English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

We combine character-level and contextual language model representations toimprove performance on Discourse Representation Structure parsing. Characterrepresentations can easily be added in a sequence-to-sequence model in eitherone encoder or as a fully separate encoder, with improvements that are robustto different language models, languages and data sets. For English, theseimprovements are larger than adding individual sources of linguisticinformation or adding non-contextual embeddings. A new method of analysis basedon semantic tags demonstrates that the character-level representations improveperformance across a subset of selected semantic phenomena.

Character-level Representations Improve DRS-based Semantic Parsing Even in the Age of BERT