Language Model Fingerprinting

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5 papers in the last four weeks, up 25% on the four weeks before. 0.0% of all new papers.

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Style, Not Self: Surface Cues Explain Zero-Shot Code Attribution by Large Language Models
Sep 24, 2026Ehsan Barkhordar, Surendrabikram ThapaLLM Evaluation Language Model Generation Evaluation
Koç University · Virginia Tech
Who Is Behind the Harness? Fingerprinting LLMs through Agentic Behavior
Sep 23, 2026Chuyi Wang, Xiaohui Xie, Tongze Wang +2Coding Agents Language Model Fingerprinting
Department of Computer Science and Technology, Tsinghua University
Inference-Engine Fingerprinting Attacks are Practical: Exploring Model-Driven Environmental Discovery, Exploitation, and Escape
Sep 17, 2026Sarah Radway, Andrew Cheng, Vijay Janapa Reddi +1Language Model Fingerprinting Software Security
Harvard University
Fingerprinting Multimodal Large Language Models
Sep 17, 2026Chao Huang, Meng Tong, Kejiang ChenLLM Auditing Language Model Fingerprinting
University of Science and Technology of China Anhui Province Key Laboratory of Digital Security Hefei, Anhui, China
SlopShape: Identifying AI-Generated Commercial Web Content
Sep 14, 2026Jochen MadlerAI-Generated Text Detection Language Model Fingerprinting
Sitefire
Auditing Anonymous AI Models: A Four-Stage Protocol for Black-Box Identity Verification
Aug 31, 2026Yisen XiLanguage Model Fingerprinting Black-Box Model Auditing
Independent Researcher, Beijing, China
Token Counts Are Not Model Lineage: A Frozen-Threshold Holdout Study of Black-Box LLM API Fingerprinting
Aug 30, 2026Bo ChenLLM Evaluation Language Model Fingerprinting
Institute of Computing Technology, Chinese Academy of Sciences
AI Writers Have a Consistent Stylometric Footprint, but AI Editors Do Not
Aug 28, 2026Zhengyang Shan, Yukyung Lee, Sophie HaoAI-Generated Text Detection Language Model Fingerprinting
Boston University
Training Leaves Traces: Centered Residual Signatures for Language Model Lineage Verification
Aug 14, 2026Aman Singh Thakur, Rayan KhouryLanguage Model Fingerprinting Open-Weight Language Models
Massachusetts Institute of Technology, USA
Targeted Counterfactual Fingerprinting for Black-Box LLM Ownership Verification
Aug 8, 2026Yutong Wu, Xiaofan Bai, Shixin Li +10Language Model Fingerprinting
Huazhong University of Science and Technology · Alibaba Group · Microsoft Corporation
TokenPrint: A Calibrated Token-Space Fingerprint for Language-Model Provenance
Aug 8, 2026Yuqi Wu, Shengming Zhao, Jie ChenLLM Auditing Language Model Fingerprinting
College of Biomedical Engineering, Fudan University
Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space
Aug 7, 2026Yiwei Chen, Bingqi Shang, Sijia LiuLanguage Model Fingerprinting Open-Weight Language Models
Michigan State University
Beyond "AI Language": The case for the idiolectal nature of LLM output
Aug 6, 2026Karolina Rudnicka, Thomas Stephan JuzekLanguage Model Fingerprinting
Faculty of Languages, University of Gdańsk, Poland · Department of Scientific Computing, Florida State University, United States
Auditing Data Provenance in LLM Fine-tuning via Intrinsic Distributional Fingerprints
Aug 3, 2026Zirui Huang, Yunlong Mao, Wei Tong +3Language Model Fingerprinting Training Data Attribution
State Key Laboratory of Novel Software Technology, Nanjing University Nanjing, Jiangsu, China
ChaosProbe: A Neurochaotic Lens on Frozen Transformer Input-Embedding Spaces
Aug 3, 2026Kunal Kumar Pant, Nithin NagarajLanguage Model Fingerprinting Representation Probing
Department of Electronics and Communication Engineering (ECE) Amrita Vishwa Vidyapeetham Kollam, Kerala, India · Complex Systems Programme National Institute of Advanced Studies (NIAS) IISc Campus, Bengaluru Karnataka, India
Stemma: Induced Decision Regions Reveal LLM Provenance
Jul 28, 2026Keyu Zhang, Vadim Safronov, Andrew MartinLanguage Model Fingerprinting Language Model Probing
Department of Computer Science, University of Oxford
Construction-Driven Injection: Linguistically-Grounded Edit-Based Code-Mixing Fingerprints for Large Language Models
Jul 28, 2026Yongyi Cui, Yue Li, Tianbao Jiang +1Language Model Fingerprinting LLM Security
East China Normal University
Leaky Language Models: Stealing Architecture and Inference Optimizations via Per-Token Timing
Jul 22, 2026Sadegh Majidi, Niloofar Mireshghallah, Kazem TaramModel Extraction Attacks Language Model Fingerprinting
Purdue University West Lafayette, IN, USA · Carnegie Mellon University Pittsburgh, PA, USA
modelDNA: Calibrated Lineage Verification and Merge Decomposition from Sampled Weight Fingerprints
Jul 12, 2026Muhammad Awais Bin Adil, Saad AamirLanguage Model Fingerprinting Open-Weight Language Models
Independent
One Token Is Enough: Fingerprinting and Verifying Large Language Models from Single-Token Output Distributions
Jul 11, 2026Tomas BrucknerLLM Answer Verification LLM Auditing
Faculty of Informatics and Statistics, Prague University of Economics and Business, Prague, Czech Republic
Multi-Channel Spread-Spectrum Code Watermarking
Jul 7, 2026Soohyeon Choi, Debin Gao, Yue DuanText Watermarking Language Model Fingerprinting
Singapore Management University Singapore Singapore
Telescope: Improving Zero Shot Detection of LLM Generated Content By Measuring Token Repetition Probability
Jul 5, 2026Christopher Nassif, Josh F. CooperAI-Generated Text Detection Language Model Generation Evaluation
Virginia Tech Department of Electrical and Computer Engineering · Virginia Tech Department of Industrial and Systems Engineering
Spectral Signatures of Large Language Models
Jul 3, 2026Zhuoying Zhang, Ishan V. Prasad, Yuanzhe Hu +4LLM Evaluation Language Model Fingerprinting
Dartmouth College Hanover, NH, USA · University of California, Berkeley Berkeley, CA, USA · Lawrence Berkeley National Laboratory Berkeley, CA, USA
Em-ergence of the em-dash: a population-level rise in em-dash frequency in medRxiv preprints at the dawn of the large-language-model era
Jun 28, 2026Przemysław CzumaAI-Generated Text Detection AI-Assisted Scientific Research
Polish Association for Artificial Intelligence in Medicine
A Watermark for Vision-Language-Action and World Action Models
Jun 22, 2026Yule Liu, Shuai Liu, Jiaheng Wei +1Language Model Fingerprinting Vision-Language-Action Models
1Hong Kong University of Science and Technology (Guangzhou) · 3Xi’an Jiao Tong University · 2Wuhan University
Black-Box Forensics for Conversational LLM Agents
Jun 21, 2026Isadora White, Yasaman Jafari, Taylor Berg-KirkpatrickLanguage Model Fingerprinting LLM Agent Security
University of California, San Diego
Agent trajectories as programs: fingerprinting and programming coding-agent behavior
Jun 15, 2026Hamidah OderinwaleAI Coding Agents AI Agent Evaluation
Work done with support from Taste Labs
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
READER: Robust Evidence-based Authorship Decoding via Extracted Representations
Jun 9, 2026Jiaxu Liu, Sunnan Mu, Dong Huang +3Language Model Fingerprinting Authorship Attribution
1National University of Singapore · 4Shanghai Artificial Intelligence Laboratory · 2Xidian University +1
LLM Self-Recognition: Steering and Retrieving Activation Signatures
Jun 4, 2026Thibaud Ardoin, Jonas Schäfer, Gerhard WunderAI-Generated Text Detection LLM Interpretability
Department of Computer Science, Freie Universitaet Berlin, Germany.

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Style, Not Self: Surface Cues Explain Zero-Shot Code Attribution by Large Language Models

Ehsan Barkhordar, Surendrabikram Thapa

Koç University · Virginia Tech

LLM Evaluation Language Model Generation Evaluation Language Model Fingerprinting Language Model Self-Assessment Authorship Attribution Code Language Models

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If a language model can recognize code it wrote, it may favor that code as a judge, and instances of one model monitoring each other could collude. We test this zero-shot on current commercial models. Five LLMs generate solutions to MBPP, HumanEval, and DS-1000, seven more to MBPP, and models act as evaluators in four tasks: picking their own solution from a pair, judging whether a single solution is their own, identifying which of two solutions a named model wrote, and judging quality blind. In the single-solution task, balanced accuracy is 49-58% for all 15 model-benchmark combinations, while raw accuracy (38-67%) mostly reflects how readily a model claims authorship. In the pairwise task, accuracy across 14 evaluator-opponent combinations correlates at r=0.93 with how often the evaluator's solution is longer. Attribution to a named model succeeds on some pairs and is consistently inverted on others. A rule-based normalization that strips docstrings, comments, type hints, and local names preserves Pass@1 and leaves ten of twelve re-tested results at chance; the other two follow a length difference it leaves, although a trained classifier still separates most normalized pairs. Claude Haiku's self-preference also disappears. We recommend reporting balanced accuracy, heuristic baselines, and label consistency.

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