88 citations · 98 across the 16 of their papers we have counts for
3 papers · 1 filter
Measuring memorization in language models via probabilistic extraction
Jamie Hayes, Marika Swanberg, Harsh Chaudhari +6
Large language models (LLMs) are susceptible to memorizing training data, raising concerns about the potential extraction of sensitive information at generation time. Discoverable…
UTrace: Poisoning Forensics for Private Collaborative Learning
Evan Rose, Hidde Lycklama, Harsh Chaudhari +3
Privacy-preserving machine learning (PPML) systems enable multiple data owners to collaboratively train models without revealing their raw, sensitive data by leveraging cryptograph…
Phantom: General Backdoor Attacks on Retrieval Augmented Language Generation
Harsh Chaudhari, Giorgio Severi, John Abascal +6
Retrieval Augmented Generation (RAG) expands the capabilities of modern large language models (LLMs), by anchoring, adapting, and personalizing their responses to the most relevant…