Forging LLM Authorship Fingerprints with Targeted Rewriting

arXiv:2609.38831 · cs.CL · Submitted 2026-09-30 · Read on arXiv

cs.CL

Submitted: 2026-09-30

Updated: 2026-09-30

Comments: 31 pages, 7 figures, 25 tables. Project page: https://haohanyuan01.github.io/ForgePrint/

Code: https://github.com/HaohanYuan01/ForgePrint

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• GRPO — 30× in this paper · explained in 6 episodes
• Accuracy — 14× in this paper · explained in 1 episode
• Ablation — 11× in this paper · explained in 1 episode
• LLM judge — 8× in this paper · explained in 2 episodes
• Provenance — 7× in this paper · explained in 5 episodes
• Benchmark — 5× in this paper · explained in 2 episodes
• Fingerprinting — 4× in this paper · explained in 2 episodes
• Core — 3× in this paper · explained in 2 episodes
• Decode — 3× in this paper · explained in 2 episodes
• Distillation — 3× in this paper · explained in 2 episodes
• Embeddings — 3× in this paper · explained in 2 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Ablation study — 2× in this paper · explained in 3 episodes
• Alignment — 2× in this paper
• Attack Success Rate (ASR) — 2× in this paper · explained in 3 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Domain Shift — 2× in this paper · explained in 6 episodes
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Adversarial Training — 1× in this paper · explained in 1 episode
• Direct Preference Optimization (DPO) — 1× in this paper · explained in 10 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• In-Context Learning — 1× in this paper · explained in 7 episodes
• LoRA Adapters — 1× in this paper · explained in 3 episodes
• Multi-Agent Framework — 1× in this paper · explained in 3 episodes
• Personalization — 1× in this paper · explained in 2 episodes
• Self-consistency — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Are You Getting What You Pay For? Auditing Model Substitution in LLM APIs
• Construction-Driven Injection: Linguistically-Grounded Edit-Based Code-Mixing Fingerprints for Large Language Models
• AuthorMist: Evading AI Text Detectors with Reinforcement Learning
• TRACE: A Two-Channel Robust Attribution Watermark via Complementary Embeddings for LLM-Agent Trajectories
• WikiHow: A Large Scale Text Summarization Dataset
• RoBERTa: A Robustly Optimized BERT Pretraining Approach
• The Assistant Erased You: Measuring Loss of Authorship Signals in AI-Mediated Communication
• ARB: A Matched Authorship-Rewriting Benchmark Dataset for AI-Text Detector Evaluation
• Direct Preference Optimization: Your Language Model is Secretly a Reward Model
• Can AI-Generated Text be Reliably Detected?
• DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
• Targeted Counterfactual Fingerprinting for Black-Box LLM Ownership Verification
• Assessing Deanonymization Risks with Stylometry-Assisted LLM Agent

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