Two papers from our group were accepted at ACL 2022 workshops.
The first evaluates pre-trained encoders on low-resource named entity recognition across several English and German datasets, and finds that encoder performance varies enough that the choice of encoder needs to be evaluated per scenario. The second analyzes relation classification evaluation and argues that reporting F1 weightings other than micro-F1 tells us considerably more about model performance, particularly on imbalanced datasets.