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Multiscript-aware evaluation reveals that traditional ASR metrics can misrepresent performance by treating valid orthographic variants as errors.
The secret to effectively pruning LLMs might not be *how* you search for redundant layers, but *what* you're optimizing for.
VLMs still struggle with subtle visual differences, exhibiting a significant gap compared to human-level comparative reasoning across diverse domains like medical and industrial imaging.
