3260 papers • 126 benchmarks • 313 datasets
Identifiy the scope of a speculation cue that indicates uncertainty in a given text.
(Image credit: Papersgraph)
These leaderboards are used to track progress in speculation-scope-resolution-9
Use these libraries to find speculation-scope-resolution-9 models and implementations
No subtasks available.
Three popular transformer-based architectures, BERT, XLNet and RoBERTa are applied to negation detection and scope resolution, on two publicly available datasets, BioScope Corpus and SFU Review Corpus, reporting substantial improvements over previously reported results.
It is shown that this Multitask Learning approach outperforms the single task learning approach, and new state-of-the-art results on Negation and Speculation Scope Resolution on the BioScope Corpus and the SFU Review Corpus are reported.
Adding a benchmark result helps the community track progress.