Cover Image

Acceptance Cards:A Four-Diagnostic Standard for Safe Fine-Tuning Defense Claims

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Konrad, Phongsakon Mark, Tanyel, Toygar, Ayvaz, Serkan
Format:	Preprint
Published:	2026
Subjects:	Cryptography and Security Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Security in the Fine-Tuning Lifecycle of Large Language Models: Threats, Defenses,Evaluation, and Future Directions
by: Li, Wenjuan, et al.
Published: (2026)

Safe Delta: Consistently Preserving Safety when Fine-Tuning LLMs on Diverse Datasets
by: Lu, Ning, et al.
Published: (2025)

Beyond Known Reality: Exploiting Counterfactual Explanations for Medical Research
by: Tanyel, Toygar, et al.
Published: (2023)

Checkpoint-GCG: Auditing and Attacking Fine-Tuning-Based Prompt Injection Defenses
by: Yang, Xiaoxue, et al.
Published: (2025)

Harmful Fine-tuning Attacks and Defenses for Large Language Models: A Survey
by: Huang, Tiansheng, et al.
Published: (2024)

Self-Mined Hardness for Safety Fine-Tuning
by: Gupta, Prakhar, et al.
Published: (2026)

PrivTune: Efficient and Privacy-Preserving Fine-Tuning of Large Language Models via Device-Cloud Collaboration
by: Liu, Yi, et al.
Published: (2025)

When Safety Geometry Collapses: Fine-Tuning Vulnerabilities in Agentic Guard Models
by: Hossain, Ismail, et al.
Published: (2026)

PACZero: PAC-Private Fine-Tuning of Language Models via Sign Quantization
by: Ertan, Murat Bilgehan, et al.
Published: (2026)

Semantic-Aware Contrastive Fine-Tuning: Boosting Multimodal Malware Classification with Discriminative Embeddings
by: Sanchez, Ivan Montoya, et al.
Published: (2025)

CTIGuardian: A Few-Shot Framework for Mitigating Privacy Leakage in Fine-Tuned LLMs
by: Arachchige, Shashie Dilhara Batan, et al.
Published: (2025)

Silent Sabotage During Fine-Tuning: Few-Shot Rationale Poisoning of Compact Medical LLMs
by: Xie, Jingyuan, et al.
Published: (2026)

No, of Course I Can! Deeper Fine-Tuning Attacks That Bypass Token-Level Safety Mechanisms
by: Kazdan, Joshua, et al.
Published: (2025)

BrowseSafe: Understanding and Preventing Prompt Injection Within AI Browser Agents
by: Zhang, Kaiyuan, et al.
Published: (2025)

SPARD: Defending Harmful Fine-Tuning Attack via Safety Projection with Relevance-Diversity Data Selection
by: Chen, Shuhao, et al.
Published: (2026)

Attacks and Defenses Against LLM Fingerprinting
by: Kurian, Kevin, et al.
Published: (2025)

Optimal Defenses Against Gradient Reconstruction Attacks
by: Chen, Yuxiao, et al.
Published: (2024)

Mitigating the Structural Bias in Graph Adversarial Defenses
by: Fang, Junyuan, et al.
Published: (2025)

DP-Adam-AC: Privacy-preserving Fine-Tuning of Localizable Language Models Using Adam Optimization with Adaptive Clipping
by: Yang, Ruoxing
Published: (2025)

A Causal Perspective for Enhancing Jailbreak Attack and Defense
by: Pan, Licheng, et al.
Published: (2026)

Stealthy Poisoning Attacks Bypass Defenses in Regression Settings
by: Carnerero-Cano, Javier, et al.
Published: (2026)

The Autonomy Tax: Defense Training Breaks LLM Agents
by: Li, Shawn, et al.
Published: (2026)

SHIELD: Secure Hypernetworks for Incremental Expansion Learning Defense
by: Krukowski, Patryk, et al.
Published: (2025)

Uncovering, Explaining, and Mitigating the Superficial Safety of Backdoor Defense
by: Min, Rui, et al.
Published: (2024)

Seed Hijacking of LLM Sampling and Quantum Random Number Defense
by: You, Ziyang, et al.
Published: (2026)

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques
by: Jaffal, Niveen O., et al.
Published: (2025)

SoK: Benchmarking Poisoning Attacks and Defenses in Federated Learning
by: Zhang, Heyi, et al.
Published: (2025)

Attacks and Defenses for Generative Diffusion Models: A Comprehensive Survey
by: Truong, Vu Tuan, et al.
Published: (2024)

Training RL Agents for Multi-Objective Network Defense Tasks
by: Molina-Markham, Andres, et al.
Published: (2025)

Combining Stochastic Defenses to Resist Gradient Inversion: An Ablation Study
by: Scheliga, Daniel, et al.
Published: (2022)

Enhancing Continual Learning for Software Vulnerability Prediction: Addressing Catastrophic Forgetting via Hybrid-Confidence-Aware Selective Replay for Temporal LLM Fine-Tuning
by: Dou, Xuhui, et al.
Published: (2026)

Adversaries Can Misuse Combinations of Safe Models
by: Jones, Erik, et al.
Published: (2024)

Semantic Chameleon: Corpus-Dependent Poisoning Attacks and Defenses in RAG Systems
by: Thornton, Scott
Published: (2026)

Backdoor Vectors: a Task Arithmetic View on Backdoor Attacks and Defenses
by: Pawlak, Stanisław, et al.
Published: (2025)

A Survey on Model Extraction Attacks and Defenses for Large Language Models
by: Zhao, Kaixiang, et al.
Published: (2025)

Optimizing Cyber Defense in Dynamic Active Directories through Reinforcement Learning
by: Goel, Diksha, et al.
Published: (2024)

A Survey of Model Extraction Attacks and Defenses in Distributed Computing Environments
by: Zhao, Kaixiang, et al.
Published: (2025)

IRSKG: Unified Intrusion Response System Knowledge Graph Ontology for Cyber Defense
by: Panigrahi, Damodar, et al.
Published: (2024)

Defending the Edge: Representative-Attention Defense against Backdoor Attacks in Federated Learning
by: Obioma, Chibueze Peace, et al.
Published: (2025)

Adversarial Robustness in Financial Machine Learning: Defenses, Economic Impact, and Governance Evidence
by: Baviskar, Samruddhi
Published: (2025)