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Found 6 papers, 3 papers with code
Evaluating NLP Models via Contrast Sets
Unfortunately, when a dataset has systematic gaps (e. g., annotation artifacts), these evaluations are misleading: a model can learn simple decision rules that perform well on the test set but do not capture a dataset's intended capabilities.
Grounded Compositional Outputs for Adaptive Language Modeling
To our knowledge, the result is the first word-level language model with a size that does not depend on the training vocabulary.
Evaluating Models' Local Decision Boundaries via Contrast Sets
Unfortunately, when a dataset has systematic gaps (e. g., annotation artifacts), these evaluations are misleading: a model can learn simple decision rules that perform well on the test set but do not capture a dataset's intended capabilities.
Low-Resource Parsing with Crosslingual Contextualized Representations
Despite advances in dependency parsing, languages with small treebanks still present challenges.
Polyglot Contextual Representations Improve Crosslingual Transfer
We introduce Rosita, a method to produce multilingual contextual word representations by training a single language model on text from multiple languages.
Polyglot Semantic Role Labeling
Previous approaches to multilingual semantic dependency parsing treat languages independently, without exploiting the similarities between semantic structures across languages.
