LLM Guardrails

LLM: Large Language Model

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15 papers in the last four weeks, up 36% on the four weeks before. 0.1% of all new papers.

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Latest papers 138

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EMBGuard: Constructing Hazard-Aware Guardrails for Safe Planning in Embodied Agents
May 29, 2026Dongwook Choi, Taeyoon Kwon, Bogyung Jeong +6LLM Guardrails AI Agent Safety
Department of Artificial Intelligence, Yonsei University · Department of Biomedical Engineering and the Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University · Independent Researcher
Triaging Threats to Specialized Guardrails
May 29, 2026Wenjie Jacky Mo, Xiaofei Wen, Rui Cai +6LLM Safety Benchmarks LLM Guardrails
University of California, Davis
Opir: Efficient Multi-Task Safety Classification for Toxicity, Jailbreaks, Hate Speech, and Harmful Content
May 28, 2026Ihor Stepanov, Aleksandr SmechovLanguage Model Safety Evaluation LLM Guardrails
1Knowledgator, Kyiv, Ukraine · 2Wordcab, New York, USA
FinGuard: Detecting Financial Regulatory Non-Compliance in LLM Interactions
May 28, 2026Huaixia Dou, Jie Zhu, Minghao Wu +5Language Model Safety Evaluation LLM Guardrails
Qwen DianJin Team, Alibaba Cloud Computing · Tongyi Lab, Alibaba Group · School of Computer Science and Technology, Soochow University
Provably Secure Agent Guardrail
May 28, 2026Benlong Wu, Weiming Zhang, Kejiang Chen +2LLM Guardrails AI Agent Security
University of Science and Technology of China
Robust and Efficient Guardrails with Latent Reasoning
May 27, 2026Siddharth Sai, Xiaofei Wen, Muhao ChenLLM Guardrails Content Moderation
University of California, Davis
The Ethics of LLM Sandbox and Persona Dynamics
May 27, 2026Tim Gebbie, Stewart GebbieLLM Guardrails LLM Safety Alignment
Dept. Statistical Sciences, University of Cape Town, South Africa
When Context Flips, Safety Breaks: Diagnosing Brittle Safety in Aligned Language Models
May 27, 2026Dasol Choi, Alex KwonLLM Safety Benchmarks Counterfactual Evaluation
AIM Intelligence · Independent Researcher
FinHarness: An Inline Lifecycle Safety Harness for Finance LLM Agents
May 26, 2026Haoxuan Jia, Yang Liu, Bin Chong +10AI Agent Reliability LLM Guardrails
Nanyang Technological University · Tsinghua University · Peking University +8
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
AI Content Moderation in Therapy Conversations
May 25, 2026Jiwon Kim, Claire Wang, Taeung Yoon +2LLM Auditing LLM Guardrails
University of Illinois Urbana-Champaign, U.S.
Reflect-Guard: Enhancing LLM Safeguards against Adversarial Prompts via Logical Self-Reflection
May 24, 2026Lixing Lin, Juli You, Yue Li +4Language Model Safety Evaluation LLM Guardrails
yaleYale University, New Haven, CT, USA · indIndependent Researcher · columbiaColumbia University, New York, NY, USA +2
CR4T: Rewrite-Based Guardrails for Adolescent LLM Safety
May 20, 2026Heajun An, Qi Zhang, Vedanth Achanta +1LLM Guardrails LLM Safety Alignment
Virginia Tech
Benchmarking and Improving Monitors for Out-Of-Distribution Alignment Failure in LLMs
May 20, 2026Dylan Feng, Pragya Srivastava, Anca Dragan +1Language Model Safety Evaluation LLM Guardrails
University of California, Berkeley, USA · 3Google DeepMind, India.
Governance by Construction for Generalist Agents
May 20, 2026Segev Shlomov, Iftach Shoham, Alon Oved +7LLM Guardrails AI Agent Governance
IBM Haifa, Israel
Robotics-Inspired Guardrails for Foundation Models in Socially Sensitive Domains
May 19, 2026Rebecca Ramnauth, Drazen Brscic, Brian ScassellatiLLM Guardrails Human-AI Interaction
Yale University, USA · Kyoto University, Japan
Exploring and Developing a Pre-Model Safeguard with Draft Models
May 19, 2026Hongyu Cai, Arjun Arunasalam, Yiming Liang +2LLM Guardrails Safety Filtering
Purdue University West Lafayette, Indiana, USA · Florida International University Miami, Florida, USA
Position: A Three-Layer Probabilistic Assume-Guarantee Architecture Is Structurally Required for Safe LLM Agent Deployment
May 18, 2026S. Bensalem, Y. Dong, M. Franzle +6AI Agent Reliability LLM Guardrails
1CSX-AI, France · University of Liverpool, UK · 3Carl von Ossietzky Universität Oldenburg, Germany +2
LPG: Balancing Efficiency and Policy Reasoning in Latent Policy Guardrails
May 17, 2026Nanxi Li, Zhengyue Zhao, Chaowei XiaoLanguage Model Safety Evaluation LLM Guardrails
Johns Hopkins University
LiSA: Lifelong Safety Adaptation via Conservative Policy Induction
May 14, 2026Minbeom Kim, Lesly Miculicich, Bhavana Dalvi Mishra +6Continual Learning for LLM Agents LLM Guardrails
Google Cloud AI Research · Google · Seoul National University
AERIC: Anticipatory Hidden-State Monitoring for Implicit Harmful Dialogue
May 13, 2026Jihyung Park, Saleh Afroogh, Junfeng JiaoLanguage Model Safety Evaluation LLM Guardrails
The University of Texas at Austin
LLM-Based Persuasion Enables Guardrail Override in Frontier LLMs
May 13, 2026Rodrigo Nogueira, Thales Sales Almeida, Giovana Kerche Bonás +7Adversarial Prompt Generation LLM Guardrails
Maritaca AI · JusBrasil
No Attack Required: Semantic Fuzzing for Specification Violations in Agent Skills
May 13, 2026Ying Li, Hongbo Wen, Yanju Chen +3LLM Guardrails LLM Agent Verification
University of California, Los Angeles · University of California, Santa Barbara · University of California, San Diego
Beyond Red-Teaming: Formal Guarantees of LLM Guardrail Classifiers
May 11, 2026Nikita Kezins, Urbas Ekka, Pascal Berrang +1Neural Network Verification Language Model Safety Evaluation
Delft University of Technology · University of Birmingham & Zeroth Research
GLiGuard: Schema-Conditioned Classification for LLM Safeguard
May 8, 2026Urchade Zaratiana, Mary Newhauser, George Hurn-Maloney +1LLM Guardrails Text Classification
Fastino Labs
LLM Wardens: Mitigating Adversarial Persuasion with Third-Party Conversational Oversight
May 8, 2026Lennart Wachowiak, Scott D. Blain, David Williams-King +1LLM Guardrails LLM Safety
ERA · University of Oxford
SafeHarbor: Hierarchical Memory-Augmented Guardrail for LLM Agent Safety
May 7, 2026Zhe Liu, Zonghao Ying, Wenxin Zhang +5LLM Guardrails LLM Agent Security
School of Cyber Science and Technology, Beihang University, Beijing, China · Institute of Artificial Intelligence, Beihang University, Beijing, China · University of Chinese Academy of Sciences, Beijing, China +1
One Turn Too Late: Learning When to Intervene Against Multi-Turn Malicious Intent
May 7, 2026Xinjie Shen, Rongzhe Wei, Peizhi Niu +6Language Model Safety Evaluation LLM Guardrails
Georgia Institute of Technology · University of Illinois Urbana-Champaign · UCSD +3
Who Decides What Is Harmful? Content Moderation Policy Through A Multi-Agent Personalised Inference Framework
May 2, 2026Ewelina Gajewska, Michal Wawer, Katarzyna Budzynska +1LLM Guardrails Content Moderation
Warsaw University of Technology, Warsaw, Poland
BabelSafe: A Policy-Grounded Multilingual Safety Benchmark for LLMs
May 1, 2026Yunhan Zhao, Zhaorun Chen, Xingjun Ma +1LLM Safety Benchmarks Multilingual Language Models
University of Illinois Urbana-Champaign · Fudan University · University of Chicago

May 29, 2026, cs.CLJ/K move · Enter open · S save

EMBGuard: Constructing Hazard-Aware Guardrails for Safe Planning in Embodied Agents

Dongwook Choi, Taeyoon Kwon, Bogyung Jeong, Minju Kim+5

Department of Artificial Intelligence, Yonsei University · Department of Biomedical Engineering and the Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University · Independent Researcher

LLM Guardrails AI Agent Safety Robot Safety AI Agent Safety Benchmarks Embodied AI

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MLLM-powered embodied agents deployed in real-world environments encounter physical hazards. However, existing approaches lack explicit mechanisms for identifying hazards and reasoning about action-conditioned risks, leading agents to either miss risky interactions or over-identify risks. To address this, we propose EMBGuard, the first MLLM-based safety guardrail for embodied agents designed to decouple physical risk reasoning from agent policy. By evaluating a (visual observation, action) pair, EMBGuard identifies hazardous configurations and provides natural language explanations of potential risks. Alongside EMBGuard, we contribute EMBHazard, a training dataset of 15.1K action-conditioned pairs, and EMBGuardTest, a benchmark of 329 manually curated real-world scenarios spanning seven physical risk categories. Through compositional variation of hazards and actions, we generate diverse risky and benign scenarios that agents may encounter during planning. Despite its compact size (2B, 4B), EMBGuard achieves performance competitive with proprietary MLLMs (e.g., GPT-5.1, Gemini-2.5-Pro) while significantly reducing the false-positive rates that hinder real-time deployment. We make the code, data, and models publicly available at https://github.com/dongwxxkchoi/EMBGuard

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