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20232025
most citedA New Era in LLM Security: Exploring Security Concerns in Real-World LLM-based Systems

17 citations · 24 across the 11 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.CR2023★ 1 cited

A Somewhat Robust Image Watermark against Diffusion-based Editing Models

Mingtian Tan, Tianhao Wang, Somesh Jha

Recently, diffusion models (DMs) have become the state-of-the-art method for image synthesis. Editing models based on DMs, known for their high fidelity and precision, have inadver…

cs.SE2023

slash: A Technique for Static Configuration-Logic Identification

Mohannad Alhanahnah, Philipp Schubert, Thomas Reps +2

Researchers have recently devised tools for debloating software and detecting configuration errors. Several of these tools rely on the observation that programs are composed of an…

cs.CL2023★ 1 cited

Adaptation with Self-Evaluation to Improve Selective Prediction in LLMs

Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi +3

Large language models (LLMs) have recently shown great advances in a variety of tasks, including natural language understanding and generation. However, their use in high-stakes de…

cs.LG2023★ 2 cited

Robust and Actively Secure Serverless Collaborative Learning

Olive Franzese, Adam Dziedzic, Christopher A. Choquette-Choo +7

Collaborative machine learning (ML) is widely used to enable institutions to learn better models from distributed data. While collaborative approaches to learning intuitively prote…

cs.LG2023

Why Train More? Effective and Efficient Membership Inference via Memorization

Jihye Choi, Shruti Tople, Varun Chandrasekaran +1

Membership Inference Attacks (MIAs) aim to identify specific data samples within the private training dataset of machine learning models, leading to serious privacy violations and…