{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T14:19:40Z","timestamp":1778768380708,"version":"3.51.4"},"reference-count":40,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100004106","name":"East China Normal University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004106","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Neurocomputing"],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1016\/j.neucom.2026.133756","type":"journal-article","created":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T16:05:17Z","timestamp":1776787517000},"page":"133756","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Dual-responder and dynamic dual-routing: LoRA-based safety\u2013availability synergy for large language models"],"prefix":"10.1016","volume":"686","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-9902-5381","authenticated-orcid":false,"given":"Tianhao","family":"Shen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"issue":"9","key":"10.1016\/j.neucom.2026.133756_bib0005","first-page":"696","article-title":"The intersection of AI safety, privacy, and trust: technical foundations for responsible AI systems","volume":"7","author":"Medapati","year":"2025","journal-title":"J. Comput. Sci. Technol. Stud."},{"key":"10.1016\/j.neucom.2026.133756_bib0010","author":"Cui"},{"key":"10.1016\/j.neucom.2026.133756_bib0015","author":"Xu"},{"key":"10.1016\/j.neucom.2026.133756_bib0020","series-title":"Proc. ACM Conf. On Fairness, Accountability, and Transparency","article-title":"Designing for responsible trust in AI systems: a communication perspective","author":"Liao","year":"2022"},{"key":"10.1016\/j.neucom.2026.133756_bib0025","author":"Bai"},{"key":"10.1016\/j.neucom.2026.133756_bib0030","author":"Gehman"},{"key":"10.1016\/j.neucom.2026.133756_bib0035","author":"Ganguli"},{"key":"10.1016\/j.neucom.2026.133756_bib0040","author":"Krause"},{"key":"10.1016\/j.neucom.2026.133756_bib0045","first-page":"1877","article-title":"Language models are few-shot learners","volume":"33","author":"Brown","year":"2020","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.neucom.2026.133756_bib0050","author":"Guan"},{"key":"10.1016\/j.neucom.2026.133756_bib0055","author":"Zou"},{"key":"10.1016\/j.neucom.2026.133756_bib0060","doi-asserted-by":"crossref","first-page":"278","DOI":"10.1016\/j.neucom.2022.04.020","article-title":"Adversarial attack and defense technologies in natural language processing: a survey","volume":"492","author":"Qiu","year":"2022","journal-title":"Neurocomputing"},{"key":"10.1016\/j.neucom.2026.133756_bib0065","series-title":"37th Conference on Neural Information Processing Systems (NeurIPS 2023), Track on Datasets and Benchmarks","article-title":"DecodingTrust: a comprehensive assessment of trustworthiness in GPT models","volume":"vol. 36","author":"Wang","year":"2023"},{"key":"10.1016\/j.neucom.2026.133756_bib0070","series-title":"2025 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML)","article-title":"Jailbreaking black box large language models in twenty queries","author":"Chao","year":"2025"},{"key":"10.1016\/j.neucom.2026.133756_bib0075","series-title":"Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","article-title":"On second thought, let\u2019s not think step by step! bias and toxicity in zero-shot reasoning","author":"Shaikh","year":"2023"},{"key":"10.1016\/j.neucom.2026.133756_bib0080","series-title":"Proceedings of the 2024 ACM SIGSAC Conference on Computer and Communications Security","article-title":"Do anything now: characterizing and evaluating in-the-wild jailbreak prompts on large language models","author":"Shen","year":"2024"},{"key":"10.1016\/j.neucom.2026.133756_bib0085","author":"Shah"},{"key":"10.1016\/j.neucom.2026.133756_bib0090","author":"Yu"},{"key":"10.1016\/j.neucom.2026.133756_bib0095","author":"Alon"},{"key":"10.1016\/j.neucom.2026.133756_bib0100","author":"Liu"},{"issue":"16","key":"10.1016\/j.neucom.2026.133756_bib0105","doi-asserted-by":"crossref","first-page":"7150","DOI":"10.3390\/app14167150","article-title":"Open Sesame! universal black-box jailbreaking of large language models","volume":"14","author":"Lapid","year":"2024","journal-title":"Appl. Sci."},{"key":"10.1016\/j.neucom.2026.133756_bib0110","author":"Touvron"},{"key":"10.1016\/j.neucom.2026.133756_bib0115","first-page":"27730","article-title":"Training language models to follow instructions with human feedback","volume":"35","author":"Ouyang","year":"2022","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.neucom.2026.133756_bib0120","first-page":"80079","article-title":"Jailbroken: how does LLM safety training fail?","volume":"36","author":"Wei","year":"2023","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.neucom.2026.133756_bib0125","author":"Zhang"},{"issue":"12","key":"10.1016\/j.neucom.2026.133756_bib0130","doi-asserted-by":"crossref","first-page":"1486","DOI":"10.1038\/s42256-023-00765-8","article-title":"Defending ChatGPT against jailbreak attack via self-reminders","volume":"5","author":"Xie","year":"2023","journal-title":"Nat. Mach. Intell."},{"key":"10.1016\/j.neucom.2026.133756_bib0135","author":"Jain"},{"issue":"12","key":"10.1016\/j.neucom.2026.133756_bib0140","article-title":"A holistic approach to undesired content detection in the real world","volume":"37","author":"Markov","year":"2023","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"10.1016\/j.neucom.2026.133756_bib0145","author":"Phute"},{"issue":"2","key":"10.1016\/j.neucom.2026.133756_bib0150","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3712061","article-title":"Supposititious sarcasm detection and sentiment analysis coping Hindi language in social networks harnessing Zipf-Mandelbrot probabilistic optimisation and perplexity entropy learning","volume":"24","author":"Pokhriyal","year":"2025","journal-title":"ACM Trans. Asian Low-Resour. Lang. Inf. Process."},{"key":"10.1016\/j.neucom.2026.133756_bib0155","series-title":"International Conference on Learning Representations","article-title":"LoRA: low-rank adaptation of large language models","author":"Hu","year":"2022"},{"key":"10.1016\/j.neucom.2026.133756_bib0160","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2025.130374","article-title":"MSLoRA: meta-learned scaling for adaptive fine-tuning of LoRA","volume":"643","author":"Luo","year":"2025","journal-title":"Neurocomputing"},{"key":"10.1016\/j.neucom.2026.133756_bib0165","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2025.130859","article-title":"Lora2: multi-scale low-rank approximations for fine-tuning large language models","volume":"650","author":"Zhang","year":"2025","journal-title":"Neurocomputing"},{"key":"10.1016\/j.neucom.2026.133756_bib0170","author":"Qi"},{"issue":"120","key":"10.1016\/j.neucom.2026.133756_bib0175","first-page":"1","article-title":"Switch transformers: scaling to trillion parameter models with simple and efficient sparsity","volume":"23","author":"Fedus","year":"2022","journal-title":"J. Mach. Learn. Res."},{"key":"10.1016\/j.neucom.2026.133756_bib0180","author":"Li"},{"issue":"6","key":"10.1016\/j.neucom.2026.133756_bib0185","article-title":"A hybrid autoencoder and gated recurrent unit model optimized by Honey Badger algorithm for enhanced cyber threat detection in IoT networks","volume":"8","author":"Addula","year":"2025","journal-title":"Secur. Priv."},{"issue":"3","key":"10.1016\/j.neucom.2026.133756_bib0190","first-page":"2600","article-title":"AttackBench: evaluating gradient-based attacks for adversarial examples","volume":"39","author":"Cin\u00e0","year":"2025","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"10.1016\/j.neucom.2026.133756_bib0195","author":"Lee"},{"key":"10.1016\/j.neucom.2026.133756_bib0200","author":"Li"}],"container-title":["Neurocomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231226011537?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231226011537?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T13:55:07Z","timestamp":1778766907000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0925231226011537"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":40,"alternative-id":["S0925231226011537"],"URL":"https:\/\/doi.org\/10.1016\/j.neucom.2026.133756","relation":{},"ISSN":["0925-2312"],"issn-type":[{"value":"0925-2312","type":"print"}],"subject":[],"published":{"date-parts":[[2026,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Dual-responder and dynamic dual-routing: LoRA-based safety\u2013availability synergy for large language models","name":"articletitle","label":"Article Title"},{"value":"Neurocomputing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.neucom.2026.133756","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"133756"}}