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Baselines for Identifying Watermarked Large Language Models
We consider the emerging problem of identifying the presence and use of watermarking schemes in widely used, publicly hosted, closed source large language models (LLMs).
Learning the Wrong Lessons: Inserting Trojans During Knowledge Distillation
In recent years, knowledge distillation has become a cornerstone of efficiently deployed machine learning, with labs and industries using knowledge distillation to train models that are inexpensive and resource-optimized.
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