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

In this paper, inspired by the successes of visionlanguage pre-trained modelsand the benefits from training with adversarial attacks, we present a noveltransformerbased cross-modal fusion modeling by incorporating the both notionsfor VQA challenge 2021. Specifically, the proposed model is on top of thearchitecture of VinVL model [19], and the adversarial training strategy [4] isapplied to make the model robust and generalized. Moreover, two implementationtricks are also used in our system to obtain better results. The experimentsdemonstrate that the novel framework can achieve 76.72% on VQAv2 test-std set.

A Transformer-based Cross-modal Fusion Model with Adversarial Training for VQA Challenge 2021