{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T15:29:44Z","timestamp":1781018984542,"version":"3.54.1"},"reference-count":49,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Pattern Recognition"],"published-print":{"date-parts":[[2026,10]]},"DOI":"10.1016\/j.patcog.2026.113395","type":"journal-article","created":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T07:40:58Z","timestamp":1772610058000},"page":"113395","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":2,"special_numbering":"C","title":["Linguistic profiling of deepfakes: An open database for next-Generation deepfake detection"],"prefix":"10.1016","volume":"178","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2931-572X","authenticated-orcid":false,"given":"Yabin","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0611-0636","authenticated-orcid":false,"given":"Xiaopeng","family":"Hong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-2536-9521","authenticated-orcid":false,"given":"Yaqi","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0034-2065","authenticated-orcid":false,"given":"Zhiheng","family":"Ma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7385-079X","authenticated-orcid":false,"given":"Zhiwu","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.patcog.2026.113395_bib0001","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"10684","article-title":"High-resolution image synthesis with latent diffusion models","author":"Rombach","year":"2022"},{"key":"10.1016\/j.patcog.2026.113395_bib0002","unstructured":"D. Podell, Z. English, K. Lacey, A. Blattmann, T. Dockhorn, J. M\u00fcller, J. Penna, R. Rombach, SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis, in: The Twelfth International Conference on Learning Representations, 2024. https:\/\/openreview.net\/forum?id=di52zR8xgf."},{"key":"10.1016\/j.patcog.2026.113395_bib0003","first-page":"36479","article-title":"Photorealistic text-to-image diffusion models with deep language understanding","volume":"35","author":"Saharia","year":"2022","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.patcog.2026.113395_bib0004","unstructured":"OpenAI, Introducing 4o Image Generation, 2025, (https:\/\/openai.com\/zh-Hans-CN\/index\/introducing-4o-image-generation)."},{"key":"10.1016\/j.patcog.2026.113395_bib0005","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","first-page":"1","article-title":"Faceforensics++: learning to detect manipulated facial images","author":"Rossler","year":"2019"},{"key":"10.1016\/j.patcog.2026.113395_bib0006","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2022.109179","article-title":"Watching the big artifacts: exposing deepfake videos via bi-granularity artifacts","volume":"135","author":"Chen","year":"2023","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.113395_bib0007","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2022.108832","article-title":"Learning a deep dual-level network for robust deepfake detection","volume":"130","author":"Pu","year":"2022","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.113395_bib0008","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"8695","article-title":"CNN-Generated images are surprisingly easy to spot...for now","author":"Wang","year":"2020"},{"key":"10.1016\/j.patcog.2026.113395_bib0009","series-title":"Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security","first-page":"3418","article-title":"De-fake: detection and attribution of fake images generated by text-to-image generation models","author":"Sha","year":"2023"},{"key":"10.1016\/j.patcog.2026.113395_bib0010","first-page":"77771","article-title":"Genimage: a million-scale benchmark for detecting ai-generated image","volume":"36","author":"Zhu","year":"2023","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.patcog.2026.113395_bib0011","series-title":"Proceedings of the 61St Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","first-page":"893","article-title":"Diffusiondb: a large-scale prompt gallery dataset for text-to-image generative models","author":"Wang","year":"2023"},{"key":"10.1016\/j.patcog.2026.113395_bib0012","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","first-page":"22445","article-title":"Dire for diffusion-generated image detection","author":"Wang","year":"2023"},{"key":"10.1016\/j.patcog.2026.113395_bib0013","doi-asserted-by":"crossref","first-page":"15642","DOI":"10.1109\/ACCESS.2024.3356122","article-title":"CIFAKE: Image classification and explainable identification of AI-Generated synthetic images","volume":"12","author":"Bird","year":"2024","journal-title":"IEEE Access"},{"key":"10.1016\/j.patcog.2026.113395_bib0014","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV)","first-page":"18937","article-title":"LEGION: Learning to ground and explain for synthetic image detection","author":"Kang","year":"2025"},{"key":"10.1016\/j.patcog.2026.113395_bib0015","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"28831","article-title":"SIDA: Social media image deepfake detection, localization and explanation with large multimodal model","author":"Huang","year":"2025"},{"key":"10.1016\/j.patcog.2026.113395_bib0016","unstructured":"S. Wen, J. Ye, P. Feng, H. Kang, Z. Wen, Y. Chen, J. Wu, w. wu, C. He, W. Li, Spot the Fake: Large Multimodal Model-Based Synthetic Image Detection with Artifact Explanation, in: The Thirty-ninth Annual Conference on Neural Information Processing Systems, 2025. https:\/\/openreview.net\/forum?id=xLFYd1owiP."},{"key":"10.1016\/j.patcog.2026.113395_bib0017","series-title":"Proceedings of the Computer Vision and Pattern Recognition Conference","first-page":"4291","article-title":"OpenSDI: spotting diffusion-Generated images in the open world","author":"Wang","year":"2025"},{"key":"10.1016\/j.patcog.2026.113395_bib0018","series-title":"Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision","first-page":"1339","article-title":"A continual deepfake detection benchmark: dataset, methods, and essentials","author":"Li","year":"2023"},{"issue":"11","key":"10.1016\/j.patcog.2026.113395_bib0019","first-page":"3438","article-title":"Benchmark dataset and framework for continual AI-generated image detection","volume":"30","author":"Wang","year":"2025","journal-title":"J. Image Graph."},{"key":"10.1016\/j.patcog.2026.113395_bib0020","series-title":"Conference on Neural Information Processing Systems (NeurIPS)","article-title":"S-Prompts Learning with pre-trained transformers: an Occam\u2019s razor for domain incremental learning","author":"Wang","year":"2022"},{"key":"10.1016\/j.patcog.2026.113395_bib0021","article-title":"Dual-Attention based prompt generation and catalyzing for instance-wise continual learning","author":"Dai","year":"2025","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.113395_bib0022","first-page":"1","article-title":"Penny-Wise and pound-Foolish in AI-Generated image detection","author":"Wang","year":"2026","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.patcog.2026.113395_bib0023","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2021.107950","article-title":"PRRNet: Pixel-Region relation network for face forgery detection","volume":"116","author":"Shang","year":"2021","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.113395_bib0024","series-title":"Intelligent Systems Conference","first-page":"615","article-title":"Level up the deepfake detection: a method to effectively discriminate images generated by gan architectures and diffusion models","author":"Guarnera","year":"2024"},{"key":"10.1016\/j.patcog.2026.113395_sbref0025","series-title":"Proceedings of the 19Th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP","first-page":"446","article-title":"Towards the detection of diffusion model deepfakes","author":"Ricker","year":"2024"},{"key":"10.1016\/j.patcog.2026.113395_bib0026","series-title":"International Conference on Machine Learning","first-page":"12888","article-title":"Blip: bootstrapping language-image pre-training for unified vision-language understanding and generation","author":"Li","year":"2022"},{"key":"10.1016\/j.patcog.2026.113395_bib0027","series-title":"Proceedings of the 33Rd ACM International Conference on Multimedia","first-page":"12666","article-title":"Dfbench: benchmarking deepfake image detection capability of large multimodal models","author":"Wang","year":"2025"},{"key":"10.1016\/j.patcog.2026.113395_bib0028","article-title":"Fakebench: probing explainable fake image detection via large multimodal models","author":"Li","year":"2025","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"10.1016\/j.patcog.2026.113395_bib0029","unstructured":"P. Yu, J. Fei, H. Gao, X. Feng, Z. Xia, C.H. Chang, Unlocking the Capabilities of Large Vision-Language Models for Generalizable and Explainable Deepfake Detection, in: A. Singh, M. Fazel, D. Hsu, S. Lacoste-Julien, F. Berkenkamp, T. Maharaj, K. Wagstaff, J. Zhu (Eds.), Proceedings of the 42nd International Conference on Machine Learning, 267 of Proceedings of Machine Learning Research, PMLR, 2025, pp. 72925\u201372943. https:\/\/proceedings.mlr.press\/v267\/yu25d.HTML."},{"key":"10.1016\/j.patcog.2026.113395_bib0030","unstructured":"M. Liang, Y. Qu, Y. Jiang, M. Backes, Y. Zhang, From Evidence to Verdict: An Agent-Based Forensic Framework for AI-Generated Image Detection, (2025). arXiv preprint arXiv: 2511.00181."},{"key":"10.1016\/j.patcog.2026.113395_bib0031","unstructured":"B.F. Labs, FLUX.1-dev, 2024, (https:\/\/huggingface.co\/black-forest-labs\/FLUX.1-dev)."},{"key":"10.1016\/j.patcog.2026.113395_bib0032","unstructured":"J. Maier, Civitai: The AI art community\u2019s free, open-source model-sharing hub, 2023, https:\/\/civitai.com\/."},{"key":"10.1016\/j.patcog.2026.113395_bib0033","unstructured":"A. Alush, D. Neoh, D. Bickson, et al., FastDup, GitHub. Note: https:\/\/github.com\/visual-layer\/fastdup (2022)."},{"key":"10.1016\/j.patcog.2026.113395_bib0034","first-page":"25278","article-title":"Laion-5b: an open large-scale dataset for training next generation image-text models","volume":"35","author":"Schuhmann","year":"2022","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.patcog.2026.113395_bib0035","unstructured":"D. Team, safebooru_full: A large-scale anime illustration dataset from Safebooru, 2023, (https:\/\/huggingface.co\/datasets\/deepghs\/safebooru_full). Accessed: 2025-12-18."},{"key":"10.1016\/j.patcog.2026.113395_bib0036","unstructured":"M. Oquab, T. Darcet, T. Moutakanni, H.V. Vo, M. Szafraniec, V. Khalidov, P. Fernandez, D. HAZIZA, F. Massa, A. El-Nouby, M. Assran, N. Ballas, W. Galuba, R. Howes, P.-Y. Huang, S.-W. Li, I. Misra, M. Rabbat, V. Sharma, G. Synnaeve, H. Xu, H. Jegou, J. Mairal, P. Labatut, A. Joulin, P. Bojanowski, DINOv2: Learning Robust Visual Features without Supervision, Trans. Mach. Learn. Res.(2024). Featured Certification, https:\/\/openreview.net\/forum?id=a68SUt6zFt."},{"key":"10.1016\/j.patcog.2026.113395_bib0037","series-title":"Forty-first International Conference on Machine Learning","article-title":"Scaling rectified flow transformers for high-resolution image synthesis","author":"Esser","year":"2024"},{"key":"10.1016\/j.patcog.2026.113395_bib0038","unstructured":"J. Chen, Y. Wu, S. Luo, E. Xie, S. Paul, P. Luo, H. Zhao, Z. Li, PIXART-delta: Fast and Controllable Image Generation with Latent Consistency Models, 2024, arXiv: 2401.05252."},{"key":"10.1016\/j.patcog.2026.113395_bib0039","unstructured":"Z. Li, J. Zhang, Q. Lin, J. Xiong, Y. Long, X. Deng, Y. Zhang, X. Liu, M. Huang, Z. Xiao, D. Chen, J. He, J. Li, W. Li, C. Zhang, R. Quan, J. Lu, J. Huang, X. Yuan, X. Zheng, Y. Li, J. Zhang, C. Zhang, M. Chen, J. Liu, Z. Fang, W. Wang, J. Xue, Y. Tao, J. Zhu, K. Liu, S. Lin, Y. Sun, Y. Li, D. Wang, M. Chen, Z. Hu, X. Xiao, Y. Chen, Y. Liu, W. Liu, D. Wang, Y. Yang, J. Jiang, Q. Lu, Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding, 2024, arXiv: 2405.08748."},{"key":"10.1016\/j.patcog.2026.113395_bib0040","unstructured":"G. DeepMind, Imagen 4 Model Card, 2025, (https:\/\/storage.googleapis.com\/deepmind-media\/Model-Cards\/Imagen-4-Model-Card.pdf)."},{"key":"10.1016\/j.patcog.2026.113395_bib0041","series-title":"International Conference on Learning Representations","article-title":"LoRA: low-Rank adaptation of large language models","author":"Hu","year":"2021"},{"key":"10.1016\/j.patcog.2026.113395_bib0042","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"28130","article-title":"Rethinking the up-sampling operations in cnn-based generative network for generalizable deepfake detection","author":"Tan","year":"2024"},{"key":"10.1016\/j.patcog.2026.113395_bib0043","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"24480","article-title":"Towards universal fake image detectors that generalize across generative models","author":"Ojha","year":"2023"},{"key":"10.1016\/j.patcog.2026.113395_bib0044","series-title":"European Conference on Computer Vision","first-page":"394","article-title":"Leveraging representations from intermediate encoder-blocks for synthetic image detection","author":"Koutlis","year":"2024"},{"key":"10.1016\/j.patcog.2026.113395_bib0045","series-title":"The Thirteenth International Conference on Learning Representations","article-title":"A sanity check for AI-generated image detection","author":"Yan","year":"2024"},{"key":"10.1016\/j.patcog.2026.113395_bib0046","unstructured":"S. Bai, K. Chen, X. Liu, J. Wang, W. Ge, S. Song, K. Dang, P. Wang, S. Wang, J. Tang, et al., Qwen2. 5-vl technical report, (2025). arXiv preprint arXiv: 2502.13923."},{"key":"10.1016\/j.patcog.2026.113395_bib0047","series-title":"The Eleventh International Conference on Learning Representations","article-title":"An image is worth one word: personalizing text-to-Image generation using textual inversion","author":"Gal","year":"2022"},{"key":"10.1016\/j.patcog.2026.113395_bib0048","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","first-page":"586","article-title":"The unreasonable effectiveness of deep features as a perceptual metric","author":"Zhang","year":"2018"},{"key":"10.1016\/j.patcog.2026.113395_bib0049","series-title":"International Conference on Machine Learning","first-page":"19730","article-title":"Blip-2: bootstrapping language-image pre-training with frozen image encoders and large language models","author":"Li","year":"2023"}],"container-title":["Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031320326003602?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031320326003602?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T17:00:59Z","timestamp":1779382859000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0031320326003602"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10]]},"references-count":49,"alternative-id":["S0031320326003602"],"URL":"https:\/\/doi.org\/10.1016\/j.patcog.2026.113395","relation":{},"ISSN":["0031-3203"],"issn-type":[{"value":"0031-3203","type":"print"}],"subject":[],"published":{"date-parts":[[2026,10]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Linguistic profiling of deepfakes: An open database for next-Generation deepfake detection","name":"articletitle","label":"Article Title"},{"value":"Pattern Recognition","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.patcog.2026.113395","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"113395"}}