{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,2]],"date-time":"2026-08-02T05:46:35Z","timestamp":1785649595372,"version":"3.56.0"},"publisher-location":"Cham","reference-count":35,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032319265","type":"print"},{"value":"9783032319272","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T00:00:00Z","timestamp":1785715200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T00:00:00Z","timestamp":1785715200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2027]]},"DOI":"10.1007\/978-3-032-31927-2_7","type":"book-chapter","created":{"date-parts":[[2026,8,2]],"date-time":"2026-08-02T05:15:10Z","timestamp":1785647710000},"page":"94-108","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["SPARK-IL: Spectral Retrieval-Augmented RAG for\u00a0Knowledge-Driven Deepfake Detection via\u00a0Incremental Learning"],"prefix":"10.1007","author":[{"given":"Hessen Bougueffa","family":"Eutamene","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abdellah Zakaria","family":"Sellam","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abdelmalik","family":"Taleb-Ahmed","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abdenour","family":"Hadid","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,8,3]]},"reference":[{"key":"7_CR1","unstructured":"Bonomo, M., Bianco, S.: Visual rag: Expanding mllm visual knowledge without fine-tuning (2025). arXiv:2501.10834 arXiv preprint"},{"key":"7_CR2","doi-asserted-by":"crossref","unstructured":"Caffagni, D., et al.: Wiki-llava: hierarchical retrieval-augmented generation for multimodal llms. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 1818\u20131826. (2024)","DOI":"10.1109\/CVPRW63382.2024.00188"},{"key":"7_CR3","doi-asserted-by":"crossref","unstructured":"Chai, L., Bau, D., Lim, S.N., Isola, P.: What makes fake images detectable? understanding properties that generalize. In: European Conference on Computer Vision (2020)","DOI":"10.1007\/978-3-030-58574-7_7"},{"key":"7_CR4","unstructured":"Chang, Y.M., Yeh, C., Chiu, W.C., Yu, N.: Antifakeprompt: prompt-tuned vision-language models are fake image detectors (2024). arXiv:2310.17419 arXiv preprint"},{"key":"7_CR5","doi-asserted-by":"crossref","unstructured":"Chen, Y., Yashtini, M.: Detecting ai generated images through texture and frequency analysis of patches. In: International Conference on Artificial Intelligence, Virtual Reality and Visualization (2024)","DOI":"10.1109\/AIVRV63595.2024.10860248"},{"key":"7_CR6","doi-asserted-by":"crossref","unstructured":"Cozzolino, D., Poggi, G., Corvi, R., Nie\u00dfner, M., Verdoliva, L.: Raising the bar of ai-generated image detection with clip. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (2024)","DOI":"10.1109\/CVPRW63382.2024.00439"},{"key":"7_CR7","unstructured":"Dhariwal, P., Nichol, A.Q.: Diffusion models beat gans on image synthesis. In: Advances in Neural Information Processing Systems (2021)"},{"key":"7_CR8","unstructured":"Goodfellow, I.J., et al.: Generative adversarial nets. In: Advances in Neural Information Processing Systems (2014)"},{"key":"7_CR9","doi-asserted-by":"crossref","unstructured":"He, X., et al.: G-retriever: retrieval-augmented generation for textual graph understanding and question answering. In: Advances in Neural Information Processing Systems (2024)","DOI":"10.52202\/079017-4224"},{"key":"7_CR10","unstructured":"Karras, T., Aila, T., Laine, S., Lehtinen, J.: Progressive growing of gans for improved quality, stability, and variation. In: International Conference on Learning Representations (2018)"},{"key":"7_CR11","unstructured":"Ke\u00efta, M., et al.: Bi-lora: a vision-language approach for synthetic image detection. Expert. Syst. (2025)"},{"key":"7_CR12","doi-asserted-by":"crossref","unstructured":"Keita, M., Hamidouche, W., Eutamene, H.B., Taleb-Ahmed, A., Hadid, A.: Reveal: a retrieval-augmented generation approach for contextual identification of synthetic visual content. In: Proceedings of the Deepfake Forensics Workshop, (2025)","DOI":"10.1145\/3746265.3759667"},{"key":"7_CR13","unstructured":"Keita, M., Hamidouche, W., Eutamene, H.B., Taleb-Ahmed, A., Hadid, A.: Ravid: Retrieval-augmented visual detection (2025). arXiv:2508.03967 arXiv preprint"},{"key":"7_CR14","doi-asserted-by":"crossref","unstructured":"Kirkpatrick, J., et al.: Overcoming catastrophic forgetting in neural networks. Proc. Natl. Acad. Sci. (2017)","DOI":"10.1073\/pnas.1611835114"},{"key":"7_CR15","doi-asserted-by":"crossref","unstructured":"Koutlis, C., Papadopoulos, S.: Leveraging representations from intermediate encoder-blocks for synthetic image detection. In: European Conference on Computer Vision (2024)","DOI":"10.1007\/978-3-031-73220-1_23"},{"key":"7_CR16","unstructured":"Lewis, P., Oguz, B., Rinott, R., Riedel, S., Rockt\u00e4schel, T.: Retrieval-augmented generation for knowledge-intensive natural language processing. In: Advances in Neural Information Processing Systems (2020)"},{"key":"7_CR17","doi-asserted-by":"crossref","unstructured":"Liu, H., Tan, Z., Tan, C., Wei, Y., Wang, J., Zhao, Y.: Forgery-aware adaptive transformer for generalizable synthetic image detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (2024)","DOI":"10.1109\/CVPR52733.2024.01024"},{"key":"7_CR18","doi-asserted-by":"crossref","unstructured":"Long, X., Ma, Z., Hua, E., Zhang, K., Qi, B., Zhou, B.: Retrieval-augmented visual question answering via built-in autoregressive search engines (2025). arXiv:2502.16641 arXiv preprint","DOI":"10.1609\/aaai.v39i23.34653"},{"key":"7_CR19","unstructured":"Nataraj, L., et al.: Detecting gan generated fake images using co-occurrence matrices (2019). arXiv:1903.06836 arXiv preprint"},{"key":"7_CR20","unstructured":"Nichol, A.Q., et al.: Glide: Towards photorealistic image generation and editing with text-guided diffusion models. In: International Conference on Machine Learning (2022)"},{"key":"7_CR21","doi-asserted-by":"crossref","unstructured":"Ojha, U., Li, Y., Lee, Y.J.: Towards universal fake image detectors that generalize across generative models. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (2023)","DOI":"10.1109\/CVPR52729.2023.02345"},{"key":"7_CR22","unstructured":"OpenAI: Dall$$\\cdot $$e 3: Improving image generation with better captions. Tech. rep. (2023)"},{"key":"7_CR23","doi-asserted-by":"crossref","unstructured":"Qian, Y., Yin, G., Sheng, L., Chen, Z., Shao, J.: Thinking in frequency: Face forgery detection by mining frequency-aware clues. In: European Conference on Computer Vision (2020)","DOI":"10.1007\/978-3-030-58610-2_6"},{"key":"7_CR24","unstructured":"Ramesh, A., et al.: Zero-shot text-to-image generation. In: International Conference on Machine Learning (2021)"},{"key":"7_CR25","doi-asserted-by":"crossref","unstructured":"Rombach, R., Blattmann, A., Lorenz, D., Esser, P., Ommer, B.: High-resolution image synthesis with latent diffusion models. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (2022)","DOI":"10.1109\/CVPR52688.2022.01042"},{"key":"7_CR26","doi-asserted-by":"crossref","unstructured":"Saharia, C., et al.: Photorealistic text-to-image diffusion models with deep language understanding. In: Advances in Neural Information Processing Systems (2022)","DOI":"10.52202\/068431-2643"},{"key":"7_CR27","doi-asserted-by":"crossref","unstructured":"Tan, C., Tao, R., Liu, H., Gu, G., Wu, B., Zhao, Y., Wei, Y.: C2p-clip: Injecting category common prompt in clip to enhance generalization in deepfake detection, (2024). arXiv:2408.09647 arXiv preprint","DOI":"10.1609\/aaai.v39i7.32772"},{"key":"7_CR28","doi-asserted-by":"crossref","unstructured":"Tan, C., Zhao, Y., Wei, S., Gu, G., Liu, P., Wei, Y.: Frequency-aware deepfake detection: improving generalizability through frequency space domain learning. In: Proceedings of the AAAI Conference on Artificial Intelligence (2024)","DOI":"10.1609\/aaai.v38i5.28310"},{"key":"7_CR29","doi-asserted-by":"crossref","unstructured":"Tan, C., Zhao, Y., Wei, S., Gu, G., Liu, P., Wei, Y.: Rethinking the up-sampling operations in cnn-based generative network for generalizable deepfake detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (2024)","DOI":"10.1109\/CVPR52733.2024.02657"},{"key":"7_CR30","doi-asserted-by":"crossref","unstructured":"Tan, C., Zhao, Y., Wei, S., Gu, G., Wei, Y.: Learning on gradients: generalized artifacts representation for gan-generated images detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (2023)","DOI":"10.1109\/CVPR52729.2023.01165"},{"key":"7_CR31","doi-asserted-by":"crossref","unstructured":"Tao, M., Bao, B.K., Tang, H., Xu, C.: Galip: generative adversarial clips for text-to-image synthesis. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (2023)","DOI":"10.1109\/CVPR52729.2023.01366"},{"key":"7_CR32","doi-asserted-by":"crossref","unstructured":"Wang, S.Y., Wang, O., Zhang, R., Owens, A., Efros, A.A.: Cnn-generated images are surprisingly easy to spot... for now. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (2020)","DOI":"10.1109\/CVPR42600.2020.00872"},{"key":"7_CR33","doi-asserted-by":"crossref","unstructured":"Wang, Z., Guo, J., Li, R., Hu, R., Zhou, H., Huang, R., Chen, Y.: Dire: diffusion reconstruction error for diffusion-generated image detection. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (2023)","DOI":"10.1109\/ICCV51070.2023.02051"},{"key":"7_CR34","doi-asserted-by":"crossref","unstructured":"Xu, Y., Zhao, Y., Xiao, Z., Hou, T.: Ufogen: You forward once large-scale text-to-image generation via diffusion gans. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (2024)","DOI":"10.1109\/CVPR52733.2024.00783"},{"key":"7_CR35","doi-asserted-by":"crossref","unstructured":"Zhang, X., Karaman, S., Chang, S.F.: Detecting and simulating artifacts in gan fake images. IEEE International Workshop on Information Forensics and Security (2019)","DOI":"10.1109\/WIFS47025.2019.9035107"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-31927-2_7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,2]],"date-time":"2026-08-02T05:15:14Z","timestamp":1785647714000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-31927-2_7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,3]]},"ISBN":["9783032319265","9783032319272"],"references-count":35,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-31927-2_7","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,3]]},"assertion":[{"value":"3 August 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICPR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Pattern Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Lyon","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"France","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2026","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 August 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 August 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icpr2026","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icpr2026.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}