{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T03:28:48Z","timestamp":1772767728484,"version":"3.50.1"},"reference-count":47,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"8","license":[{"start":{"date-parts":[[2025,8,1]],"date-time":"2025-08-01T00:00:00Z","timestamp":1754006400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,8,1]],"date-time":"2025-08-01T00:00:00Z","timestamp":1754006400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,8,1]],"date-time":"2025-08-01T00:00:00Z","timestamp":1754006400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Hong Kong Research Grants Council"},{"name":"General Research Fund","award":["PolyU 15200021"],"award-info":[{"award-number":["PolyU 15200021"]}]},{"name":"General Research Fund","award":["PolyU 15200023"],"award-info":[{"award-number":["PolyU 15200023"]}]},{"DOI":"10.13039\/501100000923","name":"Australian Research Council","doi-asserted-by":"publisher","award":["DP220103717"],"award-info":[{"award-number":["DP220103717"]}],"id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000923","name":"Australian Research Council","doi-asserted-by":"publisher","award":["LE220100078"],"award-info":[{"award-number":["LE220100078"]}],"id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Knowl. Data Eng."],"published-print":{"date-parts":[[2025,8]]},"DOI":"10.1109\/tkde.2025.3569585","type":"journal-article","created":{"date-parts":[[2025,5,13]],"date-time":"2025-05-13T13:48:13Z","timestamp":1747144093000},"page":"4564-4577","source":"Crossref","is-referenced-by-count":1,"title":["Educating Language Models as Promoters: Multi-Aspect Instruction Alignment With Self-Augmentation"],"prefix":"10.1109","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2212-9422","authenticated-orcid":false,"given":"Xueyao","family":"Sun","sequence":"first","affiliation":[{"name":"The Hong Kong Polytechnic University, Kowloon, Hong Kong"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3561-3627","authenticated-orcid":false,"given":"Kaize","family":"Shi","sequence":"additional","affiliation":[{"name":"University of Technology Sydney, Broadway, NSW, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0700-8710","authenticated-orcid":false,"given":"Haoran","family":"Tang","sequence":"additional","affiliation":[{"name":"The Hong Kong Polytechnic University, Kowloon, Hong Kong"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6880-7869","authenticated-orcid":false,"given":"Dingxian","family":"Wang","sequence":"additional","affiliation":[{"name":"University of Technology Sydney, Broadway, NSW, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4493-6663","authenticated-orcid":false,"given":"Guandong","family":"Xu","sequence":"additional","affiliation":[{"name":"The Education University of Hong Kong, Ting Kok, Hong Kong"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3370-471X","authenticated-orcid":false,"given":"Qing","family":"Li","sequence":"additional","affiliation":[{"name":"The Hong Kong Polytechnic University, Kowloon, Hong Kong"}]}],"member":"263","reference":[{"key":"ref1","article-title":"Scenario-based multi-product advertising copywriting generation for e-commerce","author":"Zhang","year":"2022"},{"key":"ref2","first-page":"870","article-title":"LLaMA-E: Empowering e-commerce authoring with object-interleaved instruction following","volume-title":"Proc. 31st Int. Conf. Comput. Linguistics","author":"Shi"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3603374"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1189"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330725"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.ecnlp-1.2"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1810.04805"},{"issue":"8","key":"ref9","first-page":"9","article-title":"Language models are unsupervised multitask learners","volume":"1","author":"Radford","year":"2019","journal-title":"OpenAI Blog"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.findings-acl.260"},{"key":"ref11","article-title":"LLaMA: Open and efficient foundation language models","author":"Touvron","year":"2023"},{"key":"ref12","article-title":"PaLM 2 technical report","author":"Anil","year":"2023"},{"issue":"140","key":"ref13","first-page":"1","article-title":"Exploring the limits of transfer learning with a unified text-to-text transformer","volume":"21","author":"Raffel","year":"2020","journal-title":"J. Mach. Learn. Res."},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acllong.353"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.acl-short.8"},{"issue":"2","key":"ref16","first-page":"3","article-title":"LoRA: Low-rank adaptation of large language models","volume-title":"Proc. Int. Conf. Learn. Representations","volume":"1","author":"Hu"},{"key":"ref17","article-title":"Finetuned language models are zero-shot learners","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Wei"},{"key":"ref18","first-page":"17506","article-title":"Pretraining language models with human preferences","volume-title":"Proc. 40th Int. Conf. Mach. Learn.","author":"Korbak"},{"key":"ref19","article-title":"Compressing long context for enhancing RAG with AMR-based concept distillation","author":"Shi","year":"2024"},{"key":"ref20","article-title":"Expert-guided extinction of toxic tokens for debiased generation","author":"Sun","year":"2024"},{"key":"ref21","article-title":"Goat: Fine-tuned LLaMA outperforms GPT-4 on arithmetic tasks","author":"Liu","year":"2023"},{"key":"ref22","article-title":"InstructUIE: Multi-task instruction tuning for unified information extraction","author":"Wang","year":"2023"},{"key":"ref23","article-title":"Radiology-LLaMA2: Best-in-class large language model for radiology","author":"Liu","year":"2023"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.7759\/cureus.40895"},{"key":"ref25","first-page":"1877","article-title":"Language models are few-shot learners","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Brown"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539171"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/3604915.3608857"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-long.383"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/3580488"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1145\/3523227.3546767"},{"key":"ref31","article-title":"M6-Rec: Generative pretrained language models are open-ended recommender systems","author":"Cui","year":"2022"},{"key":"ref32","article-title":"Chat-REC: Towards interactive and explainable LLMs-augmented recommender system","author":"Gao","year":"2023"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467206"},{"key":"ref34","article-title":"The curious case of neural text degeneration","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Holtzman"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1145\/3560815"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.acl-long.687"},{"key":"ref37","article-title":"Multitask prompted training enables zero-shot task generalization","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Sanh"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1525\/9780520940420-020"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/3077136.3080822"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/E17-1059"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1018"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.3115\/1073083.1073135"},{"key":"ref44","first-page":"74","article-title":"ROUGE: A package for automatic evaluation of summaries","volume-title":"Proc. Text Summarization Branches Out","author":"Lin"},{"key":"ref45","article-title":"BERTScore: Evaluating text generation with BERT","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Zhang"},{"key":"ref46","article-title":"Stanford alpaca: An instruction-following LLaMA model","author":"Taori","year":"2023"},{"key":"ref47","article-title":"Vicuna: An open-source chatbot impressing GPT-4 with 90% ChatGPT quality","year":"2023"}],"container-title":["IEEE Transactions on Knowledge and Data Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/69\/11072530\/11002714.pdf?arnumber=11002714","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,26]],"date-time":"2025-08-26T21:54:47Z","timestamp":1756245287000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11002714\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8]]},"references-count":47,"journal-issue":{"issue":"8"},"URL":"https:\/\/doi.org\/10.1109\/tkde.2025.3569585","relation":{},"ISSN":["1041-4347","1558-2191","2326-3865"],"issn-type":[{"value":"1041-4347","type":"print"},{"value":"1558-2191","type":"electronic"},{"value":"2326-3865","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8]]}}}