{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T01:03:41Z","timestamp":1770771821847,"version":"3.50.0"},"reference-count":45,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"New Generation Artificial Intelligence-National Science and Technology Major Project","award":["2025ZD0123703"],"award-info":[{"award-number":["2025ZD0123703"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["92267107"],"award-info":[{"award-number":["92267107"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Key R&D Program of China","award":["2023YFB3308004"],"award-info":[{"award-number":["2023YFB3308004"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Comput. Biol. Bioinform."],"published-print":{"date-parts":[[2026,1]]},"DOI":"10.1109\/tcbbio.2025.3650547","type":"journal-article","created":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T18:37:53Z","timestamp":1767638273000},"page":"528-538","source":"Crossref","is-referenced-by-count":0,"title":["Efficient Tuning Framework for Resource- Constrained Biomedical Question Answering"],"prefix":"10.1109","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9851-5528","authenticated-orcid":false,"given":"Binrui","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Computer Science and Technology, Beijing University of Technology, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6867-2063","authenticated-orcid":false,"given":"Yongping","family":"Du","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Beijing University of Technology, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xingnan","family":"Jin","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Beijing University of Technology, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zikai","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Beijing University of Technology, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","article-title":"A survey of large language models","author":"Zhao","year":"2023"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3641289"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3571730"},{"key":"ref4","first-page":"578","article-title":"Do we still need clinical language models","volume-title":"Proc. ACM Conf. Health, Inference, Learn.","author":"Lehman"},{"key":"ref5","article-title":"A survey on large language models for critical societal domains: Finance, healthcare, and law","author":"Chen","year":"2024","journal-title":"Trans. Mach. Learn. Res."},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.24818\/ida-ql\/2019.5"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref8","article-title":"Improving language understanding by generative pre-training","author":"Radford","year":"2018"},{"issue":"1","key":"ref9","first-page":"5485","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":"ref10","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-024-03423-7"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2025.103347"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1259"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/W19-5006"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/W19-1909"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/d19-1371"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.bionlp-1.16"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/3458754"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.acl-long.551"},{"key":"ref19","first-page":"37309","article-title":"Deep bidirectional language-knowledge graph pretraining","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"35","author":"Yasunaga"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1093\/bib\/bbac409"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/3611651"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.2196\/70080"},{"key":"ref23","first-page":"2790","article-title":"Parameter-efficient transfer learning for NLP","volume-title":"Proc. Int. Conf. Mach. Learn","author":"Houlsby"},{"key":"ref24","article-title":"LoRA: Low-rank adaptation of large language models","volume-title":"Proc. Int. Conf. Learn. Representations (ICLR)","author":"Hu"},{"key":"ref25","article-title":"Adaptive budget allocation for parameter-efficient fine-tuning","volume-title":"Proc. 11th Int. Conf. Learn. Representations (ICLR)","author":"Zhang"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-long.353"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.acl-short.8"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/3560815"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.aiopen.2023.08.012"},{"key":"ref30","article-title":"CLEAR: Contrastive learning for sentence representation","author":"Wu","year":"2020"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.552"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-short.135"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1186\/s12859-015-0564-6"},{"key":"ref34","article-title":"Stanford CRFM introduces PubMedGPT 2.7 B","author":"Bolton","year":"2022"},{"key":"ref35","article-title":"PMC-LLaMA: Further finetuning LLaMA on medical papers","author":"Wu","year":"2023"},{"key":"ref36","article-title":"Capabilities of GPT-4 on medical challenge problems","author":"Nori","year":"2023"},{"issue":"70","key":"ref37","first-page":"1","article-title":"Scaling instruction-finetuned language models[J]","volume":"25","author":"Chung","year":"2024","journal-title":"J. Mach. Learn. Res."},{"key":"ref38","article-title":"Vicuna: An open-source chatbot impressing GPT-4 with 90 chatGPT quality","author":"Chiang","year":"2023"},{"key":"ref39","article-title":"Llama 2: Open foundation and fine-tuned chat models[J]","author":"Touvron","year":"2023"},{"key":"ref40","article-title":"Clinical Camel: An open expert-level medical language model with dialogue-based knowledge encoding","author":"Toma","year":"2023"},{"key":"ref41","article-title":"MEDITRON-70B: Scaling medical pretraining for large language models","author":"Chen","year":"2023"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.findings-acl.348"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.findings-acl.14"},{"key":"ref44","first-page":"10088","article-title":"QLoRA: Efficient finetuning of quantized LLMs","volume-title":"Proc Adv. Neural Inf. Process. Syst.","volume":"36","author":"Dettmers"},{"key":"ref45","article-title":"Reka Core, Flash, and Edge: A series of powerful multimodal language models","year":"2024"}],"container-title":["IEEE Transactions on Computational Biology and Bioinformatics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10723156\/11372637\/11328997.pdf?arnumber=11328997","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,9]],"date-time":"2026-02-09T21:04:22Z","timestamp":1770671062000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11328997\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1]]},"references-count":45,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/tcbbio.2025.3650547","relation":{},"ISSN":["2998-4165"],"issn-type":[{"value":"2998-4165","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1]]}}}