LLM Auditing

LLM: Large Language Model

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59 papers in the last four weeks, up 79% on the four weeks before. 0.6% of all new papers.

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LLMSniffer: Detecting LLM-Generated Code via GraphCodeBERT and Supervised Contrastive Learning
Apr 17, 2026Mahir Labib Dihan, Abir MuhtasimLLM Auditing
Department of Computer Science and Engineering Bangladesh University of Engineering and Technology (BUET) Dhaka, Bangladesh
What Does a Sharing Question Add? Auditing LLM Survey Scores for Misinformation
Apr 8, 2026Zonghuan Xu, Xiang Zheng, Yutao Wu +1LLM Evaluation LLM Auditing
Shanghai Key Laboratory of Multimodal Embodied AI, Shanghai, China · City University of Hong Kong, Hong Kong SAR, China · Deakin University, Australia
Auditable Agents
Apr 7, 2026Yi Nian, Aojie Yuan, Haiyue Zhang +7AI Accountability AI Agent Auditing
University of Southern California · Arizona State University · University of Tennessee, Knoxville +1
Fine-Tuning Integrity for Modern Neural Networks: Structured Drift Proofs via Norm, Rank, and Sparsity Certificates
Apr 6, 2026Zhenhang Shang, Yingzhe Yu, Kani ChenNeural Network Verification LLM Auditing
The Hong Kong University of Science and Technology, Hong Kong, China
How Does "English (US)" Become the Default? Triangulating Structural Bias Towards American English Across the LLM Pipeline
Apr 5, 2026Mir Tafseer Nayeem, Davood RafieiLanguage Model Pretraining LLM Auditing
Department of Computing Science University of Alberta
The Anatomy of Uncertainty in LLMs
Mar 26, 2026Aditya Taparia, Ransalu Senanayake, Kowshik Thopalli +1LLM Auditing LLM Reliability
School of Computing and Augmented Intelligence, Arizona State University · Lawrence Livermore National Laboratory
MemGuard-Alpha: Limits of Membership Inference for Detecting and Filtering Memorization-Contaminated Signals in LLM-Based Financial Forecasting
Mar 26, 2026Anisha Roy, Dip RoyMembership Inference Attacks LLM Auditing
Department of Electronics and Communication Engineering, Jaypee Institute of Information Technology, Noida, India · Department of Computer Science and Engineering, Indian Institute of Technology Patna, India
PopResume: Causal Fairness Evaluation of LLM/VLM Resume Screeners with Population-Representative Dataset
Mar 24, 2026Sumin Yu, Juhyeon Park, Taesup MoonAI-Assisted Decision Making LLM Auditing
ECE, Seoul National University · IPAI, Seoul National University · ASRI / INMC / AIIS, Seoul National University
Detecting Data Poisoning in Code Generation LLMs via Black-Box, Vulnerability-Oriented Scanning
Mar 17, 2026Shenao Yan, Shan Jin, Shimaa Ahmed +4LLM Auditing Backdoor Detection
University of Connecticut · Visa Research
Real Money, Fake Models: Deceptive Model Claims in Shadow APIs
Mar 2, 2026Yage Zhang, Yukun Jiang, Zeyuan Chen +3LLM Auditing Black-Box Model Auditing
CISPA Helmholtz Center for Information Security
NEST: Nascent Encoded Steganographic Thoughts
Feb 15, 2026Artem KarpovLanguage Model Safety Evaluation LLM Auditing
Independent.
Auditing Multi-Agent LLM Reasoning Trees Outperforms Majority Vote and LLM-as-Judge
Feb 10, 2026Wei Yang, Shixuan Li, Heng Ping +3LLM Auditing Preference Optimization
University of Southern California
Bypassing the Rationale: Causal Auditing of Implicit Reasoning in Language Models
Feb 3, 2026Anish Sathyanarayanan, Aditya Nagarsekar, Aarush RathoreCoT Faithfulness Faithfulness of Language Model Explanations
BITS Pilani, K. K. Birla Goa Campus
Verifiable Manifest Signing and Transparency Enforcement for Secure MCP-Based LLM Pipelines
Jan 30, 2026Saeid Jamshidi, Kawser Wazed Nafi, Arghavan Moradi Dakhel +2LLM Auditing MCP Security
SWAT Laboratory, Polytechnique Montr´eal, Montr´eal, Canada · SæT Laboratory, Polytechnique Montr´eal, Montr´eal, Canada
Framing Instability in LLM Ethical Stance: Auditing Negation Sensitivity in Moral Dilemmas
Jan 29, 2026Katherine Elkins, Jon ChunMoral Reasoning in Language Models LLM Auditing
Kenyon College Gambier, OH
Unknown Unknowns: Do Hidden Intentions in LLMs Evade Detection?
Jan 26, 2026Devansh Srivastav, David Pape, Lea SchönherrLanguage Model Safety Evaluation LLM Auditing
CISPA Helmholtz Center for Information Security, Saarbrücken, Germany
White-Box Sensitivity Auditing with Steering Vectors
Jan 23, 2026Hannah Cyberey, Yangfeng Ji, David EvansAlgorithmic Auditing LLM Auditing
University of Virginia
A Scalable Entity-Based Framework for Auditing Bias in Large Language Models
Jan 18, 2026Akram Elbouanani, Aboubacar Tuo, Adrian PopescuLLM Auditing Political Bias in Language Models
Université Paris-Saclay, CEA, List, F-91120, Palaiseau, France
Audit Me If You Can: Query-Efficient Active Fairness Auditing of Black-Box LLMs
Jan 6, 2026David Hartmann, Lena Pohlmann, Lelia Hanslik +3LLM Auditing Algorithmic Fairness
Weizenbaum Institut Berlin · Technische Universität Berlin · FIZ Karlsruhe +2
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
MAS-Shield: A Defense Framework for Secure and Efficient LLM MAS
Nov 28, 2025Kaixiang Wang, Zhaojiacheng Zhou, Bunyod Suvonov +8Multi-Agent LLM Systems LLM Auditing
Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240, China
Auditing Information Disclosure During Large-Scale Gradient-Based Training via Gradient Uniqueness
Oct 13, 2025Sleem Abdelghafar, Maryam Aliakbarpour, Christopher JermaineData Leakage Privacy Auditing
Rice University Houston, USA
The Alignment Auditor: A Bayesian Framework for Verifying and Refining LLM Objectives
Oct 7, 2025Matthieu Bou, Nyal Patel, Arjun Jagota +2Reinforcement Learning LLM Auditing
1Imperial College London · 2Amazon AGI
Data Provenance Auditing of Fine-Tuned Large Language Models with a Text-Preserving Technique
Oct 7, 2025Yanming Li, Cédric Eichler, Nicolas Anciaux +3Data Provenance Dataset Watermarking
PETSCRAFT · Petscraft, Inria, Palaiseau, France · INSA CVL, Bourges, France +6
WirelessMathBench-XL: An Auditable Benchmark for Wireless Mathematical Reasoning
Sep 27, 2025Xin Li, Mengbing Liu, Yiyang Zhu +4Mathematical Reasoning Benchmarks Benchmark Auditing
Nanyang Technological University
What Is The Political Content in LLMs' Pre- and Post-Training Data?
Sep 26, 2025Tanise Ceron, Dmitry Nikolaev, Dominik Stammbach +1LLM Auditing Political Bias in Language Models
Bocconi University, Italy · University of Manchester, UK · Princeton University, USA
Addressing Benchmarking Gaps in Large Language Models for Health and Medicine with Dynamic Red-Teaming
Jul 30, 2025Jiazhen Pan, Bailiang Jian, Paul Hager +20LLM Safety Benchmarks Language Model Safety Evaluation
Cherise · School of Computation, Information and Technology, Technical University of Munich (TUM), Munich, Germany · Department of Engineering Science, University of Oxford, Oxford, United Kingdom +9
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
The PIMMUR Principles: Ensuring Validity in Collective Behavior of LLM Societies
Date pendingJiaxu Zhou, Jen-tse Huang, Xuhui Zhou +5LLM Evaluation LLM Auditing
CUHK · JHU · CMU +3
ReasoningFlow: Discourse Structures for Understanding LLM Reasoning Traces
Date pendingJinu Lee, Shivam Agarwal, Amruta Parulekar +3LLM Reasoning with Graphs LLM Auditing
The Grainger College of Engineering University of Illinois Urbana-Champaign

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LLMSniffer: Detecting LLM-Generated Code via GraphCodeBERT and Supervised Contrastive Learning

Mahir Labib Dihan, Abir Muhtasim

Department of Computer Science and Engineering Bangladesh University of Engineering and Technology (BUET) Dhaka, Bangladesh

LLM Auditing

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The rapid proliferation of Large Language Models (LLMs) in software development has made distinguishing AI-generated code from human-written code a critical challenge with implications for academic integrity, code quality assurance, and software security. We present LLMSniffer, a detection framework that fine-tunes GraphCodeBERT using a two-stage supervised contrastive learning pipeline augmented with comment removal preprocessing and an MLP classifier. Evaluated on two benchmark datasets - GPTSniffer and Whodunit - LLMSniffer achieves substantial improvements over prior baselines: accuracy increases from 70% to 78% on GPTSniffer (F1: 68% to 78%) and from 91% to 94.65% on Whodunit (F1: 91% to 94.64%). t-SNE visualizations confirm that contrastive fine-tuning yields well-separated, compact embeddings. We release our model checkpoints, datasets, codes and a live interactive demo to facilitate further research.

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Latest papers 453