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

Chinese poetry is an important part of worldwide culture, and classical andmodern sub-branches are quite different. The former is a unique genre and hasstrict constraints, while the latter is very flexible in length, optional tohave rhymes, and similar to modern poetry in other languages. Thus, it requiresmore to control the coherence and improve the novelty. In this paper, wepropose a generate-retrieve-then-refine paradigm to jointly improve thecoherence and novelty. In the first stage, a draft is generated given keywords(i.e., topics) only. The second stage produces a "refining vector" fromretrieval lines. At last, we take into consideration both the draft and the"refining vector" to generate a new poem. The draft provides futuresentence-level information for a line to be generated. Meanwhile, the "refiningvector" points out the direction of refinement based on impressive wordsdetection mechanism which can learn good patterns from references and thencreate new ones via insertion operation. Experimental results on a collectedlarge-scale modern Chinese poetry dataset show that our proposed approach cannot only generate more coherent poems, but also improve the diversity andnovelty.

Compose Like Humans: Jointly Improving the Coherence and Novelty for Modern Chinese Poetry Generation