1 citations · 1 across the 3 of their papers we have counts for
3 papers
Minerva: A Programmable Memory Test Benchmark for Language Models
Menglin Xia, Victor Ruehle, Saravan Rajmohan +1
How effectively can LLM-based AI assistants utilize their memory (context) to perform various tasks? Traditional data benchmarks, which are often manually crafted, suffer from seve…
Context-Aware Membership Inference Attacks against Pre-trained Large Language Models
Hongyan Chang, Ali Shahin Shamsabadi, Kleomenis Katevas +2
Membership Inference Attacks (MIAs) on pre-trained Large Language Models (LLMs) aim at determining if a data point was part of the model's training set. Prior MIAs that are built f…
Watermark Smoothing Attacks against Language Models
Hongyan Chang, Hamed Hassani, Reza Shokri
Watermarking is a key technique for detecting AI-generated text. In this work, we study its vulnerabilities and introduce the Smoothing Attack, a novel watermark removal method. By…