Matches in SemOpenAlex for { <https://semopenalex.org/work/W4366683619> ?p ?o ?g. }
Showing items 1 to 91 of
91
with 100 items per page.
- W4366683619 endingPage "24" @default.
- W4366683619 startingPage "1" @default.
- W4366683619 abstract "This work presents the task of text polishing, which generates a sentence that is more graceful than the input sentence while retaining its semantic meaning. Text polishing has great value in real usage and is an important component in modern writing assistance systems. However, the task is still not well studied in the literature. Further research in this important direction requires more formal task definitions, benchmark datasets, and powerful baseline models. In this work, we formulate the task as a context-dependent text generation problem and conduct a case study on the text polishing with Chinese idiom. To circumvent the difficulties of task data annotation, we propose a semi-automatic data construction pipeline based on human-machine collaboration, and establish a large-scale text polishing dataset consisting of 1.5 million instances. We propose two types of task-specific pre-training objectives for the text polishing task and implement a series of Transformer-based models pre-trained on a massive Chinese corpus as baselines. We conduct extensive experiments with the baseline models on the constructed text polishing datasets and have some major findings. The human evaluation further reveals the polishing ability of the final system." @default.
- W4366683619 created "2023-04-24" @default.
- W4366683619 creator A5017377911 @default.
- W4366683619 creator A5078591720 @default.
- W4366683619 date "2023-06-19" @default.
- W4366683619 modified "2023-10-01" @default.
- W4366683619 title "Text Polishing with Chinese Idiom: Task, Datasets and Pre-trained Baselines" @default.
- W4366683619 cites W1975879668 @default.
- W4366683619 cites W2051593977 @default.
- W4366683619 cites W2481467102 @default.
- W4366683619 cites W2767608965 @default.
- W4366683619 cites W2963216553 @default.
- W4366683619 cites W2963631950 @default.
- W4366683619 cites W2978707643 @default.
- W4366683619 cites W3024131638 @default.
- W4366683619 cites W3034999214 @default.
- W4366683619 cites W3102725307 @default.
- W4366683619 cites W3103753836 @default.
- W4366683619 cites W3144320030 @default.
- W4366683619 cites W3210120707 @default.
- W4366683619 cites W3180439001 @default.
- W4366683619 doi "https://doi.org/10.1145/3593806" @default.
- W4366683619 hasPublicationYear "2023" @default.
- W4366683619 type Work @default.
- W4366683619 citedByCount "0" @default.
- W4366683619 crossrefType "journal-article" @default.
- W4366683619 hasAuthorship W4366683619A5017377911 @default.
- W4366683619 hasAuthorship W4366683619A5078591720 @default.
- W4366683619 hasBestOaLocation W43666836191 @default.
- W4366683619 hasConcept C111368507 @default.
- W4366683619 hasConcept C119599485 @default.
- W4366683619 hasConcept C12725497 @default.
- W4366683619 hasConcept C127313418 @default.
- W4366683619 hasConcept C127413603 @default.
- W4366683619 hasConcept C13280743 @default.
- W4366683619 hasConcept C138113353 @default.
- W4366683619 hasConcept C151730666 @default.
- W4366683619 hasConcept C154945302 @default.
- W4366683619 hasConcept C165801399 @default.
- W4366683619 hasConcept C185798385 @default.
- W4366683619 hasConcept C201995342 @default.
- W4366683619 hasConcept C204321447 @default.
- W4366683619 hasConcept C205649164 @default.
- W4366683619 hasConcept C2777530160 @default.
- W4366683619 hasConcept C2779343474 @default.
- W4366683619 hasConcept C2780451532 @default.
- W4366683619 hasConcept C41008148 @default.
- W4366683619 hasConcept C66322947 @default.
- W4366683619 hasConcept C78519656 @default.
- W4366683619 hasConcept C86803240 @default.
- W4366683619 hasConceptScore W4366683619C111368507 @default.
- W4366683619 hasConceptScore W4366683619C119599485 @default.
- W4366683619 hasConceptScore W4366683619C12725497 @default.
- W4366683619 hasConceptScore W4366683619C127313418 @default.
- W4366683619 hasConceptScore W4366683619C127413603 @default.
- W4366683619 hasConceptScore W4366683619C13280743 @default.
- W4366683619 hasConceptScore W4366683619C138113353 @default.
- W4366683619 hasConceptScore W4366683619C151730666 @default.
- W4366683619 hasConceptScore W4366683619C154945302 @default.
- W4366683619 hasConceptScore W4366683619C165801399 @default.
- W4366683619 hasConceptScore W4366683619C185798385 @default.
- W4366683619 hasConceptScore W4366683619C201995342 @default.
- W4366683619 hasConceptScore W4366683619C204321447 @default.
- W4366683619 hasConceptScore W4366683619C205649164 @default.
- W4366683619 hasConceptScore W4366683619C2777530160 @default.
- W4366683619 hasConceptScore W4366683619C2779343474 @default.
- W4366683619 hasConceptScore W4366683619C2780451532 @default.
- W4366683619 hasConceptScore W4366683619C41008148 @default.
- W4366683619 hasConceptScore W4366683619C66322947 @default.
- W4366683619 hasConceptScore W4366683619C78519656 @default.
- W4366683619 hasConceptScore W4366683619C86803240 @default.
- W4366683619 hasIssue "6" @default.
- W4366683619 hasLocation W43666836191 @default.
- W4366683619 hasOpenAccess W4366683619 @default.
- W4366683619 hasPrimaryLocation W43666836191 @default.
- W4366683619 hasRelatedWork W159132833 @default.
- W4366683619 hasRelatedWork W2758480492 @default.
- W4366683619 hasRelatedWork W2889111319 @default.
- W4366683619 hasRelatedWork W2946668189 @default.
- W4366683619 hasRelatedWork W3019278637 @default.
- W4366683619 hasRelatedWork W3186577291 @default.
- W4366683619 hasRelatedWork W4294661698 @default.
- W4366683619 hasRelatedWork W4304777330 @default.
- W4366683619 hasRelatedWork W4319453497 @default.
- W4366683619 hasRelatedWork W4385877744 @default.
- W4366683619 hasVolume "22" @default.
- W4366683619 isParatext "false" @default.
- W4366683619 isRetracted "false" @default.
- W4366683619 workType "article" @default.