{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T07:17:23Z","timestamp":1767683843799,"version":"3.48.0"},"reference-count":51,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T00:00:00Z","timestamp":1767657600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T00:00:00Z","timestamp":1767657600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100018542","name":"Natural Science Foundation of Sichuan Province","doi-asserted-by":"publisher","award":["2022NSFSC0571"],"award-info":[{"award-number":["2022NSFSC0571"]}],"id":[{"id":"10.13039\/501100018542","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100012542","name":"Sichuan Provincial Science and Technology Support Program","doi-asserted-by":"publisher","award":["2018JY0273"],"award-info":[{"award-number":["2018JY0273"]}],"id":[{"id":"10.13039\/100012542","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004543","name":"China Scholarship Council","doi-asserted-by":"publisher","award":["201908510026"],"award-info":[{"award-number":["201908510026"]}],"id":[{"id":"10.13039\/501100004543","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Supercomput"],"DOI":"10.1007\/s11227-025-08194-7","type":"journal-article","created":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T07:13:33Z","timestamp":1767683613000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Complementary perspectives enhancement via hierarchical graph networks for multimodal fake news detection"],"prefix":"10.1007","volume":"82","author":[{"given":"Zhijian","family":"Huang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenbin","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,1,6]]},"reference":[{"key":"8194_CR1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2945521","volume":"240","author":"Y Wang","year":"2019","unstructured":"Wang Y, McKee M, Torbica A, Stuckler D (2019) Systematic literature review on the spread of health-related misinformation on social media. Social sci Med 240:112552. https:\/\/doi.org\/10.1109\/TMI.2019.2945521","journal-title":"Social sci Med"},{"key":"8194_CR2","doi-asserted-by":"publisher","unstructured":"Fox B (2018) Making the headlines: Eu immigration to the uk and the wave of new racism after brexit. Migration and crime: realities and media representations, 87\u2013107. https:\/\/doi.org\/10.1007\/978-3-319-95813-2_5","DOI":"10.1007\/978-3-319-95813-2_5"},{"issue":"1","key":"8194_CR3","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1186\/s40854-021-00271-z","volume":"7","author":"B Fong","year":"2021","unstructured":"Fong B (2021) Analysing the behavioural finance impact of\u2019fake news\u2019 phenomena on financial markets: a representative agent model and empirical validation. Financial Innov 7(1):53. https:\/\/doi.org\/10.1186\/s40854-021-00271-z","journal-title":"Financial Innov"},{"issue":"1","key":"8194_CR4","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1145\/3137597.3137600","volume":"19","author":"K Shu","year":"2017","unstructured":"Shu K, Sliva A, Wang S, Tang J, Liu H (2017) Fake news detection on social media: A data mining perspective. ACM SIGKDD Explorations Newsl 19(1):22\u201336. https:\/\/doi.org\/10.1145\/3137597.3137600","journal-title":"ACM SIGKDD Explorations Newsl"},{"key":"8194_CR5","doi-asserted-by":"publisher","unstructured":"Nikopensius G, Mayank M, Phukan OC, Sharma R (2023) Reinforcement learning-based knowledge graph reasoning for explainable fact-checking. In: Proceedings of the International Conference on Advances in Social Networks Analysis and Mining, pp 164\u2013170. https:\/\/doi.org\/10.1145\/3625007.3627593","DOI":"10.1145\/3625007.3627593"},{"key":"8194_CR6","doi-asserted-by":"publisher","unstructured":"Mayank M, Sharma S, Sharma R (2022) Deap-faked: Knowledge graph based approach for fake news detection. In: 2022 IEEE\/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 47\u201351. IEEE. https:\/\/doi.org\/10.1109\/ASONAM55673.2022.10068653","DOI":"10.1109\/ASONAM55673.2022.10068653"},{"key":"8194_CR7","doi-asserted-by":"publisher","unstructured":"Singhal S, Shah RR, Chakraborty T, Kumaraguru P, Satoh S (2019) Spotfake: A multi-modal framework for fake news detection. In: 2019 IEEE Fifth International Conference on Multimedia Big Data (BigMM), pp. 39\u201347. IEEE. https:\/\/doi.org\/10.1109\/BigMM.2019.00-44","DOI":"10.1109\/BigMM.2019.00-44"},{"key":"8194_CR8","doi-asserted-by":"publisher","unstructured":"Singhal S, Kabra A, Sharma M, Shah RR, Chakraborty T, Kumaraguru P (2020) Spotfake+: A multimodal framework for fake news detection via transfer learning (student abstract). In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34, pp. 13915\u201313916. https:\/\/doi.org\/10.1609\/aaai.v34i10.7230","DOI":"10.1609\/aaai.v34i10.7230"},{"key":"8194_CR9","doi-asserted-by":"publisher","unstructured":"Khattar D, Goud JS, Gupta M, Varma V (2019) Mvae: Multimodal variational autoencoder for fake news detection. In: The World Wide Web Conference, pp. 2915\u20132921. https:\/\/doi.org\/10.1145\/3308558.3313552","DOI":"10.1145\/3308558.3313552"},{"key":"8194_CR10","doi-asserted-by":"publisher","unstructured":"Wang Y, Ma F, Jin Z, Yuan Y, Xun G, Jha K, Su L, Gao J (2018) Eann: Event adversarial neural networks for multi-modal fake news detection. In: Proceedings of the 24th Acm Sigkdd International Conference on Knowledge Discovery & Data Mining, pp 849\u2013857. https:\/\/doi.org\/10.1145\/3219819.3219903","DOI":"10.1145\/3219819.3219903"},{"key":"8194_CR11","doi-asserted-by":"publisher","unstructured":"Chen Y, Li D, Zhang P, Sui J, Lv Q, Tun L, Shang L (2022) Cross-modal ambiguity learning for multimodal fake news detection. In: Proceedings of the ACM Web Conference 2022, pp 2897\u20132905. https:\/\/doi.org\/10.1145\/3485447.3511968","DOI":"10.1145\/3485447.3511968"},{"key":"8194_CR12","doi-asserted-by":"publisher","DOI":"10.1016\/j.csi.2023.103822","volume":"89","author":"H Yang","year":"2024","unstructured":"Yang H, Zhang J, Zhang L, Cheng X, Hu Z (2024) Mran: Multimodal relationship-aware attention network for fake news detection. Comput Standards Interf 89:103822. https:\/\/doi.org\/10.1016\/j.csi.2023.103822","journal-title":"Comput Standards Interf"},{"issue":"1","key":"8194_CR13","doi-asserted-by":"publisher","first-page":"299","DOI":"10.1007\/s11227-024-06815-1","volume":"81","author":"Y Zhang","year":"2025","unstructured":"Zhang Y, Ma J, Jia Y (2025) Mcan: multimodal cross-aware network for fake news detection by extracting semantic-physical feature consistency. J Supercomput 81(1):299. https:\/\/doi.org\/10.1007\/s11227-024-06815-1","journal-title":"J Supercomput"},{"key":"8194_CR14","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2024.102500","volume":"111","author":"B Wang","year":"2024","unstructured":"Wang B, Li X, Li C, Wang S, Gao W (2024) Escaping the neutralization effect of modality features fusion in multimodal fake news detection. Inf Fusion 111:102500. https:\/\/doi.org\/10.1016\/j.inffus.2024.102500","journal-title":"Inf Fusion"},{"issue":"1","key":"8194_CR15","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1109\/TKDE.2023.3280555","volume":"36","author":"L Wu","year":"2023","unstructured":"Wu L, Liu P, Zhao Y, Wang P, Zhang Y (2023) Human cognition-based consistency inference networks for multi-modal fake news detection. IEEE Trans Knowl Data Eng 36(1):211\u2013225. https:\/\/doi.org\/10.1109\/TKDE.2023.3280555","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"8194_CR16","doi-asserted-by":"publisher","unstructured":"Zhou X, Wu J, Zafarani R (2020) Similarity-aware multi-modal fake news detection. In: Pacific-Asia Conference on Knowledge Discovery and Data Mining, pp. 354\u2013367. Springer. https:\/\/doi.org\/10.1007\/978-3-030-47436-2_27","DOI":"10.1007\/978-3-030-47436-2_27"},{"key":"8194_CR17","doi-asserted-by":"publisher","unstructured":"Devlin J, Chang M-W, Lee K, Toutanova K (2019) Bert: Pre-training of deep bidirectional transformers for language understanding. In: Proceedings of NAACL-HLT, pp. 4171\u20134186. https:\/\/doi.org\/10.18653\/v1\/N19-1423","DOI":"10.18653\/v1\/N19-1423"},{"key":"8194_CR18","doi-asserted-by":"publisher","unstructured":"Zhang Q, Liu J, Zhang F, Xie J, Zha Z-J (2023) Hierarchical semantic enhancement network for multimodal fake news detection. In: Proceedings of the 31st ACM International Conference on Multimedia, pp 3424\u20133433. https:\/\/doi.org\/10.1145\/3581783.3612423","DOI":"10.1145\/3581783.3612423"},{"issue":"15","key":"8194_CR19","doi-asserted-by":"publisher","first-page":"1394","DOI":"10.1007\/s11227-025-07860-0","volume":"81","author":"F You","year":"2025","unstructured":"You F, Ding M, Luo H, Ma Y, Li H (2025) Profnse: propagation dynamics-derived fake news detection in social networks: F. you et al. J Supercomput 81(15):1394. https:\/\/doi.org\/10.1007\/s11227-025-07860-0","journal-title":"J Supercomput"},{"key":"8194_CR20","doi-asserted-by":"publisher","unstructured":"Bhutani B, Rastogi N, Sehgal P, Purwar A (2019) Fake news detection using sentiment analysis. In: 2019 Twelfth International Conference on Contemporary Computing (IC3), pp. 1\u20135. IEEE. https:\/\/doi.org\/10.1109\/IC3.2019.8844880","DOI":"10.1109\/IC3.2019.8844880"},{"key":"8194_CR21","doi-asserted-by":"publisher","unstructured":"Rashkin H, Choi E, Jang JY, Volkova S, Choi Y (2017) Truth of varying shades: Analyzing language in fake news and political fact-checking. In: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pp. 2931\u20132937. https:\/\/doi.org\/10.18653\/v1\/D17-1317","DOI":"10.18653\/v1\/D17-1317"},{"key":"8194_CR22","unstructured":"Qazvinian V, Rosengren E, Radev D, Mei Q (2011) Rumor has it: Identifying misinformation in microblogs. In: Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, pp 1589\u20131599"},{"key":"8194_CR23","doi-asserted-by":"publisher","unstructured":"Yang F, Liu Y, Yu X, Yang M (2012) Automatic detection of rumor on sina weibo. In: Proceedings of the ACM SIGKDD Workshop on Mining Data Semantics, pp 1\u20137. https:\/\/doi.org\/10.1145\/2350190.2350203","DOI":"10.1145\/2350190.2350203"},{"key":"8194_CR24","doi-asserted-by":"publisher","unstructured":"Castillo C, Mendoza M, Poblete B (2011) Information credibility on twitter. In: Proceedings of the 20th International Conference on World Wide Web, pp 675\u2013684. https:\/\/doi.org\/10.1145\/1963405.1963500","DOI":"10.1145\/1963405.1963500"},{"key":"8194_CR25","doi-asserted-by":"publisher","unstructured":"Gupta A, Lamba H, Kumaraguru P, Joshi A (2013) Faking sandy: characterizing and identifying fake images on twitter during hurricane sandy. In: Proceedings of the 22nd International Conference on World Wide Web, pp 729\u2013736. https:\/\/doi.org\/10.1145\/2487788.2488033","DOI":"10.1145\/2487788.2488033"},{"key":"8194_CR26","unstructured":"Ma J, Gao W, Mitra P, Kwon S, Jansen BJ, Wong K-F, Cha M (2016) Detecting rumors from microblogs with recurrent neural networks. IJCAI International Joint Conference on Artificial Intelligence"},{"key":"8194_CR27","doi-asserted-by":"crossref","unstructured":"Yu F, Liu Q, Wu S, Wang L, Tan T (2017) A convolutional approach for misinformation identification. In: IJCAI, pp. 3901\u20133907","DOI":"10.24963\/ijcai.2017\/545"},{"issue":"2","key":"8194_CR28","doi-asserted-by":"publisher","first-page":"1015","DOI":"10.1007\/s11227-020-03294-y","volume":"77","author":"RK Kaliyar","year":"2021","unstructured":"Kaliyar RK, Goswami A, Narang P (2021) Deepfake: improving fake news detection using tensor decomposition-based deep neural network. J Supercomput 77(2):1015\u20131037. https:\/\/doi.org\/10.1007\/s11227-020-03294-y","journal-title":"J Supercomput"},{"key":"8194_CR29","doi-asserted-by":"publisher","unstructured":"Cheng M, Nazarian S, Bogdan P (2020) Vroc: Variational autoencoder-aided multi-task rumor classifier based on text. In: Proceedings of the Web Conference 2020, pp 2892\u20132898. https:\/\/doi.org\/10.1145\/3366423.3380054","DOI":"10.1145\/3366423.3380054"},{"key":"8194_CR30","doi-asserted-by":"publisher","unstructured":"Chen J, Zhang A (2020) Hgmf: heterogeneous graph-based fusion for multimodal data with incompleteness. In: Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, pp 1295\u20131305. https:\/\/doi.org\/10.1145\/3394486.3403182","DOI":"10.1145\/3394486.3403182"},{"key":"8194_CR31","doi-asserted-by":"publisher","unstructured":"Jin Z, Cao J, Guo H, Zhang Y, Luo J (2017) Multimodal fusion with recurrent neural networks for rumor detection on microblogs. In: Proceedings of the 25th ACM International Conference on Multimedia, pp 795\u2013816. https:\/\/doi.org\/10.1145\/3123266.3123454","DOI":"10.1145\/3123266.3123454"},{"key":"8194_CR32","doi-asserted-by":"publisher","unstructured":"Kirchknopf A, Slijep\u010devi\u0107 D, Zeppelzauer M (2021) Multimodal detection of information disorder from social media. In: 2021 International Conference on Content-based Multimedia Indexing (CBMI), pp. 1\u20134. IEEE. https:\/\/doi.org\/10.1109\/CBMI50038.2021.9461898","DOI":"10.1109\/CBMI50038.2021.9461898"},{"key":"8194_CR33","doi-asserted-by":"crossref","unstructured":"Wu Y, Zhan P, Zhang Y, Wang L, Xu Z (2021) Multimodal fusion with co-attention networks for fake news detection. In: Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pp 2560\u20132569","DOI":"10.18653\/v1\/2021.findings-acl.226"},{"key":"8194_CR34","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2024.123967","volume":"250","author":"E Raja","year":"2024","unstructured":"Raja E, Soni B, Borgohain SK (2024) Fake news detection in dravidian languages using multiscale residual cnn_bilstm hybrid model. Expert Syst Appl 250:123967. https:\/\/doi.org\/10.1016\/j.eswa.2024.123967","journal-title":"Expert Syst Appl"},{"issue":"5","key":"8194_CR35","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2021.102610","volume":"58","author":"J Xue","year":"2021","unstructured":"Xue J, Wang Y, Tian Y, Li Y, Shi L, Wei L (2021) Detecting fake news by exploring the consistency of multimodal data. Inf Processing Manag 58(5):102610. https:\/\/doi.org\/10.1016\/j.ipm.2021.102610","journal-title":"Inf Processing Manag"},{"key":"8194_CR36","doi-asserted-by":"publisher","unstructured":"Singhal S, Dhawan M, Shah RR, Kumaraguru P (2021) Inter-modality discordance for multimodal fake news detection. In: Proceedings of the 3rd ACM International Conference on Multimedia in Asia, pp 1\u20137. https:\/\/doi.org\/10.1145\/3469877.3490614","DOI":"10.1145\/3469877.3490614"},{"key":"8194_CR37","doi-asserted-by":"publisher","unstructured":"Singhal S, Pandey T, Mrig S, Shah RR, Kumaraguru P (2022) Leveraging intra and inter modality relationship for multimodal fake news detection. In: Companion Proceedings of the Web Conference 2022, pp 726\u2013734. https:\/\/doi.org\/10.1145\/3487553.3524650","DOI":"10.1145\/3487553.3524650"},{"issue":"8","key":"8194_CR38","doi-asserted-by":"publisher","first-page":"889","DOI":"10.1007\/s11227-025-07365-w","volume":"81","author":"L Ji","year":"2025","unstructured":"Ji L, Feng J, Xiao S, Zhang H (2025) Multi-dimensional feature collaborative fusion networks for multimodal fake news detection: L. ji et al. J Supercomput 81(8):889. https:\/\/doi.org\/10.1007\/s11227-025-07365-w","journal-title":"J Supercomput"},{"issue":"1","key":"8194_CR39","doi-asserted-by":"publisher","first-page":"114","DOI":"10.1007\/s13278-024-01271-4","volume":"14","author":"M Dhawan","year":"2024","unstructured":"Dhawan M, Sharma S, Kadam A, Sharma R, Kumaraguru P (2024) Game-on: Graph attention network based multimodal fusion for fake news detection. Soc Netw Anal Min 14(1):114. https:\/\/doi.org\/10.1007\/s13278-024-01271-4","journal-title":"Soc Netw Anal Min"},{"key":"8194_CR40","doi-asserted-by":"publisher","DOI":"10.1109\/TCSS.2024.3404921","author":"Z Qu","year":"2024","unstructured":"Qu Z, Zhou F, Song X, Ding R, Yuan L, Wu Q (2024) Temporal enhanced multimodal graph neural networks for fake news detection. IEEE Trans Comput Social Syst. https:\/\/doi.org\/10.1109\/TCSS.2024.3404921","journal-title":"IEEE Trans Comput Social Syst"},{"key":"8194_CR41","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2025.127751","volume":"281","author":"A Kukkar","year":"2025","unstructured":"Kukkar A, Kaur G (2025) Aec: A novel adaptive ensemble classifier with lime and shap-based interpretability for fake news detection. Expert Syst Appl 281:127751. https:\/\/doi.org\/10.1016\/j.eswa.2025.127751","journal-title":"Expert Syst Appl"},{"key":"8194_CR42","doi-asserted-by":"publisher","unstructured":"Wang H, Guo J, Liu S, Chen P, Li X (2025) Sepm: Multiscale semantic enhancement-progressive multimodal fusion network for fake news detection. Expert Syst Appl 127741. https:\/\/doi.org\/10.1016\/j.eswa.2025.127741","DOI":"10.1016\/j.eswa.2025.127741"},{"key":"8194_CR43","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp 770\u2013778","DOI":"10.1109\/CVPR.2016.90"},{"key":"8194_CR44","doi-asserted-by":"publisher","unstructured":"Song Y, Wang J, Liang Z, Liu Z, Jiang T (2020) Utilizing bert intermediate layers for aspect based sentiment analysis and natural language inference. arXiv preprint arXiv:2002.04815. https:\/\/doi.org\/10.48550\/arXiv.2002.04815","DOI":"10.48550\/arXiv.2002.04815"},{"key":"8194_CR45","doi-asserted-by":"crossref","unstructured":"Yoon K (2015) Convolutional neural networks for sentence classification. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, ACL, pp 1746\u20131751","DOI":"10.3115\/v1\/D14-1181"},{"issue":"3","key":"8194_CR46","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1089\/big.2020.0062","volume":"8","author":"K Shu","year":"2020","unstructured":"Shu K, Mahudeswaran D, Wang S, Lee D, Liu H (2020) Fakenewsnet: A data repository with news content, social context, and spatiotemporal information for studying fake news on social media. Big data 8(3):171\u2013188. https:\/\/doi.org\/10.1089\/big.2020.0062","journal-title":"Big data"},{"key":"8194_CR47","doi-asserted-by":"publisher","unstructured":"Hu B, Sheng Q, Cao J, Shi Y, Li Y, WangD, Qi P (2024) Bad actor, good advisor: Exploring the role of large language models in fake news detection. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 38, pp. 22105\u201322113. https:\/\/doi.org\/10.1609\/aaai.v38i20.30214","DOI":"10.1609\/aaai.v38i20.30214"},{"key":"8194_CR48","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2025.107377","volume":"187","author":"X Chen","year":"2025","unstructured":"Chen X, Huang X, Gao Q, Huang L, Liu G (2025) Enhancing text-centric fake news detection via external knowledge distillation from llms. Neural Netw 187:107377. https:\/\/doi.org\/10.1016\/j.neunet.2025.107377","journal-title":"Neural Netw"},{"key":"8194_CR49","doi-asserted-by":"publisher","unstructured":"Zhang T, Wang D, Chen H, Zeng Z, Guo W, Miao C, Cui L (2020) Bdann: Bert-based domain adaptation neural network for multi-modal fake news detection. In: 2020 International Joint Conference on Neural Networks (IJCNN), pp. 1\u20138. IEEE. https:\/\/doi.org\/10.1109\/IJCNN48605.2020.9206973","DOI":"10.1109\/IJCNN48605.2020.9206973"},{"key":"8194_CR50","doi-asserted-by":"publisher","unstructured":"Ying Q, Hu X, Zhou Y, Qian Z, Zeng D, Ge S (2023) Bootstrapping multi-view representations for fake news detection. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 37, pp. 5384\u20135392. https:\/\/doi.org\/10.1609\/aaai.v37i4.25670","DOI":"10.1609\/aaai.v37i4.25670"},{"key":"8194_CR51","doi-asserted-by":"publisher","unstructured":"Yu X, Sheng Z, Lu W, Luo X, Zhou J (2025) Racmc: Residual-aware compensation network with multi-granularity constraints for fake news detection. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 39, pp. 986\u2013994. https:\/\/doi.org\/10.1609\/aaai.v39i1.32084","DOI":"10.1609\/aaai.v39i1.32084"}],"container-title":["The Journal of Supercomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-025-08194-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11227-025-08194-7","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-025-08194-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T07:13:37Z","timestamp":1767683617000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11227-025-08194-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,6]]},"references-count":51,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2026,1]]}},"alternative-id":["8194"],"URL":"https:\/\/doi.org\/10.1007\/s11227-025-08194-7","relation":{},"ISSN":["1573-0484"],"issn-type":[{"value":"1573-0484","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,6]]},"assertion":[{"value":"27 August 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 December 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 January 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"46"}}