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AToMiC: An Image/Text Retrieval Test Collection to Support Multimedia Content Creation
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“recent multimodal retrieval systems leverage both text and image representations [76], exposing additional attack surfaces”
From External Data Extraction Attacks Against Retrieval-Augmented Large Language Models (2026) · cites this paper as [76]
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Cited by
External Data Extraction Attacks Against Retrieval-Augmented Large Language Models
He, Y., Chen, Y., Li, Y., Shao, S., Qi, L., Li, B., Tao, D., & Qin, Z. (2026) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2026.3705326 · Cited by 4
Metadata
- Authors
- Yang, J.-H., Lassance, C., Sampaio De Rezende, R., Srinivasan, K., Redi, M., Clinchant, S., & Lin, J.
- Venue
- Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval
- Publisher
- ACM
- Published
- 2023-07-18
- Pages
- 2975-2984
- Cited by
- 9
- References
- 2
- Funders
- NSERC
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.