Cover Image

AdvJudge-Zero: Binary Decision Flips in LLM-as-a-Judge via Adversarial Control Tokens

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Tung-Ling, Wu, Yuhao, Liu, Hongliang
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Computation and Language Cryptography and Security
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Logit-Gap Steering: A Forward-Pass Diagnostic for Alignment Robustness
by: Li, Tung-Ling, et al.
Published: (2025)

Refining Input Guardrails: Enhancing LLM-as-a-Judge Efficiency Through Chain-of-Thought Fine-Tuning and Alignment
by: Rad, Melissa Kazemi, et al.
Published: (2025)

Token-Modification Adversarial Attacks for Natural Language Processing: A Survey
by: Roth, Tom, et al.
Published: (2021)

Adversarial Attacks on LLM-as-a-Judge Systems: Insights from Prompt Injections
by: Maloyan, Narek, et al.
Published: (2025)

Know Thy Judge: On the Robustness Meta-Evaluation of LLM Safety Judges
by: Eiras, Francisco, et al.
Published: (2025)

Permute-and-Flip: An optimally stable and watermarkable decoder for LLMs
by: Zhao, Xuandong, et al.
Published: (2024)

Subspace Defense: Discarding Adversarial Perturbations by Learning a Subspace for Clean Signals
by: Zheng, Rui, et al.
Published: (2024)

BadJudge: Backdoor Vulnerabilities of LLM-as-a-Judge
by: Tong, Terry, et al.
Published: (2025)

Adaptive Pre-training Data Detection for Large Language Models via Surprising Tokens
by: Zhang, Anqi, et al.
Published: (2024)

TFL: Targeted Bit-Flip Attack on Large Language Model
by: Guo, Jingkai, et al.
Published: (2026)

Deciphering the Chaos: Enhancing Jailbreak Attacks via Adversarial Prompt Translation
by: Li, Qizhang, et al.
Published: (2024)

SBFA: Single Sneaky Bit Flip Attack to Break Large Language Models
by: Guo, Jingkai, et al.
Published: (2025)

AdvPrompter: Fast Adaptive Adversarial Prompting for LLMs
by: Paulus, Anselm, et al.
Published: (2024)

Image Hijacks: Adversarial Images can Control Generative Models at Runtime
by: Bailey, Luke, et al.
Published: (2023)

Dynamic Adversarial Fine-Tuning Reorganizes Refusal Geometry
by: Lan, Wenhao, et al.
Published: (2026)

Hijacking Large Language Models via Adversarial In-Context Learning
by: Zhou, Xiangyu, et al.
Published: (2023)

Adversarial Decoding: Generating Readable Documents for Adversarial Objectives
by: Zhang, Collin, et al.
Published: (2024)

Route to Rome Attack: Directing LLM Routers to Expensive Models via Adversarial Suffix Optimization
by: Tang, Haochun, et al.
Published: (2026)

Certifying LLM Safety against Adversarial Prompting
by: Kumar, Aounon, et al.
Published: (2023)

Time Will Tell: Timing Side Channels via Output Token Count in Large Language Models
by: Zhang, Tianchen, et al.
Published: (2024)

AdvPrefix: An Objective for Nuanced LLM Jailbreaks
by: Zhu, Sicheng, et al.
Published: (2024)

Beyond Indistinguishability: Measuring Extraction Risk in LLM APIs
by: Liu, Ruixuan, et al.
Published: (2026)

How Different Tokenization Algorithms Impact LLMs and Transformer Models for Binary Code Analysis
by: Mostafa, Ahmed, et al.
Published: (2025)

Advancing Adversarial Suffix Transfer Learning on Aligned Large Language Models
by: Liu, Hongfu, et al.
Published: (2024)

LARGO: Latent Adversarial Reflection through Gradient Optimization for Jailbreaking LLMs
by: Li, Ran, et al.
Published: (2025)

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent
by: Biswas, Sajib, et al.
Published: (2025)

AutoAdv: Automated Adversarial Prompting for Multi-Turn Jailbreaking of Large Language Models
by: Reddy, Aashray, et al.
Published: (2025)

LLM Unlearning Should Be Form-Independent
by: Ye, Xiaotian, et al.
Published: (2025)

MPAT: Building Robust Deep Neural Networks against Textual Adversarial Attacks
by: Zhang, Fangyuan, et al.
Published: (2024)

Graded Suspiciousness of Adversarial Texts to Human
by: Tonni, Shakila Mahjabin, et al.
Published: (2024)

MARAGE: Transferable Multi-Model Adversarial Attack for Retrieval-Augmented Generation Data Extraction
by: Hu, Xiao, et al.
Published: (2025)

AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks
by: Zeng, Yifan, et al.
Published: (2024)

Robust LLM safeguarding via refusal feature adversarial training
by: Yu, Lei, et al.
Published: (2024)

Proving membership in LLM pretraining data via data watermarks
by: Wei, Johnny Tian-Zheng, et al.
Published: (2024)

When the Same Coefficients Reach Different Places: Asymmetric Realizability in Transplanting Tokenizers across Large Language Models
by: Liu, Xiaoze, et al.
Published: (2025)

Rubrics as an Attack Surface: Stealthy Preference Drift in LLM Judges
by: Ding, Ruomeng, et al.
Published: (2026)

Differentially Private Next-Token Prediction of Large Language Models
by: Flemings, James, et al.
Published: (2024)

Saliency Attention and Semantic Similarity-Driven Adversarial Perturbation
by: Waghela, Hetvi, et al.
Published: (2024)

IDT: Dual-Task Adversarial Attacks for Privacy Protection
by: Faustini, Pedro, et al.
Published: (2024)

Towards More Realistic Extraction Attacks: An Adversarial Perspective
by: More, Yash, et al.
Published: (2024)