LLM Safety

LLM: Large Language Model

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36 papers in the last four weeks, up 200% on the four weeks before. 0.4% of all new papers.

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TWGuard: A Case Study of LLM Safety Guardrails for Localized Linguistic Contexts
Apr 17, 2026Hua-Rong Chu, Kuan-Chun Wang, Yao-Te HuangLanguage Model Safety Evaluation LLM Guardrails
Chunghwa Telecom Laboratories
FineSteer: A Unified Framework for Fine-Grained Inference-Time Steering in Large Language Models
Apr 16, 2026Zixuan Weng, Jinghuai Zhang, Kunlin Cai +3Language Model Steering LLM Safety
University of California, Los Angeles
Segment-Level Coherence for Robust Harmful Intent Probing in LLMs
Apr 16, 2026Xuanli He, Bilgehan Sel, Faizan Ali +3LLM Safety LLM Jailbreak Attacks
University College London · Virginia Tech · Anthropic
Bounded Autonomy for Enterprise AI: Typed Action Contracts and Consumer-Side Execution
Apr 16, 2026Sarmad Sohail, Ghufran HaiderLLM Guardrails AI Agent Security
CausalDetox: Causal Head Selection and Intervention for Language Model Detoxification
Apr 16, 2026Yian Wang, Yuen Chen, Agam Goyal +1Causal Reasoning in Language Models LLM Safety
Department of Computer Science University of Illinois, Urbana-Champaign Champaign, IL 61801
HazardArena: Evaluating Semantic Safety in Vision-Language-Action Models
Apr 14, 2026Zixing Chen, Yifeng Gao, Li Wang +8Robotics AI Safety Evaluation
Fudan University · City University of Hong Kong · Shanghai Innovation Institute
Large Language Models Generate Harmful Responses Using a Distinct Mechanism, Shared Across Harm Types
Apr 10, 2026Hadas Orgad, Boyi Wei, Kaden Zheng +4LLM Alignment Emergent Misalignment in Language Models
Kempner Institute, Harvard University · Princeton University · Harvard University +2
How Alignment Routes: Localizing, Scaling, and Controlling Policy Circuits in Language Models
Apr 6, 2026Gregory N. FrankLLM Interpretability LLM Safety
Chief Scientist, Molt AI Corp.
Over-Refusal and Representation Subspaces: A Mechanistic Analysis of Task-Conditioned Refusal in Aligned LLMs
Mar 29, 2026Utsav Maskey, Mark Dras, Usman NaseemLLM Interpretability LLM Refusal Behavior
Macquarie University
Risk-Adjusted Harm Scoring for Automated Red Teaming for LLMs in Financial Services
Mar 11, 2026Fabrizio Dimino, Bhaskarjit Sarmah, Stefano PasqualiLanguage Model Safety Evaluation LLM Safety
1Domyn, New York, US · 2Domyn, New York, US · 3Domyn, New York, US
MUSE: A Run-Centric Platform for Multimodal Unified Safety Evaluation of Large Language Models
Mar 3, 2026Zhongxi Wang, Yueqian Lin, Jingyang Zhang +3LLM Safety Benchmarks Language Model Safety Evaluation
1Duke University · 2Virtue AI
YuFeng-XGuard: A Reasoning-Centric, Interpretable, and Flexible Guardrail Model for Large Language Models
Jan 22, 2026Junyu Lin, Meizhen Liu, Xiufeng Huang +12LLM Guardrails LLM Interpretability
Alibaba-AAIG
In Vino Veritas and Vulnerabilities: Examining LLM Safety via Drunk Language Inducement
Jan 19, 2026Anudeex Shetty, Aditya Joshi, Salil S. KanhereLanguage Model Safety Evaluation Adversarial Attacks on LLMs
School of Computer Science and Engineering, UNSW Sydney, Australia · School of Computing and Information System, the University of Melbourne, Australia
Test-Time Detoxification without Training or Learning Anything
Jan 14, 2026Baturay Saglam, Dionysis KalogeriasLarge Language Model-Guided Optimization LLM Safety
Department of Electrical and Computer Engineering, Yale University, New Haven, CT.
Large language models can effectively convince people to believe conspiracies
Jan 8, 2026Thomas H. Costello, Kellin Pelrine, Matthew Kowal +6Deception in Language Models LLM Safety
Carnegie Mellon University · York University · Center for Research and Teaching in Economics +5
Bridging Mechanistic Interpretability and Prompt Engineering with Gradient Ascent for Interpretable Persona Control
Jan 6, 2026Harshvardhan Saini, Yiming Tang, Dianbo LiuLanguage Model Steering LLM Interpretability
Indian Institute of Technology (ISM), Dhanbad · National University of Singapore
The Homogenization Problem in LLMs: Towards Meaningful Diversity in AI Safety
Jan 3, 2026Ian Rios-SialerLLM Safety
Independent Researcher San Francisco, CA, USA
Safety boundary maintenance in consumer AI systems responding to pediatric health queries: a cross-platform benchmark evaluation under naturalistic and adversarially pressured conditions
Dec 26, 2025Vahideh Zolfaghari, Leila Mashhadi, Mitra Ahadi +2Healthcare LLM Safety
Medical Sciences Education Research Center, Mashhad University of Medical Sciences, Mashhad, Iran. · Student Research Committee, Department of Health Information Technology and Management, Medical Informatics, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran. · Department of Anesthesiology and Intensive Care, Mashhad University of Medical Sciences, Mashhad, Iran. +2
SGM: Safety Glasses for Multimodal Large Language Models via Neuron-Level Detoxification
Dec 17, 2025Hongbo Wang, AprilPyone MaungMaung, Isao EchizenMultimodal Robustness LLM Safety
1Graduate School of Information Science and Technology, The University of Tokyo, Japan · 2Information and Society Research Division, National Institute of Informatics, Japan · 3The Graduate University for Advanced Studies, SOKENDAI, Japan
Training-Free Policy Violation Detection via Activation-Space Whitening in LLMs
Dec 3, 2025Oren Rachmil, Avishag Shapira, Roy Betser +5Language Model Safety Evaluation LLM Auditing
Fujitsu Research of Europe · Ben-Gurion University of the Negev
A Neurosymbolic Approach to Natural Language Formalization and Verification
Nov 12, 2025Chenyang An, Sam Bayless, Stefano Buliani +27Formal Verification LLM Safety
Amazon Web Services · University College London · Queen Mary University of London +1
Moloch's Bargain: Emergent Misalignment When LLMs Compete for Audiences
Oct 7, 2025Batu El, James ZouLLM Alignment LLM Safety
Stanford University
Context Misleads LLMs: The Role of Context Filtering in Maintaining Safe Alignment of LLMs
Aug 9, 2025Jinhwa Kim, Ian G. HarrisLLM Safety Alignment LLM Safety
Department of Computer Science University of California, Irvine
LLMs Encode Harmfulness and Refusal Separately
Jul 16, 2025Jiachen Zhao, Jing Huang, Zhengxuan Wu +2LLM Interpretability LLM Refusal Behavior
Northeastern University · Stanford University
PRISON: Unmasking the Criminal Potential of Large Language Models
Jun 19, 2025Xinyi Wu, Geng Hong, Pei Chen +3Language Model Safety Evaluation LLM Auditing
Fudan University · Shanghai Innovation Institute
HauntAttack: When Attack Follows Reasoning as a Shadow
Jun 8, 2025Jingyuan Ma, Rui Li, Zheng Li +4Adversarial Attacks on LLMs Jailbreak Attacks
State Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University · StepFun · Department of Computing, The Hong Kong Polytechnic University +1
Popular but Wrong: Understanding and Mitigating LLM Overconfidence through Knowledge Popularity
May 23, 2025Shiyu Ni, Keping Bi, Jiafeng Guo +1LLM Hallucination Mitigation Confidence Estimation in Language Models
CAS Key Lab of Network Data Science and Technology, ICT, CAS · State Key Laboratory of AI Safety · University of Chinese Academy of Sciences
Decoding One Safety Trigger Token for Balancing Safety and Usability in Large Language Models
May 12, 2025Haoran Gu, Handing Wang, Yi Mei +2LLM Safety Alignment LLM Safety
Xidian University · Victoria University of Wellington · Westlake University
Using Mechanistic Interpretability to Craft Adversarial Attacks against Large Language Models
Mar 8, 2025Thomas Winninger, Boussad Addad, Katarzyna KapustaAdversarial Prompt Generation Adversarial Attacks on LLMs
*Work started during internship at Thales.
Divide and Conquer: A Hybrid Strategy Defeats Multimodal Large Language Models
Dec 21, 2024Yanxu Mao, Peipei Liu, Tiehan Cui +3Adversarial Attacks on LLMs Multimodal Large Language Models
School of Computer Science and Technology, Shanghai Jiao Tong University, Shanghai, China · Zhongguancun Laboratory, Beijing, China · School of Software, Henan University, Kaifeng, China +1

Apr 17, 2026, cs.CRJ/K move · Enter open · S save

TWGuard: A Case Study of LLM Safety Guardrails for Localized Linguistic Contexts

Hua-Rong Chu, Kuan-Chun Wang, Yao-Te Huang

Chunghwa Telecom Laboratories

Language Model Safety Evaluation LLM Guardrails LLM Safety

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Safety guardrails have become an active area of research in AI safety, aimed at ensuring the appropriate behavior of large language models (LLMs). However, existing research lacks consideration of nuances across linguistic and cultural contexts, resulting in a gap between reported performance and in-the-wild effectiveness. To address this issue, this paper proposes an approach to optimize guardrail models for a designated linguistic context by leveraging a curated dataset tailored to local linguistic characteristics, targeting the Taiwan linguistic context as a representative example of localized deployment challenges. The proposed approach yields TWGuard, a linguistic context-optimized guardrail model that achieves a huge gain (+0.289 in F1) compared to the foundation model and significantly outperforms the strongest baseline in practical use (-0.037 in false positive rate, a 94.9% reduction). Together, this work lays a foundation for regional communities to establish AI safety standards grounded in their own linguistic contexts, rather than accepting boundaries imposed by dominant languages. The inadequacy of the latter is reconfirmed by our findings.

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