share between tasks has been a topic of great importance recently, as strategic sharing of knowledge has been shown to improve downstream task performance. This is…
Transductive Auxiliary Task Self-Training for Neural Multi-Task Models
Johannes Bjerva, Katharina Kann, Isabelle Augenstein
Multi-task learning and self-training are two common ways to improve a machine learning model's performance in settings with limited training data. Drawing heavily on ideas from th…