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Independently trained depth slices can be recombined to match the performance of monolithic models, revealing a new avenue for efficient language model training.
SkillSmith achieves unprecedented performance gains by seamlessly merging textual knowledge with parametric skills, outperforming traditional methods that treat these domains separately.
