A survey of LLM copyright protection that unifies text watermarking, model watermarking, and model fingerprinting while presenting new coverage of fingerprint transfer and removal.
arXiv preprint arXiv:2402.11746
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The paper introduces a new taxonomy for model merging methods and reviews their applications in LLMs, MLLMs, continual learning, multi-task learning, and other subfields while outlining open challenges.
LlamaFactory provides a unified no-code framework for efficient fine-tuning of 100+ LLMs via an integrated web UI and has been released on GitHub.
citing papers explorer
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Copyright Protection for Large Language Models: A Survey of Methods, Challenges, and Trends
A survey of LLM copyright protection that unifies text watermarking, model watermarking, and model fingerprinting while presenting new coverage of fingerprint transfer and removal.
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Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities
The paper introduces a new taxonomy for model merging methods and reviews their applications in LLMs, MLLMs, continual learning, multi-task learning, and other subfields while outlining open challenges.
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LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models
LlamaFactory provides a unified no-code framework for efficient fine-tuning of 100+ LLMs via an integrated web UI and has been released on GitHub.