MEUV: Achieving Fine-Grained Capability Activation in Large Language Models via Mutually Exclusive Unlock Vectors

Documenti analoghi

• CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning
  di: Yi, Biao, et al.
  Pubblicazione: (2025)
• Eguard: Defending LLM Embeddings Against Inversion Attacks via Text Mutual Information Optimization
  di: Liu, Tiantian, et al.
  Pubblicazione: (2024)
• Fingerprint Vector: Enabling Scalable and Efficient Model Fingerprint Transfer via Vector Addition
  di: Xu, Zhenhua, et al.
  Pubblicazione: (2024)
• Privacy-Preserving Parameter-Efficient Fine-Tuning for Large Language Model Services
  di: Li, Yansong, et al.
  Pubblicazione: (2023)
• EnchTable: Unified Safety Alignment Transfer in Fine-tuned Large Language Models
  di: Wu, Jialin, et al.
  Pubblicazione: (2025)