{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T18:41:48Z","timestamp":1775068908853,"version":"3.50.1"},"reference-count":32,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,5,23]],"date-time":"2025-05-23T00:00:00Z","timestamp":1747958400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,5,23]],"date-time":"2025-05-23T00:00:00Z","timestamp":1747958400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,5,23]]},"DOI":"10.1109\/icmlt65785.2025.11193311","type":"proceedings-article","created":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T17:39:05Z","timestamp":1760377145000},"page":"248-256","source":"Crossref","is-referenced-by-count":6,"title":["ADALog: Adaptive Unsupervised Anomaly detection in Logs with Self-attention Masked Language Model"],"prefix":"10.1109","author":[{"given":"Przemek","family":"Pospieszny","sequence":"first","affiliation":[{"name":"Cognizant,NeuroEdge AI"}]},{"given":"Wojciech","family":"Mormul","sequence":"additional","affiliation":[{"name":"Cognizant,NeuroEdge AI"}]},{"given":"Karolina","family":"Szyndler","sequence":"additional","affiliation":[{"name":"Cognizant,NeuroEdge AI"}]},{"given":"Sanjeev","family":"Kumar","sequence":"additional","affiliation":[{"name":"Cognizant,NeuroEdge AI"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.7717\/peerj-cs.489"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICRITO48877.2020.9197818"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/QRS60937.2023.00012"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.mlwa.2023.100470"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/s10664-023-10364-1"},{"key":"ref6","article-title":"A Comprehensive Study of Machine Learning Techniques for Log-Based Anomaly Detection","author":"Ali","year":"2023"},{"key":"ref7","article-title":"LogELECTRA: Self-supervised Anomaly Detection for Unstructured Logs","author":"Yamanaka"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN52387.2021.9534113"},{"key":"ref9","article-title":"Efficiency of Unsupervised Anomaly Detection Methods on Software Logs","volume-title":"Proceedings of ACM Conference (Conference\u201917)","volume":"1","author":"Nyyss\u00f6l\u00e4"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/s10664-024-10533-w"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/s10664-022-10214-6"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/3133956.3134015"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE-Companion52605.2021.00106"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/3338906.3338931"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/WFPST58552.2024.00034"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/658"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM50108.2020.00148"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2023.110689"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TNSM.2024.3358730"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.7763\/IJCTE.2016.V8.1057"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/3510003.3510155"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.3233\/faia220378"},{"key":"ref23","doi-asserted-by":"crossref","DOI":"10.2139\/ssrn.4968529","article-title":"Log2graphs: An Unsupervised Framework for Log Anomaly Detection with Efficient Feature Extraction","author":"Wang","year":"2024"},{"issue":"1","key":"ref24","first-page":"135","article-title":"LogFormer: A Pre-train and Tuning Pipeline for Log Anomaly Detection","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","volume":"38","author":"Guo"},{"key":"ref25","article-title":"TRANSLOG: A Unified Transformer-based Framework for Log Anomaly Detection","author":"Guo"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.230"},{"key":"ref27","article-title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding","author":"Devlin"},{"key":"ref28","article-title":"DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter","author":"Sanh","year":"2019"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-1031"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/s42979-021-00866-4"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/DSN.2007.103"}],"event":{"name":"2025 10th International Conference on Machine Learning Technologies (ICMLT)","location":"Helsinki, Finland","start":{"date-parts":[[2025,5,23]]},"end":{"date-parts":[[2025,5,25]]}},"container-title":["2025 10th International Conference on Machine Learning Technologies (ICMLT)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11192828\/11192850\/11193311.pdf?arnumber=11193311","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,14]],"date-time":"2025-10-14T05:24:31Z","timestamp":1760419471000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11193311\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,23]]},"references-count":32,"URL":"https:\/\/doi.org\/10.1109\/icmlt65785.2025.11193311","relation":{},"subject":[],"published":{"date-parts":[[2025,5,23]]}}}