LLM Safety Evaluation

LLM: Large Language Model

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16 papers in the last four weeks, level with the four weeks before. 0.2% of all new papers.

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Safe Alone, Unsafe Together: Safeguarding Against Implicit Toxicity When Benign Images Combine
Jul 1, 2026Jiaxian Lv, Shiyao Cui, Yingkang Wang +3Toxicity Detection Safety Filtering
The Conversational AI (CoAI) Group, DCST, Tsinghua University
EMPATH: A Multilingual Auditor-Judge Benchmark for Safety Evaluation of Emotional-Support Chatbots
Jun 29, 2026Camilo Chacón SartoriLLM Safety Benchmarks Multilingual Language Model Evaluation
MindSurf
EvalSafetyGap: A Hybrid Survey and Conceptual Framework for LLM Evaluation-Safety Failures
Jun 29, 2026Buğra Alperen Uluırmak, Rifat KurbanAI Alignment LLM Safety Alignment
Erciyes University, Türkiye. · Abdullah Gül University, Türkiye.
SCARCE: Scalable Cascade Analysis for Rare-event Characterisation via Embeddings
Jun 28, 2026Yingjie Wang, Yi Dong, Edmund Lau +3LLM Safety Evaluation Rare-Event Estimation
University of Liverpool, UK · UK AI Security Institute, UK · Loughborough University, UK +1
The Joint Effect of Quantization and Sampling Temperature on LLM Safety Alignment: A Factorial Analysis
Jun 28, 2026Hari Prasad, Ritam PalLLM Safety Benchmarks LLM Quantization
Conscious Engines
Paved with True Intents: Intent-Aware Training Improves LLM Safety Classification Across Training Regimes
Jun 25, 2026Jeremias Ferrao, Niclas Müller-Hof, Iustin Sîrbu +2LLM Safety Evaluation LLM Post-Training
University of Groningen · University Politehnica of Bucharest · NVIDIA
Necessary but Not Sufficient: Temperature Control and Reproducibility in LLM-as-Judge Safety Evaluations
Jun 24, 2026Hiroki TambaLLM Evaluation LLM-as-a-Judge
Tamba Research Academy
RAS: Measuring LLM Safety Through Refusal Alignment
Jun 24, 2026Chang-Chieh Huang, Yan-Lun Chen, Chia-Mu Yu +1LLM Safety Alignment LLM Safety
National Yang Ming Chiao Tung University · Hon Hai Research Institute
A Red Teaming Framework for Large Language Models: A Case Study on Faithfulness Evaluation
Jun 24, 2026Abrar Alotaibi, Raed Mughus, Moataz AhmedMultilingual Language Model Evaluation LLM Evaluation
Information and Computer Science Department, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia. · College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, Dammam, 31441, Saudi Arabia. · SDAIA-KFUPM Joint Research Center for Artificial Intelligence, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia.
Do Thinking Tokens Help with Safety?
Jun 23, 2026Narutatsu Ri, Abhishek Panigrahi, Sanjeev AroraLLM Refusal Behavior LLM Safety Evaluation
Princeton Language and Intelligence, Princeton University
Distributed Quality-Diversity Search for Toxicity in Large Language Models
Jun 23, 2026Onkar Shelar, Travis DesellAdversarial Prompt Generation LLM Red Teaming
Rochester Institute of Technology, Rochester NY 14623, USA
Old Fictions, New Skins: Evaluating the Manipulative Capabilities of LLMs in Healthcare
Jun 20, 2026Gathoni Ireri, Roger D. OdipoHealthcare Deception in Language Models
1ILINA Program · 2Haki AI
FinRED: An Expert-Guided Benchmark Generation and Evaluation Framework for Financial LLM Red-Teaming
Jun 18, 2026Chaeyun Kim, Daeyoung Park, Junghwan Kim +4LLM Safety Benchmarks Financial Services
DATUMO INC., Republic of Korea · Korea Advanced Institute of Science and Technology (KAIST), Republic of Korea · Financial Security Institute (FSI), Republic of Korea
Analyzing the Narration Gap in LLM-Solver Loops
Jun 17, 2026Zunchen Huang, Songgaojun DengAdversarial Attacks on LLMs Formal Verification
Centrum Wiskunde & Informatica, Amsterdam, The Netherlands · Eindhoven University of Technology, Eindhoven, The Netherlands
SciRisk-Bench: A Risk-Dimension-Aware Benchmark for AI4Science Safety
Jun 17, 2026Linghao Feng, Yinqian Sun, Dongqi Liang +8LLM Safety Benchmarks AI for Science
Brain-inspired Cognitive Intelligence Lab, Institute of Automation, Chinese Academy of Sciences, Beijing, China · School of Future Technology, University of Chinese Academy of Sciences, China · School of Artificial Intelligence, University of Chinese Academy of Sciences, China +5
Automated jailbreak attack targeting multiple defense strategies
Jun 15, 2026Qi Wang, Chengcheng Wan, Weijia He +4Adversarial Prompt Generation LLM Jailbreak Attacks
East China Normal University Shanghai, China · East China Normal University, Shanghai Innovation Institute Shanghai, China · University of Southampton Southampton, England +2
Risk-Aware LLM Agents for Geospatial Data Retrieval: Design and Preliminary Adversarial Evaluation
Jun 13, 2026Kyle Gao, Joel Cumming, Jonathan Li +2Multi-Agent LLM Systems LLM Tool Use
Dept. of Systems Design Engineering, University of Waterloo, Waterloo, ON, N2L 3G1, Canada · SkyWatch, Kitchener, ON, N2H 2G8, Canada · Dept. of Geography and Environmental Management, University of Waterloo, Waterloo, ON, N2L 3G1, Canada +1
BELLS-O: Evaluating the Operational Trade-offs of LLM Supervision Systems
Jun 12, 2026Leonhard Waibl, Felix Michalak, Hadrien MariacciaLLM Safety Benchmarks LLM Guardrails
University of Graz, Graz, Austria · Supervised Program for Alignment Research (SPAR) · Centre pour la Sécurité de l’IA (CeSIA), Paris, France.
Safeguard-Conditioned Uplift: Measuring Utility-Risk Frontiers for Dual-Use Biology Assistants
Jun 12, 2026Dipesh Tharu MahatoAI Safety Evaluation LLM Safety Evaluation
New York University
Risk Under Pressure: Compute-Aware Evaluation of Adversarial Robustness in Language Models
Jun 9, 2026Malikeh Ehghaghi, Boglárka Ecsedi, Marsha Chechik +1LLM Alignment Neural Network Robustness
University of Toronto · Vector Institute · Hugging Face
Quality Is Not a Safety Proxy Under Quantization
Jun 8, 2026Sahil KadadekarLLM Quantization LLM Refusal Behavior
Independent Researcher
The Injection Paradox: Brand-Level Suppression in Safety-Trained LLM Recommendations via RAG Context Injection
Jun 8, 2026Hyunseok PaengRetrieval-Augmented Generation Adversarial Attacks on LLMs
Independent Researcher.
Reliable to Expressive: A Curriculum for Rubric-Following Safety Judges
Jun 8, 2026Yongtaek Lim, Hyeji Choi, Minwoo KimLLM-as-a-Judge LLM Safety Evaluation
AI Safety Team, DATUMO.INC, Seoul, South Korea.
Personalization Meets Safety:Mechanisms,Risks,and Mitigations in Personalized LLMs
Jun 8, 2026Yanyan Luo, Xue Han, Ruiqiao Bai +10LLM Personalization LLM Safety
Jiutian Research, China Mobile Jiutian Artificial Intelligence Technology (Beijing) Co., Ltd., Beijing, China. · Xinjiang Technical Institute of Physics and Chemistry, Chinese2026 Academy of Sciences, Beijing, China.
SafeRun: Enabling Determinism in LLM Planning for Running
Jun 8, 2026Meilin Chen, Zepeng Zhai, Jiaxuan Zhao +1LLM Planning LLM Safety Evaluation
Xiaohongshu Inc. · Institute of Information Engineering, Chinese Academy of Sciences
Sycophancy Towards Researchers Drives Performative Misalignment
Jun 7, 2026David D. Baek, Xinnuo Li, Anay Gupta +4LLM Sycophancy LLM Alignment
Massachusetts Institute of Technology, Cambridge, MA, USA · University of Michigan, Ann Arbor, MI, USA · Georgia Institute of Technology, Atlanta, GA, USA +1
Building Comparative Motivation Profiles with Instrumental Interventions
Jun 6, 2026David Vella Zarb, Rustem Turtayev, Taywon Min +2LLM Safety Evaluation Causal Interventions in Language Models
MATS · University of Cambridge · KAIST +1
SciTrace: Trajectory-Aware Safety Reasoning for Scientific Discovery Agents
Jun 6, 2026Tanush Swaminathan, Runmin Jiang, Letian Zhang +1AI Agents for Scientific Discovery LLM Safety Evaluation
Carnegie Mellon University · Allen Institute
The Governance of Human-LLM Interaction: Safety Gating, Civility Steering, and Affective Default Lock-In
Jun 6, 2026Manuele Reani, Hongjian Zhang, Hongyu TianLanguage Model Steering LLM Safety Evaluation
School of Management and Economics, The Chinese University of Hong Kong, Shenzhen, China
Safety is Contextual, LLM-Judges Are Not: Navigating the Rigid Priors of Evaluators
Jun 5, 2026Anissa Alloula, Federico Licini, Ava Batchkala +1LLM-as-a-Judge In-Context Learning
University of Oxford · Cohere
AICompanionBench: Benchmarking LLMs-as-Judges for AI Companion Safety
Jun 3, 2026Yanjing Ren, Reza Ebrahimi, TengTeng MaLLM Safety Benchmarks LLM-as-a-Judge
The School of Information Systems University of South Florida Tampa, US
PreAct-Bench: Benchmarking Predictive Monitoring in LLMs
Jun 3, 2026Hainiu Xu, Italo Luis da Silva, Jiangnan Ye +7LLM Safety Benchmarks Moral Reasoning in Language Models
King’s College London · National University of Singapore · Southern University of Science and Technology +3
Can I Take Another Dose? Evaluating LLM Decision-Making Under Temporal Uncertainty in OTC Dosing QA
Jun 2, 2026Maroof Kousar, Yibo HuTemporal Reasoning Medical QA
Illinois Institute of Technology Chicago, IL, USA
Black-box, Adaptive, Efficient, Transferable, Harmful, Applicable... Attacks Are All You Need to Break LLMs
Jun 2, 2026Vincent Limbach, Jonas Dornbusch, David Lüdke +2LLM Jailbreak Attacks LLM Safety Evaluation
Department of Computer Science, Technical University of Munich, Germany · Munich Data Science Institute · Munich Center for Machine Learning +1
DDOR: Delta Debugging for Explainable Overrefusal Testing and Repair
Jun 2, 2026Qinyan Zhou, Peixin Zhang, Jun Sun +2LLM Guardrails LLM Refusal Behavior
Southeast University, China · School of Computing and Information Systems, Singapore Management University, Singapore · Zhejiang University, China +1
Unpredictable Safety: Domain-Dependent Compliance and the Transparency Gap in Open-Weight LLMs
Jun 1, 2026Zacharie BugaudLLM Safety Alignment LLM Safety
Astera Institute
Food Noise & False Safety: A Systematic Evaluation of How LLMs Fail to Adapt to Eating Disorder Queries with Clinician Feedback
Jun 1, 2026Giulia Pucci, Emily Hemendinger, Ruizhe Li +3Mental Health LLM Safety
University of Aberdeen · University of Colorado Anschutz · Heriot-Watt University +1
Lost in Delusion: Examining LLM Safety Under User Delusions and Distress
May 31, 2026Andrew Aquilina, Chetna Nihalani, Vasudha Varadarajan +3Mental Health LLM Safety Alignment
University of Pittsburgh · Carnegie Mellon University · Fordham University
Cross-Generational Transfer of Adversarial Attacks Reveals Non-Monotonic Safety Alignment in LLMs
May 30, 2026Subhadip MitraAdversarial Attacks on LLMs LLM Red Teaming
Research Lead, Rota Labs
Quality-Diversity Evolution for Discovering Diverse Vulnerabilities in LLM Safety
May 30, 2026Subhadip MitraAdversarial Prompt Generation Adversarial Attacks on LLMs
Research Lead, Rota Labs
TRACE: Trajectory Risk-Aware Compression for Long-Horizon Agent Safety
May 30, 2026Zhepei Hong, Lin Wang, Liting Li +5AI Agent Safety LLM Safety Evaluation
University of Science and Technology of China · National University of Singapore · South China Normal University
Same Payload, Different Channel: Measuring Trust Asymmetry in Tool-Using Language Models
May 30, 2026Mohammed Sameer Syed, Rozhin YasaeiAdversarial Attacks on LLMs Prompt Injection Attacks
University of Arizona
Position: Anthropomorphic Misalignment Research Needs Stronger Evidence
May 29, 2026Vansh Gupta, Peter Nutter, Samuel Stante +5LLM Safety Evaluation
1ETH Zurich
Triaging Threats to Specialized Guardrails
May 29, 2026Wenjie Jacky Mo, Xiaofei Wen, Rui Cai +6LLM Safety Benchmarks LLM Guardrails
University of California, Davis
Beyond Attack Success Rate: Temporal Logit Observability for LLM Safety Failures
May 28, 2026Junyoung Park, Sunghwan Park, Seongyong Ju +1LLM Refusal Behavior LLM Jailbreak Attacks
Chung-Ang University
Inform, Coach, Relate, Listen: Auditing LLM Caregiving Support Roles
May 28, 2026Drishti Goel, Agam Goyal, Veda Duddu +8Healthcare LLM Auditing
University of Illinois Urbana-Champaign · University of Massachusetts Amherst · OSF HealthCare +1
SciIntBench: Measuring LLM Compliance with Research Integrity Norms Under Adversarial Framing
May 28, 2026Almene De Meran Meguimtsop, Maria Leonor Pacheco, Daniel E. AcunaAI for Science Adversarial Attacks on LLMs
Department of Computer Science, University of Colorado Boulder, Boulder, CO 80309
A Study on Question-Answer Dataset for LLM Safety Evaluation with a Focus on Illegal Activities
May 28, 2026Kenji Imamura, Masao Ideuchi, Atsushi FujitaAI Safety Evaluation LLM Safety Evaluation
National Institute of Information and Communications Technology 3-5 Hikaridai, Seika-cho, Soraku-gun, Kyoto, 619-0289, Japan
Relevance as a Vulnerability: How Web Retrieval Degrades Safety Alignment in LLM Agents
May 28, 2026Aditya Nawal, Manit Baser, Mohan GurusamyAI Agent Security Benchmarks LLM Safety Evaluation
Department of Electrical and Computer Engineering · National University of Singapore
Code as a Weapon: A Consensus-Labeled Prompt Bank for Measuring Coding-Model Compliance with Malicious-Code Requests
May 27, 2026Richard J. Young, Gregory D. MoodyClassification LLM Safety Evaluation
University of Nevada Las Vegas · Department of Information Systems · Las Vegas, NV, USA
Got a Secret? LLM Agents Can't Keep It: Evaluating Privacy in Multi-Agent Systems
May 26, 2026Aman Priyanshu, Supriti Vijay, Esha PahwaData Leakage Multi-Agent LLM Systems
Foundation AI · USA · Corvic AI
When Medical Safety Alignment Fails: A Benchmark for Evaluating LLMs on High-Risk Medical Queries
May 26, 2026Yige Li, Jun Sun, Wei Zhao +5LLM Safety Benchmarks Healthcare
Singapore Management University · Deakin University · The University of Melbourne +2
KZ-SafetyPrompts: A Kazakh Safety Evaluation Prompt Dataset for Large Language Models
May 26, 2026Wajdi Zaghouani, Shimaa Amer Ibrahim, Aruzhan Muratbek +2LLM Safety Benchmarks Language Model Safety Evaluation
Northwestern University in Qatar
Preferred, Not Safer: Pairwise Preference Is a Poor Proxy for Clinical Safety
May 25, 2026Fay Elhassan, David Sasu, Alexandra Kulinkina +2LLM Safety Benchmarks Human Preference Evaluation
LiGHT Laboratory, EPFL, Lausanne, Switzerland
SafetyRepro: Configuration-Conditional Rank Instability on Alignment Benchmarks
May 25, 2026Yanhang Li, Zhichao Fan, Zexin ZhuangPairwise Comparison Pairwise Preference Evaluation
Northeastern University, Boston, MA, USA · University of Illinois Urbana-Champaign, Urbana, IL, USA · Southern Methodist University, Dallas, TX, USA
From Automation to Collaboration: Human-in-the-Loop Methods for Safe and Trustworthy NLP
May 24, 2026Most. Sharmin Sultana Samu, MD. Tanvir Ahmed Seum, Md. Rakibul IslamLLM Auditing Human-in-the-Loop Annotation
Department of Computer Science and Engineering, BRAC University, Dhaka-1212. · Department of Electrical and Electronic Engineering, Rajshahi University of Engineering and Technology, Rajshahi-6204.
Furina: Fragmented Uncertainty-Driven Refusal Instability Attack
May 24, 2026Tongxi Wu, Jian Zhang, Yang GaoAdversarial Attacks on VLMs LLM Safety
School of Intelligence Science and Technology, Nanjing University, Suzhou, China · State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China
Open-source LLMs administer maximum electric shocks in a Milgram-like obedience experiment
May 20, 2026Roland Pihlakas, Jan Llenzl DagohoyLLM Refusal Behavior LLM Safety Evaluation
for the Three Laws collaboration · Independent researcher · Three Laws research collaboration +2
RefusalBench: Why Refusal Rate Misranks Frontier LLMs on Biological Research Prompts
May 20, 2026Lukas Weidener, Marko Brkić, Mihailo Jovanović +2LLM Safety Benchmarks Language Model Safety Evaluation
Applied Scientific Intelligence, Inc.
Remembering More, Risking More: Longitudinal Safety Risks in Memory-Equipped LLM Agents
May 18, 2026Ahmad Al-Tawaha, Shangding Gu, Peizhi Niu +2Long-Horizon Agent Evaluation LLM Safety Evaluation
Virginia Tech · University of California, Berkeley · University of Illinois Urbana-Champaign

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Safe Alone, Unsafe Together: Safeguarding Against Implicit Toxicity When Benign Images Combine

Jiaxian Lv, Shiyao Cui, Yingkang Wang, Guoxin Wu+2

The Conversational AI (CoAI) Group, DCST, Tsinghua University

Toxicity Detection Safety Filtering LLM Safety Evaluation

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Multi-image content has become an increasingly prevalent form of visual communication in social media, giving rise to a new safety issue, multi-image implicit toxicity (MIIT), where each image appears benign in isolation, but harmful semantics emerge when the images are interpreted jointly. MIIT is particularly challenging for existing commercial moderation APIs and models due to the lack of explicit risky cues in each image. This paper aims to study how to identify MIIT. We first provide a formal definition of MIIT and analyze three key challenges for its detection. To alleviate the scarcity of data in this area, we construct MIIT-dataset, an image-only multi-image safety dataset covering seven representative risk categories through an automatic generation pipeline. Finally, we train MiShield with progressively distilled reasoning supervision, enabling it to produce safety judgments accompanied by explicit analyses of the correlated entities that result in the hazards. Experiments show that MiShield-8B models outperform representative moderation services and even larger-scale models, revealing its effectiveness and practical value for this widely used visual format. Warning: This paper contains potentially sensitive content.

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