Cover Image

GaussMark: A Practical Approach for Structural Watermarking of Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Block, Adam, Sekhari, Ayush, Rakhlin, Alexander
Format:	Preprint
Published:	2025
Subjects:	Cryptography and Security Artificial Intelligence Computation and Language Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

PostMark: A Robust Blackbox Watermark for Large Language Models
by: Chang, Yapei, et al.
Published: (2024)

Mark Your LLM: Detecting the Misuse of Open-Source Large Language Models via Watermarking
by: Xu, Yijie, et al.
Published: (2025)

MarkTune: Improving the Quality-Detectability Trade-off in Open-Weight LLM Watermarking
by: Zhao, Yizhou, et al.
Published: (2025)

AliMark: Enhancing Robustness of Sentence-Level Watermarking Against Text Paraphrasing
by: Li, Yuexin, et al.
Published: (2026)

Watermarking Makes Language Models Radioactive
by: Sander, Tom, et al.
Published: (2024)

Duwak: Dual Watermarks in Large Language Models
by: Zhu, Chaoyi, et al.
Published: (2024)

UCD: Unlearning in LLMs via Contrastive Decoding
by: Suriyakumar, Vinith M., et al.
Published: (2025)

Mark My Words: Analyzing and Evaluating Language Model Watermarks
by: Piet, Julien, et al.
Published: (2023)

Hidden Poison: Machine Unlearning Enables Camouflaged Poisoning Attacks
by: Di, Jimmy Z., et al.
Published: (2022)

OBLIVIATE: Robust and Practical Machine Unlearning for Large Language Models
by: Xu, Xiaoyu, et al.
Published: (2025)

Downstream Trade-offs of a Family of Text Watermarks
by: Ajith, Anirudh, et al.
Published: (2023)

Adversarial Text Purification: A Large Language Model Approach for Defense
by: Moraffah, Raha, et al.
Published: (2024)

Machine Unlearning Fails to Remove Data Poisoning Attacks
by: Pawelczyk, Martin, et al.
Published: (2024)

Revealing Weaknesses in Text Watermarking Through Self-Information Rewrite Attacks
by: Cheng, Yixin, et al.
Published: (2025)

On Evaluating The Performance of Watermarked Machine-Generated Texts Under Adversarial Attacks
by: Liu, Zesen, et al.
Published: (2024)

Watermarking Language Models for Many Adaptive Users
by: Cohen, Aloni, et al.
Published: (2024)

TurboFuzzLLM: Turbocharging Mutation-based Fuzzing for Effectively Jailbreaking Large Language Models in Practice
by: Goel, Aman, et al.
Published: (2025)

An Interpretable N-gram Perplexity Threat Model for Large Language Model Jailbreaks
by: Boreiko, Valentyn, et al.
Published: (2024)

GaussMarker: Robust Dual-Domain Watermark for Diffusion Models
by: Li, Kecen, et al.
Published: (2025)

Topic-Based Watermarks for Large Language Models
by: Nemecek, Alexander, et al.
Published: (2024)

Exposing the Systematic Vulnerability of Open-Weight Models to Prefill Attacks
by: Struppek, Lukas, et al.
Published: (2026)

FreeMark: A Non-Invasive White-Box Watermarking for Deep Neural Networks
by: Chen, Yuzhang, et al.
Published: (2024)

Watermarking Diffusion Language Models
by: Gloaguen, Thibaud, et al.
Published: (2025)

A Study of Backdoors in Instruction Fine-tuned Language Models
by: Raghuram, Jayaram, et al.
Published: (2024)

Lifelong Safety Alignment for Language Models
by: Wang, Haoyu, et al.
Published: (2025)

Instructional Fingerprinting of Large Language Models
by: Xu, Jiashu, et al.
Published: (2024)

Personal Information Parroting in Language Models
by: Subramani, Nishant, et al.
Published: (2026)

Jailbreak Attacks and Defenses Against Large Language Models: A Survey
by: Yi, Sibo, et al.
Published: (2024)

SimMark: A Robust Sentence-Level Similarity-Based Watermarking Algorithm for Large Language Models
by: Dabiriaghdam, Amirhossein, et al.
Published: (2025)

A Watermark for Large Language Models
by: Kirchenbauer, John, et al.
Published: (2023)

Preserving Privacy in Large Language Models: A Survey on Current Threats and Solutions
by: Miranda, Michele, et al.
Published: (2024)

RECAP: A Resource-Efficient Method for Adversarial Prompting in Large Language Models
by: Chugh, Rishit
Published: (2026)

SALAD-Bench: A Hierarchical and Comprehensive Safety Benchmark for Large Language Models
by: Li, Lijun, et al.
Published: (2024)

Rethinking How to Evaluate Language Model Jailbreak
by: Cai, Hongyu, et al.
Published: (2024)

Large Language Models in Cybersecurity: State-of-the-Art
by: Motlagh, Farzad Nourmohammadzadeh, et al.
Published: (2024)

Jailbreaking Large Language Models with Symbolic Mathematics
by: Bethany, Emet, et al.
Published: (2024)

Learnable Privacy Neurons Localization in Language Models
by: Chen, Ruizhe, et al.
Published: (2024)

On Adversarial Robustness of Language Models in Transfer Learning
by: Turbal, Bohdan, et al.
Published: (2024)

Watermarking Language Models through Language Models
by: Dasgupta, Agnibh, et al.
Published: (2024)

On the Learnability of Watermarks for Language Models
by: Gu, Chenchen, et al.
Published: (2023)