1 citations · 1 across the 11 of their papers we have counts for
11 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…
LAGO: Few-shot Crosslingual Embedding Inversion Attacks via Language Similarity-Aware Graph Optimization
Wenrui Yu, Yiyi Chen, Johannes Bjerva +2
We propose LAGO - Language Similarity-Aware Graph Optimization - a novel approach for few-shot cross-lingual embedding inversion attacks, addressing critical privacy vulnerabilitie…
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…
Trustworthy Machine Learning via Memorization and the Granular Long-Tail: A Survey on Interactions, Tradeoffs, and Beyond
Qiongxiu Li, Xiaoyu Luo, Yiyi Chen +1
The role of memorization in machine learning (ML) has garnered significant attention, particularly as modern models are empirically observed to memorize fragments of training data.…
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…
ProP: Efficient Backdoor Detection via Propagation Perturbation for Overparametrized Models
Tao Ren, Qiongxiu Li
Backdoor attacks pose significant challenges to the security of machine learning models, particularly for overparameterized models like deep neural networks. In this paper, we prop…
Large Language Models are Easily Confused: A Quantitative Metric, Security Implications and Typological Analysis
Yiyi Chen, Qiongxiu Li, Russa Biswas +1
Language Confusion is a phenomenon where Large Language Models (LLMs) generate text that is neither in the desired language, nor in a contextually appropriate language. This phenom…
An Intelligent Innovation Dataset on Scientific Research Outcomes
Xinran Wu, Hui Zou, Yidan Xing +4
Various stakeholders, such as researchers, government agencies, businesses, and research laboratories require a large volume of reliable scientific research outcomes including rese…