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 Plus annual

Presents the access of premium content as premium feature

Premium Content

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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Given a task, human learns from easy to hard, whereas the model learnsrandomly. Undeniably, difficulty insensitive learning leads to great success inNLP, but little attention has been paid to the effect of text difficulty inNLP. In this research, we propose the Human Learning Matching Index (HLM Index)to investigate the effect of text difficulty. Experiment results show: (1) LSTMhas more human-like learning behavior than BERT. (2) UID-SuperLinear gives thebest evaluation of text difficulty among four text difficulty criteria. (3)Among nine tasks, some tasks' performance is related to text difficulty,whereas some are not. (4) Model trained on easy data performs best in easy andmedium data, whereas trains on a hard level only perform well on hard data. (5)Training the model from easy to hard leads to fast convergence.

Text Difficulty Study: Do machines behave the same as humans regarding text difficulty?