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Similarity alone is a poor guide for LLM depth pruning: jointly considering representational similarity *and* transformation difference unlocks significantly better compression.
Current LLM watermarks are more vulnerable than we thought: a new adaptive stealing attack can efficiently extract and exploit watermark information, rendering them unreliable.
