← Search

Sagiv Antebi

2 accepted papers

2026

Tab-MIA: A Benchmark Dataset for Membership Inference Attacks on Tabular Data in LLMs

ICLR 2026poster

Large language models (LLMs) are increasingly trained on tabular data, which, unlike unstructured text, often contains personally identifiable information (PII) in a highly structured and explicit format. As a result, privacy risks arise, since sensitive records can be inadvertently retained by the…

Cited by 0SourceScholar
2025

Tag&Tab: Pretraining Data Detection in Large Language Models Using Keyword-Based Membership Inference Attack

EMNLP 2025

Large language models (LLMs) have become essential tools for digital task assistance. Their training relies heavily on the collection of vast amounts of data, which may include copyright-protected or sensitive information. Recent studies on detecting pretraining data in LLMs have primarily focused o