Public articles linked to the same research event.
arXiv The work introduces TellTail, a query-only fingerprinting attack that identifies the embedding model behind a black-box retrieval system: it perfectly identifies the deployed retriever from full rankings, achieves 94.3% success from unordered top-3 results, and 92.5% from language-model-generated answers alone, and still identifies 44 of 53 retrievers in an end-to-end OpenWebUI deployment.
The work introduces TellTail, a query-only fingerprinting attack that identifies the embedding model behind a black-box retrieval system: it perfectly identifies the deployed retriever from full rankings, achieves 94.3% success from unordered top-3 results, and 92.5% from language-model-generated answers alone, and still identifies 44 of 53 retrievers in an end-to-end OpenWebUI deployment.
The work introduces TellTail, a query-only fingerprinting attack that identifies the embedding model behind a black-box retrieval system: it perfectly identifies the deployed retriever from full rankings, achieves 94.3% success from unordered top-3 results, and 92.5% from language-model-generated answers alone, and still identifies 44 of 53 retrievers in an end-to-end OpenWebUI deployment.
The work introduces TellTail, a query-only fingerprinting attack that identifies the embedding model behind a black-box retrieval system: it perfectly identifies the deployed retriever from full rankings, achieves 94.3% success from unordered top-3 results, and 92.5% from language-model-generated answers alone, and still identifies 44 of 53 retrievers in an end-to-end OpenWebUI deployment.