68 citations · 162 across the 11 of their papers we have counts for
14 papers
Rerouting LLM Routers
Avital Shafran, Roei Schuster, Thomas Ristenpart +1
LLM routers aim to balance quality and cost of generation by classifying queries and routing them to a cheaper or more expensive LLM depending on their complexity. Routers represen…
Machine Against the RAG: Jamming Retrieval-Augmented Generation with Blocker Documents
Avital Shafran, Roei Schuster, Vitaly Shmatikov
Retrieval-augmented generation (RAG) systems respond to queries by retrieving relevant documents from a knowledge database and applying an LLM to the retrieved documents. We demons…
The Adversarial Implications of Variable-Time Inference
Dudi Biton, Aditi Misra, Efrat Levy +6
Machine learning (ML) models are known to be vulnerable to a number of attacks that target the integrity of their predictions or the privacy of their training data. To carry out th…
Reconstructing Individual Data Points in Federated Learning Hardened with Differential Privacy and Secure Aggregation
Franziska Boenisch, Adam Dziedzic, Roei Schuster +3
Federated learning (FL) is a framework for users to jointly train a machine learning model. FL is promoted as a privacy-enhancing technology (PET) that provides data minimization:…
Learned-Database Systems Security
Roei Schuster, Jin Peng Zhou, Thorsten Eisenhofer +2
A learned database system uses machine learning (ML) internally to improve performance. We can expect such systems to be vulnerable to some adversarial-ML attacks. Often, the learn…
Understanding Transformer Memorization Recall Through Idioms
Adi Haviv, Ido Cohen, Jacob Gidron +3
To produce accurate predictions, language models (LMs) must balance between generalization and memorization. Yet, little is known about the mechanism by which transformer LMs emplo…