Witeness Overlap: Directional Provenance Inside Open-Weight Model Families

arXiv:2609.31784 · cs.AI · Submitted 2026-09-24 · Read on arXiv

cs.AI

Submitted: 2026-09-24

Updated: 2026-09-24

Terminology

• Accuracy — 40× in this paper · explained in 1 episode
• Pruning — 23× in this paper · explained in 4 episodes
• Provenance — 19× in this paper · explained in 3 episodes
• Fine-Tuning — 12× in this paper · explained in 5 episodes
• Alignment — 9× in this paper · explained in 1 episode
• GRPO — 8× in this paper · explained in 6 episodes
• Quantization — 7× in this paper · explained in 12 episodes
• Robustness — 7× in this paper · explained in 5 episodes
• Text-to-SQL — 7× in this paper · explained in 3 episodes
• Sparsity — 6× in this paper · explained in 4 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Fingerprinting — 3× in this paper · explained in 2 episodes
• Aggregation — 2× in this paper · explained in 1 episode
• Cosine Similarity — 2× in this paper · explained in 3 episodes
• Diffusion Model — 2× in this paper · explained in 8 episodes
• Diffusion Models — 2× in this paper · explained in 6 episodes
• RAG — 2× in this paper · explained in 3 episodes
• alpha — 2× in this paper · explained in 1 episode
• Accountability — 1× in this paper · explained in 2 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Core — 1× in this paper · explained in 2 episodes
• Distribution Shift — 1× in this paper · explained in 5 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Model Merging — 1× in this paper · explained in 2 episodes
• Pairwise Comparisons — 1× in this paper · explained in 2 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Visual Grounding — 1× in this paper · explained in 2 episodes

Sources

• Fingerprinting LLMs via Prompt Injection
• FNF: Functional Network Fingerprint for Large Language Models
• AttnDiff: Attention-based Differential Fingerprinting for Large Language Models

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