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

The issue of shortcut learning is widely known in NLP and has been animportant research focus in recent years. Unintended correlations in the dataenable models to easily solve tasks that were meant to exhibit advancedlanguage understanding and reasoning capabilities. In this survey paper, wefocus on the field of machine reading comprehension (MRC), an important taskfor showcasing high-level language understanding that also suffers from a rangeof shortcuts. We summarize the available techniques for measuring andmitigating shortcuts and conclude with suggestions for further progress inshortcut research. Importantly, we highlight two concerns for shortcutmitigation in MRC: (1) the lack of public challenge sets, a necessary componentfor effective and reusable evaluation, and (2) the lack of certain mitigationtechniques that are prominent in other areas.

A Survey on Measuring and Mitigating Reasoning Shortcuts in Machine Reading Comprehension