Cover Image

Think Before Refusal : Triggering Safety Reflection in LLMs to Mitigate False Refusal Behavior

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Si, Shengyun, Wang, Xinpeng, Zhai, Guangyao, Navab, Nassir, Plank, Barbara
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Surgical, Cheap, and Flexible: Mitigating False Refusal in Language Models via Single Vector Ablation
by: Wang, Xinpeng, et al.
Published: (2024)

FalseReject: A Resource for Improving Contextual Safety and Mitigating Over-Refusals in LLMs via Structured Reasoning
by: Zhang, Zhehao, et al.
Published: (2025)

Refuse Whenever You Feel Unsafe: Improving Safety in LLMs via Decoupled Refusal Training
by: Yuan, Youliang, et al.
Published: (2024)

Refusal Direction is Universal Across Safety-Aligned Languages
by: Wang, Xinpeng, et al.
Published: (2025)

Learning to Refuse: Towards Mitigating Privacy Risks in LLMs
by: Liu, Zhenhua, et al.
Published: (2024)

Cannot or Should Not? Automatic Analysis of Refusal Composition in IFT/RLHF Datasets and Refusal Behavior of Black-Box LLMs
by: von Recum, Alexander, et al.
Published: (2024)

Can LLMs Refuse Questions They Do Not Know? Measuring Knowledge-Aware Refusal in Factual Tasks
by: Pan, Wenbo, et al.
Published: (2025)

Refusal Steering: Fine-grained Control over LLM Refusal Behaviour for Sensitive Topics
by: García-Ferrero, Iker, et al.
Published: (2025)

Refusal Behavior in Large Language Models: A Nonlinear Perspective
by: Hildebrandt, Fabian, et al.
Published: (2025)

Is It Thinking or Cheating? Detecting Implicit Reward Hacking by Measuring Reasoning Effort
by: Wang, Xinpeng, et al.
Published: (2025)

When Safety Blocks Sense: Measuring Semantic Confusion in LLM Refusals
by: Anonto, Riad Ahmed, et al.
Published: (2025)

RefusalBench: Generative Evaluation of Selective Refusal in Grounded Language Models
by: Muhamed, Aashiq, et al.
Published: (2025)

RefusalGuard: Geometry-Preserving Fine-Tuning for Safety in LLMs
by: Asif, Sadia, et al.
Published: (2026)

Look at the Text: Instruction-Tuned Language Models are More Robust Multiple Choice Selectors than You Think
by: Wang, Xinpeng, et al.
Published: (2024)

Does Refusal Training in LLMs Generalize to the Past Tense?
by: Andriushchenko, Maksym, et al.
Published: (2024)

Abstain-R1: Calibrated Abstention and Post-Refusal Clarification via Verifiable RL
by: Zhai, Skylar, et al.
Published: (2026)

Deactivating Refusal Triggers: Understanding and Mitigating Overrefusal in Safety Alignment
by: Xue, Zhiyu, et al.
Published: (2026)

Learn to Refuse: Making Large Language Models More Controllable and Reliable through Knowledge Scope Limitation and Refusal Mechanism
by: Cao, Lang
Published: (2023)

Tracing the Dynamics of Refusal: Exploiting Latent Refusal Trajectories for Robust Jailbreak Detection
by: Hu, Xulin, et al.
Published: (2026)

COSMIC: Generalized Refusal Direction Identification in LLM Activations
by: Siu, Vincent, et al.
Published: (2025)

From Hard Refusals to Safe-Completions: Toward Output-Centric Safety Training
by: Yuan, Yuan, et al.
Published: (2025)

ORFuzz: Fuzzing the "Other Side" of LLM Safety -- Testing Over-Refusal
by: Zhang, Haonan, et al.
Published: (2025)

Linearly Decoding Refused Knowledge in Aligned Language Models
by: Shrivastava, Aryan, et al.
Published: (2025)

RepIt: Steering Language Models with Concept-Specific Refusal Vectors
by: Siu, Vincent, et al.
Published: (2025)

OR-Bench: An Over-Refusal Benchmark for Large Language Models
by: Cui, Justin, et al.
Published: (2024)

Measuring and Eliminating Refusals in Military Large Language Models
by: FitzGerald, Jack, et al.
Published: (2026)

Where Do Reasoning Models Refuse?
by: Yamaguchi, Kureha, et al.
Published: (2025)

Programming Refusal with Conditional Activation Steering
by: Lee, Bruce W., et al.
Published: (2024)

When Refusals Fail: Unstable Safety Mechanisms in Long-Context LLM Agents
by: Hadeliya, Tsimur, et al.
Published: (2025)

From Threat to Tool: Leveraging Refusal-Aware Injection Attacks for Safety Alignment
by: Chae, Kyubyung, et al.
Published: (2025)

Mitigating Over-Refusal in Aligned Large Language Models via Inference-Time Activation Energy
by: Jiang, Eric Hanchen, et al.
Published: (2025)

Beyond No: Quantifying AI Over-Refusal and Emotional Attachment Boundaries
by: Noever, David, et al.
Published: (2025)

From Rogue to Safe AI: The Role of Explicit Refusals in Aligning LLMs with International Humanitarian Law
by: Mavi, John, et al.
Published: (2025)

Oyster-I: Beyond Refusal -- Constructive Safety Alignment for Responsible Language Models
by: Duan, Ranjie, et al.
Published: (2025)

Towards Understanding and Improving Refusal in Compressed Models via Mechanistic Interpretability
by: Chhabra, Vishnu Kabir, et al.
Published: (2025)

The Instability of Safety: How Random Seeds and Temperature Expose Inconsistent LLM Refusal Behavior
by: Larsen, Erik
Published: (2025)

Poison Once, Refuse Forever: Weaponizing Alignment for Injecting Bias in LLMs
by: Mamun, Md Abdullah Al, et al.
Published: (2025)

Refusal in Language Models Is Mediated by a Single Direction
by: Arditi, Andy, et al.
Published: (2024)

How Post-Training Reshapes LLMs: A Mechanistic View on Knowledge, Truthfulness, Refusal, and Confidence
by: Du, Hongzhe, et al.
Published: (2025)

Forbidden Science: Dual-Use AI Challenge Benchmark and Scientific Refusal Tests
by: Noever, David, et al.
Published: (2025)