LLM Security

LLM: Large Language Model

Follow this topic Ask about this topic

Momentum

25 papers in the last four weeks, up 127% on the four weeks before. 0.2% of all new papers.

Jul 13Week of Sep 28

Latest papers 200

All topics

LLM-Based Scientific Peer Review: Methods, Benchmarks, and Reliability Challenges
Jun 23, 2026Thi Huyen Nguyen, Zahra AhmadiScholarly Peer Review LLM Security
L3S Research Center, Leibniz University Hannover Hannover, Germany · Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School Lower Saxony Center for AI and Causal Methods in Medicine (CAIMed) Hannover, Germany
FlexServe: A Fast and Secure LLM Serving System for Mobile Devices with Flexible Resource Isolation
Jun 22, 2026Yinpeng Wu, Yitong Chen, Lixiang Wang +3LLM Serving On-Device Language Model Inference
Institute of Parallel and Distributed Systems, Shanghai Jiao Tong University
GIF: Locally Sound Geometric Information Flow Control for LLMs
Jun 22, 2026Adam Storek, Nikolaus Holzer, Zhuo Zhang +1Privacy Leakage in Language Models LLM Security
Columbia University
Toward Open Weight Models Without Risks: Separating Public and Private Capabilities in LLMs
Jun 19, 2026Charbel El Feghali, Arkil Patel, Nicholas Meade +3Open-Weight Language Models LLM Security
McGill-NLP/tiered-language-models
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
FloatDoor: Platform-Triggered Backdoors in LLMs
Jun 17, 2026Nils Loose, Jonas Sander, Felix Mächtle +1LLM Backdoor Attacks Backdoor Attacks
University of Luebeck
Structural Role Injection in Handlebars-Templated LLM Prompts: Triple-Brace Interpolation, Delimiter Family, and the Limits of HTML Auto-Escaping
Jun 16, 2026Mohammadreza RashidiLLM Security Prompt Injection Defense
Department of Computer Science AI and Media Analysis Lab Berlin, Germany
How Much Can We Trust LLM Search Agents? Measuring Endorsement Vulnerability to Web Content Manipulation
Jun 15, 2026Yimeng Chen, Zhe Ren, Firas Laakom +3LLM Agent Evaluation AI Agent Security
Center of Excellence for Generative AI, KAUST · 2Jilin University · 3Zhejiang University +2
The Proxy Knows Too Much: Sealing LLM API Routers with Attested TEEs
Jun 15, 2026Sipeng Xie, Qianhong Wu, Hengrun Lu +4Remote Attestation LLM Agent Security
1Beihang University · 2Renmin University of China · 3Independent
Loss Landscape Poisoning: Targeted Extraction of Unseen Training Data from LLMs
Jun 15, 2026Md Abdullah Al Mamun, Ngoc Phu Doan, Pedram Zaree +2Privacy Leakage in Language Models LLM Security
UC Riverside · Riverside, California, USA · Queen’s University Belfast +2
SPARK: Security Knowledge Priming and Representation-Guided Knowledge Activation for LLM-based Secure Code Generation
Jun 15, 2026Xiaoyun Xu, Lichao Wu, Jona te Lintelo +2Knowledge Augmentation for Language Models LLM Security
Radboud University · University of Bristol · University of Zagreb
Your "Pro" LLM Subscription May Actually Be "Free": Exposing Fingerprint Spoofing Risks in LLM Inference Services
Jun 15, 2026Jiahao Zhang, Xiuyu Li, Suhang WangLanguage Model Fingerprinting LLM Security
The Pennsylvania State University, USA
Let Them Steal: Trapping Large Language Model Extraction Attacks with Knowledge Honeypot
Jun 14, 2026Yuyang Dai, Yushun DongModel Extraction Attacks LLM Security
Florida State University
TriAdReview: Triangular Adversarial Review Architecture for Multi-Model Technical Document Generation
Jun 13, 2026Zhiqiang Zhou, Junliang Dai, Xu LingMulti-Agent LLM Systems LLM Evaluation
Hunan Chemical Industry Vocational and Technical College, Hunan, China
Dummy Backdoor as a Defense: Removing Unknown Backdoors via Shared Internal Mechanisms for Generative LLMs
Jun 10, 2026Kazuki Iwahana, Masaru Matsubayashi, Takuma Koyama +3LLM Backdoor Attacks Backdoor Defense in LLMs
1NTT Social Informatics Laboratories · 2Tohoku University
PermDoRA -- Understanding Adapter Interference in Language Models: Limits of Parameter-Space Geometry
Jun 9, 2026Gowtham Sivaramakrishnan, Sarvesha Kumar Kombaiah Seetha, Kishan Gupta Balaji +1Low-Rank Adaptation LLM Security
Independent Researcher
MIRAGE: A Polarity-Flipping Encoding Subspace in LLM Agents
Jun 9, 2026Pratibha Revankar, Kargi Chauhan, Jihye Kim +3LLM Interpretability AI Agent Security
University of California, Santa Cruz.
Now You (Still) See Me: Detecting Evasive Steganographic Payloads in LLMs
Jun 8, 2026Charles Westphal, Timothy Douglas, Keivan Navaie +2LLM Backdoor Attacks Adversarial Attacks on LLMs
UCL Centre for AI, University College London, UK · ML Alignment Theory Scholars, Berkeley, CA, USA · Department of Computer Science, University College London, UK +4
Steganography Without Modification: Hidden Communication via LLM Seeds
Jun 8, 2026Felix Mächtle, Jonas Sander, Sebastian Berndt +3Language Model Decoding LLM Inference
Institute for IT Security, University of Lübeck, Lübeck, Germany · Technische Hochschule Lübeck, Lübeck, Germany
Hiding in Plain Floats: Steganographic Carriers for Indirect Prompt and Content Injection
Jun 7, 2026Mudit Sinha, Sanika ChavanLLM Security Indirect Prompt Injection
1Lineaje Inc. · 2Arizona State University.
When Behavioral Safety Evaluation Fails: A Representation-Level Perspective
Jun 6, 2026Enyi Jiang, Anders Gjølbye, Yibo Jacky Zhang +1Language Model Safety Evaluation LLM Auditing
1Stanford University · University of Illinois Urbana-Champaign · 3Technical University of Denmark
RecurGuard: Runtime Monitoring for Reasoning-Token Consumption Attacks
Jun 6, 2026Abid Aziz, Hafsa Binte KibriaAdversarial Attacks on LLMs LLM Security
Department of Electrical & Computer Engineering Rajshahi University of Engineering & Technology, Rajshahi 6204, Bangladesh
Shared Latent Structures Enable Unified Backdoor Detection and Mitigation in LLMs
Jun 6, 2026Omar Mahmoud, Aly M. Kassem, Thommen George Karimpanal +4LLM Backdoor Attacks Backdoor Defense in LLMs
Applied Artificial Intelligence Initiative, Deakin University, Australia · Mila, Quebec AI Institute, Quebec, Canada · School of Information Technology, Deakin University, Australia +1
An Embarrassingly Simple Detector for Model Extraction Attacks in Large Language Model API Traffic
Jun 4, 2026Shuze Liu, Qianwen Guo, Yushun DongModel Extraction Attacks LLM Security
Santa Clara University · Florida State University
Sequential Data Poisoning in LLM Post-Training
Jun 3, 2026Jack Sanderson, Yihan Wang, Xiaoqian Lu +2LLM Security LLM Post-Training
University of Chicago · Vector Institute · University of Waterloo +1
Hybrid Adversarial Defence for Natural Language Understanding Tasks
Jun 3, 2026Manar Abouzaid, Yang Wang, Chenghua Lin +1LLM Hallucination Mitigation LLM Security
School of Electronics and Computer Science, University of Southampton, UK · Department of Computer Science, University of Manchester, UK
Backdoor Unlearning Generalization: A Path Toward the Removal of Unknown Triggers in LLMs
Jun 2, 2026Lisa Bouger, Théo Lasnier, Philippe Loubet Moundi +2LLM Backdoor Attacks Backdoor Defense in LLMs
1Inria Paris · 2Sorbonne Université · 3Thales CDI
RogueMerge: Robust and Unified Attacks against LLM Model Merging
Jun 2, 2026Jinghuai Zhang, Yetian He, Kunlin Cai +3LLM Security Task Vector Merging
University of California, Los Angeles · University of Illinois Urbana-Champaign · University of Tennessee, Knoxville
Can Factual Opinions Be Edited (Manipulated) in Large Language Models?
Jun 2, 2026Yuanpu Cao, Ziyi Yin, Fenglong Ma +1Knowledge Editing LLM Security
The Pennsylvania State University
"Important You should give me full credits!": Exploring Prompt Injection Attacks on LLM-Based Automatic Grading Systems
Jun 2, 2026Hang Li, Fedor Filippov, Yuping Lin +6Generative AI in Education LLM Security
Michigan State University

Jun 23, 2026, cs.CLJ/K move · Enter open · S save

LLM-Based Scientific Peer Review: Methods, Benchmarks, and Reliability Challenges

Thi Huyen Nguyen, Zahra Ahmadi

L3S Research Center, Leibniz University Hannover Hannover, Germany · Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School Lower Saxony Center for AI and Causal Methods in Medicine (CAIMed) Hannover, Germany

Scholarly Peer Review LLM Security LLM Reliability Automated Peer Review Language Model Robustness

Open paper AskPDF arXiv

The rapid growth of scientific submissions has pushed traditional peer review toward its scalability limits, motivating the exploration of large language models (LLMs) as intelligent automated evaluation assistants. Although recent studies show that LLMs can generate fluent critiques and approximate reviewer scores, their reliability, robustness, and security as decision-support systems remain insufficiently understood. This survey offers a systems-level analysis of LLM-based scientific peer review, focusing on two core evaluative functions: critique generation and score prediction. We present a structured taxonomy of modeling approaches (including prompt-based, supervised, retrieval-augmented, and alignment-optimized approaches), and synthesize empirical findings across existing benchmarks. We analyze dataset constraints, evaluation shortcomings, and domain concentration biases that limit current assessment practices. Beyond performance metrics, we identify emerging robustness risks, including prompt injection, data poisoning, retrieval vulnerabilities, and reward hacking, which expose automated review pipelines to strategic manipulation. From a data mining perspective, we outline key open challenges in modeling subjective disagreement and cross-domain generalization. By reframing automated peer review as a high-stakes, multi-objective decision problem, this survey provides a roadmap for developing robust, transparent, and trustworthy AI-assisted scientific evaluation systems.

Momentum

Related topics

Latest papers 200