9 papers
Characterizing Memorization in Diffusion Language Models: Generalized Extraction and Sampling Effects
Xiaoyu Luo, Wenrui Yu, Qiongxiu Li +1
Autoregressive language models (ARMs) have been shown to memorize and occasionally reproduce training data verbatim, raising concerns about privacy and copyright liability. Diffusi…
APEX: Probing Neural Networks via Activation Perturbation
Tao Ren, Xiaoyu Luo, Qiongxiu Li
Prior work on probing neural networks primarily relies on input-space analysis or parameter perturbation, both of which face fundamental limitations in accessing structural informa…
Semantic Leakage from Image Embeddings
Yiyi Chen, Qiongkai Xu, Desmond Elliott +2
Image embeddings are generally assumed to pose limited privacy risk. We challenge this assumption by formalizing semantic leakage as the ability to recover semantic structures from…
Do LLMs Really Memorize Personally Identifiable Information? Revisiting PII Leakage with a Cue-Controlled Memorization Framework
Xiaoyu Luo, Yiyi Chen, Qiongxiu Li +1
Large Language Models (LLMs) have been reported to "leak" Personally Identifiable Information (PII), with successful PII reconstruction often interpreted as evidence of memorizatio…
Shared Path: Unraveling Memorization in Multilingual LLMs through Language Similarities
Xiaoyu Luo, Yiyi Chen, Johannes Bjerva +1
We present the first comprehensive study of Memorization in Multilingual Large Language Models (MLLMs), analyzing 95 languages using models across diverse model scales, architectur…
DeMem: Privacy-Enhanced Robust Adversarial Learning via De-Memorization
Xiaoyu Luo, Qiongxiu Li
Adversarial robustness, the ability of a model to withstand manipulated inputs that cause errors, is essential for ensuring the trustworthiness of machine learning models in real-w…