3 papers
cs.CL2025
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…
cs.CL2025
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…
cs.LG2025
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…