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New watermarking framework traces LLM contributions across derivation chains

Researchers have developed LineageMark, a novel white-box watermarking framework designed to trace contributions within multi-stage derivation chains of large language models (LLMs). This system encodes watermarks directly into model parameters using a projection-based approach with stable carriers to minimize sensitivity to model alterations. LineageMark is capable of preserving contributor watermarks through multiple derivation stages and supports incremental insertion by multiple users, demonstrating robustness against common modifications like fine-tuning, quantization, and pruning. AI

IMPACT Enhances intellectual property protection and provenance tracking in open LLM ecosystems.

RANK_REASON The cluster contains a research paper detailing a new technical framework for LLM watermarking. [lever_c_demoted from research: ic=1 ai=1.0]

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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Bingxue Zhang, Xiaofeng Xu, Feida Zhu ·

    LineageMark: Multi-user White-box Watermarking for Contribution Tracing in Model Derivation Chains

    arXiv:2606.17123v1 Announce Type: cross Abstract: In open large language model (LLM) ecosystems, models are frequently adapted across multiple domains and applications, forming multi-stage derivation chains. Consequently, tracking and verifying historical contributions is essenti…