Cover Image

Adaptive Instruction Composition for Automated LLM Red-Teaming

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zymet, Jesse, Luo, Andy, Shinde, Swapnil, Wadhwa, Sahil, Chen, Emily
Format:	Preprint
Published:	2026
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

Capability-Based Scaling Trends for LLM-Based Red-Teaming
by: Panfilov, Alexander, et al.
Published: (2025)

Constitutional Classifiers: Defending against Universal Jailbreaks across Thousands of Hours of Red Teaming
by: Sharma, Mrinank, 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)

SafeSearch: Automated Red-Teaming of LLM-Based Search Agents
by: Dong, Jianshuo, et al.
Published: (2025)

The Road of Adaptive AI for Precision in Cybersecurity
by: Garg, Sahil
Published: (2025)

Gandalf the Red: Adaptive Security for LLMs
by: Pfister, Niklas, et al.
Published: (2025)

Instructional Segment Embedding: Improving LLM Safety with Instruction Hierarchy
by: Wu, Tong, et al.
Published: (2024)

DiveR-CT: Diversity-enhanced Red Teaming Large Language Model Assistants with Relaxing Constraints
by: Zhao, Andrew, et al.
Published: (2024)

A Generative Approach to LLM Harmfulness Mitigation with Red Flag Tokens
by: Dobre, David, et al.
Published: (2025)

Instructions as Backdoors: Backdoor Vulnerabilities of Instruction Tuning for Large Language Models
by: Xu, Jiashu, et al.
Published: (2023)

SAGE-RT: Synthetic Alignment data Generation for Safety Evaluation and Red Teaming
by: Kumar, Anurakt, et al.
Published: (2024)

LLM Ghostbusters: Surgical Hallucination Suppression via Adaptive Unlearning
by: Spracklen, Joseph, et al.
Published: (2026)

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

Systematically Analyzing Prompt Injection Vulnerabilities in Diverse LLM Architectures
by: Benjamin, Victoria, et al.
Published: (2024)

Are My Optimized Prompts Compromised? Exploring Vulnerabilities of LLM-based Optimizers
by: Zhao, Andrew, et al.
Published: (2025)

T-MAP: Red-Teaming LLM Agents with Trajectory-aware Evolutionary Search
by: Lee, Hyomin, et al.
Published: (2026)

X-Teaming: Multi-Turn Jailbreaks and Defenses with Adaptive Multi-Agents
by: Rahman, Salman, et al.
Published: (2025)

SECA: Semantically Equivalent and Coherent Attacks for Eliciting LLM Hallucinations
by: Liang, Buyun, et al.
Published: (2025)

ARES: Adaptive Red-Teaming and End-to-End Repair of Policy-Reward System
by: Liang, Jiacheng, et al.
Published: (2026)

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

SIRAJ: Diverse and Efficient Red-Teaming for LLM Agents via Distilled Structured Reasoning
by: Zhou, Kaiwen, et al.
Published: (2025)

REALISTA: Realistic Latent Adversarial Attacks that Elicit LLM Hallucinations
by: Liang, Buyun, et al.
Published: (2026)

Prompt2Fingerprint: Plug-and-Play LLM Fingerprinting via Text-to-Weight Generation
by: Chen, Sixu, et al.
Published: (2026)

IH-Challenge: A Training Dataset to Improve Instruction Hierarchy on Frontier LLMs
by: Guo, Chuan, et al.
Published: (2026)

Defending Against Alignment-Breaking Attacks via Robustly Aligned LLM
by: Cao, Bochuan, et al.
Published: (2023)

From Firewalls to Frontiers: AI Red-Teaming is a Domain-Specific Evolution of Cyber Red-Teaming
by: Sinha, Anusha, et al.
Published: (2025)

Follow My Instruction and Spill the Beans: Scalable Data Extraction from Retrieval-Augmented Generation Systems
by: Qi, Zhenting, et al.
Published: (2024)

Measuring Real-World Prompt Injection Attacks in LLM-based Resume Screening
by: Zhang, Mohan, et al.
Published: (2026)

Federated In-Context LLM Agent Learning
by: Wu, Panlong, et al.
Published: (2024)

CPE-Identifier: Automated CPE identification and CVE summaries annotation with Deep Learning and NLP
by: Hu, Wanyu, et al.
Published: (2024)

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

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

Automated Software Vulnerability Static Code Analysis Using Generative Pre-Trained Transformer Models
by: Pelofske, Elijah, et al.
Published: (2024)

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

Policy-Invisible Violations in LLM-Based Agents
by: Wu, Jie, et al.
Published: (2026)

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

Weird Generalization and Inductive Backdoors: New Ways to Corrupt LLMs
by: Betley, Jan, et al.
Published: (2025)

Holistic Automated Red Teaming for Large Language Models through Top-Down Test Case Generation and Multi-turn Interaction
by: Zhang, Jinchuan, et al.
Published: (2024)

Covert Malicious Finetuning: Challenges in Safeguarding LLM Adaptation
by: Halawi, Danny, et al.
Published: (2024)

Efficient LLM Moderation with Multi-Layer Latent Prototypes
by: Chrabąszcz, Maciej, et al.
Published: (2025)