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AI Safety

2972 directly classified papers

Papers per year

Papers

Permitted Knowledge Boundary: Evaluating the Knowledge-Constrained Responsiveness of Large Language Models EMNLP 2025
FC-Attack: Jailbreaking Multimodal Large Language Models via Auto-Generated Flowcharts EMNLP 2025
SafeInt: Shielding Large Language Models from Jailbreak Attacks via Safety-Aware Representation Intervention EMNLP 2025
Improving Alignment in LVLMs with Debiased Self-Judgment EMNLP 2025
Distributional Surgery for Language Model Activations EMNLP 2025
Hidden Ghost Hand: Unveiling Backdoor Vulnerabilities in MLLM-Powered Mobile GUI Agents EMNLP 2025
Towards Reverse Engineering of Language Models: A Survey EMNLP 2025
Invisible Prompts, Visible Threats: Malicious Font Injection in External Resources for Large Language Models EMNLP 2025
SafeSwitch: Steering Unsafe LLM Behavior via Internal Activation Signals EMNLP 2025
Is Safety Standard Same for Everyone? User-Specific Safety Evaluation of Large Language Models EMNLP 2025
A Knapsack by Any Other Name: Presentation impacts LLM performance on NP-hard problems EMNLP 2025
LLM Jailbreak Detection for (Almost) Free! EMNLP 2025
X-Boundary: Establishing Exact Safety Boundary to Shield LLMs from Jailbreak Attacks without Compromising Usability EMNLP 2025
Forewarned is Forearmed: Pre-Synthesizing Jailbreak-like Instructions to Enhance LLM Safety Guardrail to Potential Attacks EMNLP 2025
Breaking the Reviewer: Assessing the Vulnerability of Large Language Models in Automated Peer Review Under Textual Adversarial Attacks EMNLP 2025
How Does Cognitive Bias Affect Large Language Models? A Case Study on the Anchoring Effect in Price Negotiation Simulations EMNLP 2025
PREE: Towards Harmless and Adaptive Fingerprint Editing in Large Language Models via Knowledge Prefix Enhancement EMNLP 2025
Multilingual Collaborative Defense for Large Language Models EMNLP 2025
PD3F: A Pluggable and Dynamic DoS-Defense Framework against resource consumption attacks targeting Large Language Models EMNLP 2025
LNE-Blocking: An Efficient Framework for Contamination Mitigation Evaluation on Large Language Models EMNLP 2025
SafeConf: A Confidence-Calibrated Safety Self-Evaluation Method for Large Language Models EMNLP 2025
Not All Voices Are Rewarded Equally: Probing and Repairing Reward Models across Human Diversity EMNLP 2025
Detecting Stealthy Backdoor Samples based on Intra-class Distance for Large Language Models EMNLP 2025
PromptKeeper: Safeguarding System Prompts for LLMs EMNLP 2025
ASTPrompter: Preference-Aligned Automated Language Model Red-Teaming to Generate Low-Perplexity Unsafe Prompts EMNLP 2025