Papers with DualGuard

2 papers
DualGuard: A Parameter Space Transformation Approach for Bidirectional Defense in Split-Based LLM Fine-Tuning (2025.acl-long)

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Challenge: Existing defense methods for large language model fine-tuning (LLM-FT) sacrifice task-specific performance under privacy constraints.
Approach: They propose a bidirectional defense mechanism that uses a local warm-up parameter transformation to alter client-side model parameters before training.
Outcome: The proposed defense mechanism outperforms current defense methods while maintaining task performance.
DualGuard: Dual-stream Large Language Model Watermarking Defense against Paraphrase and Spoofing Attack (2026.findings-acl)

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Challenge: Existing watermarking algorithms focus on defending against paraphrase and piggyback spoofing attacks, which can inject harmful content, compromise reliability, and undermine trust in attribution.
Approach: They propose an algorithm capable of defending against paraphrase and spoofing attacks.
Outcome: Experiments on large language models and language models show that DualGuard is the first watermarking algorithm capable of defending against both paraphrase and spoofing attacks.

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