{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T21:14:26Z","timestamp":1740172466390,"version":"3.37.3"},"reference-count":38,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"National Key R&D Program of China","award":["2023ZD0506501","2021YFC2500803"],"award-info":[{"award-number":["2023ZD0506501","2021YFC2500803"]}]},{"name":"Ningxia Key R&D Program of China","award":["2023BEG02064"],"award-info":[{"award-number":["2023BEG02064"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82071171"],"award-info":[{"award-number":["82071171"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"BUPT Excellent Ph.D. Students Foundation","award":["CX2021122"],"award-info":[{"award-number":["CX2021122"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE\/ACM Trans. Audio Speech Lang. Process."],"published-print":{"date-parts":[[2024]]},"DOI":"10.1109\/taslp.2024.3473308","type":"journal-article","created":{"date-parts":[[2024,10,2]],"date-time":"2024-10-02T18:25:55Z","timestamp":1727893555000},"page":"4409-4419","source":"Crossref","is-referenced-by-count":0,"title":["Graph-Based Cross-Granularity Message Passing on Knowledge-Intensive Text"],"prefix":"10.1109","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9019-1063","authenticated-orcid":false,"given":"Chenwei","family":"Yan","sequence":"first","affiliation":[{"name":"Beijing University of Posts and Telecommunications and Key Laboratory of Trustworthy Distributed Computing and Service (BUPT), Ministry of Education, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1492-2829","authenticated-orcid":false,"given":"Xiangling","family":"Fu","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications and Key Laboratory of Trustworthy Distributed Computing and Service (BUPT), Ministry of Education, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinxin","family":"You","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Tsinghua University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6170-726X","authenticated-orcid":false,"given":"Ji","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Tsinghua University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9054-0523","authenticated-orcid":false,"given":"Xien","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Tsinghua University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"crossref","first-page":"6244","DOI":"10.18653\/v1\/2020.acl-main.556","article-title":"Multi-granularity interaction network for extractive and abstractive multi-document summarization","volume-title":"Proc. 58th Annu. Meeting Assoc. Comput. Linguistics","author":"Jin","year":"2020"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-021-01614-0"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531772"},{"key":"ref4","first-page":"1040","article-title":"A lexicon-based graph neural network for Chinese NER","volume-title":"Proc. Conf. Empirical Methods Natural Lang. Process. 9th Int. Joint Conf. Natural Lang. Process.","author":"Gui","year":"2019"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33017370"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"334","DOI":"10.18653\/v1\/2020.acl-main.31","article-title":"Every document owns its structure: Inductive text classification via graph neural networks","volume-title":"Proc. 58th Annu. Meeting Assoc. Comput. Linguistics","author":"Zhang","year":"2020"},{"key":"ref7","first-page":"1554","article-title":"Chinese NER using lattice LSTM","volume-title":"Proc. 56th Annu. Meeting Assoc. Comput. Linguistics","author":"Zhang","year":"2018"},{"key":"ref8","doi-asserted-by":"crossref","first-page":"1430","DOI":"10.18653\/v1\/P19-1138","article-title":"Multi-grained named entity recognition","volume-title":"Proc. 57th Annu. Meeting Assoc. Comput. Linguistics","author":"Xia","year":"2019"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/3591106.3592253"},{"key":"ref10","doi-asserted-by":"crossref","first-page":"5951","DOI":"10.18653\/v1\/2020.acl-main.528","article-title":"Simplify the usage of lexicon in Chinese NER","volume-title":"Proc. 58th Annu. Meeting Assoc. Comput. Linguistics","author":"Ma","year":"2020"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3474085.3475369"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/jbhi.2020.3048700"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1186\/s12911-019-0781-4"},{"key":"ref14","first-page":"3111","article-title":"Distributed representations of words and phrases and their compositionality","volume-title":"Proc. Conf. Neural Inf. Process. Syst.","author":"Tomas","year":"2013"},{"key":"ref15","first-page":"1532","article-title":"GloVe: Global vectors for word representation","volume-title":"Proc. Conf. Empirical Methods Natural Lang. Process.","author":"Pennington","year":"2014"},{"key":"ref16","first-page":"1746","article-title":"Convolutional neural networks for sentence classification","volume-title":"Proc. Conf. Empirical Methods Natural Lang. Process.","author":"Kim","year":"2014"},{"key":"ref17","first-page":"1197","article-title":"Long short-term memory neural networks for Chinese word segmentation","volume-title":"Proc. Conf. Empirical Methods Natural Lang. Process.","author":"Chen","year":"2015"},{"key":"ref18","first-page":"207","article-title":"Attention-based bidirectional long short-term memory networks for relation classification","volume-title":"Proc. 54th Annu. Meeting Assoc. Comput. Linguistics","author":"Zhou","year":"2016"},{"key":"ref19","article-title":"Gated graph sequence neural networks","volume-title":"Proc. 4th Int. Conf. Learn. Representations","author":"Li","year":"2016"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3186005"},{"key":"ref21","doi-asserted-by":"crossref","first-page":"3308","DOI":"10.18653\/v1\/P19-1320","article-title":"Incorporating syntactic and semantic information in word embeddings using graph convolutional networks","volume-title":"Proc. 57th Annu. Meeting Assoc. Comput. Linguistics","author":"Vashishth","year":"2019"},{"key":"ref22","first-page":"4171","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","volume-title":"Proc. Conf. North Amer. Chapter Assoc. Comput. Linguistics: Hum. Lang. Technol.","author":"Devlin","year":"2019"},{"journal-title":"XLNet: Generalized Autoregressive Pretraining for Language Understanding","year":"2019","author":"Yang","key":"ref23"},{"article-title":"Conceptualized representation learning for chinese biomedical text mining","year":"2020","author":"Zhang","key":"ref24"},{"key":"ref25","doi-asserted-by":"crossref","first-page":"421","DOI":"10.18653\/v1\/2021.findings-acl.37","article-title":"AMBERT: A pre-trained language model with multi-grained tokenization","volume-title":"Proc. Findings Assoc. Comput. Linguistics: ACL-IJCNLP","author":"Zhang","year":"2021"},{"key":"ref26","first-page":"4729","article-title":"ZEN: Pre-training chinese text encoder enhanced by N-gram representations","volume-title":"Proc. Findings Assoc. Comput. Linguistics: EMNLP","author":"Diao","year":"2020"},{"key":"ref27","first-page":"2532","article-title":"Comparison of the impact of word segmentation on name tagging for Chinese and Japanese","volume-title":"Proc. Ninth Int. Conf. Lang. Resour. Eval.","author":"Li","year":"2014"},{"key":"ref28","first-page":"3274","article-title":"Condensed memory networks for clinical diagnostic inferencing","volume-title":"Proc. 31st AAAI Conf. Artif. Intell.","author":"Prakash","year":"2017"},{"key":"ref29","first-page":"1","article-title":"Graph attention networks","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Velikovi","year":"2018"},{"key":"ref30","article-title":"Adam: A method for stochastic optimization","volume-title":"Proc. 3rd Int. Conf. Learn. Representations","author":"Kingma","year":"2015"},{"key":"ref31","first-page":"440","article-title":"Baseline needs more love: On simple word-embedding-based models and associated pooling mechanisms","volume-title":"Proc. 56th Annu. Meeting Assoc. Comput. Linguistics","author":"Shen","year":"2018"},{"key":"ref32","first-page":"427","article-title":"Bag of tricks for efficient text classification","volume-title":"Proc. 15th Conf. Eur. Chapter Assoc. Comput. Linguistics","author":"Joulin","year":"2017"},{"key":"ref33","first-page":"2873","article-title":"Recurrent neural network for text classification with multi-task learning","volume-title":"Proc. 25th Int. Joint Conf. Artif. Intell.","author":"Liu","year":"2016"},{"key":"ref34","first-page":"562","article-title":"Deep pyramid convolutional neural networks for text categorization","volume-title":"Proc. 55th Annu. Meeting Assoc. Comput. Linguistics","author":"Johnson","year":"2017"},{"key":"ref35","first-page":"2321","article-title":"Joint embedding of words and labels for text classification","volume-title":"Proc. 56th Annu. Meeting Assoc. Comput. Linguistics","author":"Wang","year":"2018"},{"key":"ref36","article-title":"Attention is all you need","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"30","author":"Vaswani","year":"2017"},{"key":"ref37","first-page":"172","article-title":"This patient looks like that patient: Prototypical networks for interpretable diagnosis prediction from clinical text","volume-title":"Proc. 2nd Conf. Asia-Pacific Chapter Assoc. Comput. Linguistics 12th Int. Joint Conf. Natural Lang. Process.","author":"Aken","year":"2022"},{"key":"ref38","first-page":"6810","article-title":"low-resource text classification: A parameter-free classification method with compressors","volume-title":"Proc. Findings Assoc. Comput. Linguistics","author":"Jiang","year":"2023"}],"container-title":["IEEE\/ACM Transactions on Audio, Speech, and Language Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6570655\/10304349\/10704050.pdf?arnumber=10704050","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,14]],"date-time":"2024-10-14T17:26:15Z","timestamp":1728926775000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10704050\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":38,"URL":"https:\/\/doi.org\/10.1109\/taslp.2024.3473308","relation":{},"ISSN":["2329-9290","2329-9304"],"issn-type":[{"type":"print","value":"2329-9290"},{"type":"electronic","value":"2329-9304"}],"subject":[],"published":{"date-parts":[[2024]]}}}