Beyond Unsafe Detection: Counterfactually Anchored Evidence Attribution for Multi-Turn LLM Safety Failures
cs.CL, cs.AI
Submitted: 2026-08-17
Updated: 2026-10-13
Comments: This work is currently under review for EMNLP 2026
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- GPT-4 Technical Report
- SafeDialBench: A Fine-Grained Safety Evaluation Benchmark for Large Language Models in Multi-Turn Dialogues with Diverse Jailbreak Attacks
- OR-Bench: An Over-Refusal Benchmark for Large Language Models
- The Llama 3 Herd of Models
- DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing
- Attention-Aware GNN-based Input Defense against Multi-Turn LLM Jailbreak
- Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations
- Mistral 7B
- LLM Defenses Are Not Robust to Multi-Turn Human Jailbreaks Yet
- HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal
- Qwen2.5 Technical Report
- MultiBreak: A Scalable and Diverse Multi-turn Jailbreak Benchmark for Evaluating LLM Safety
- ShieldGemma: Generative AI Content Moderation Based on Gemma
- Universal and Transferable Adversarial Attacks on Aligned Language Models
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