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Fine-tuning LALMs on just the right layers, guided by layer-wise analysis, unlocks better paralinguistic understanding than naively fine-tuning everything.
Forget bigger models: clever prompt engineering with explicit decision rules crushes fine-tuning and embeddings for word sense disambiguation.
LLMs struggle with code migration when APIs evolve, but KCoEvo's knowledge graph augmentation boosts migration accuracy and execution success.
AI agents can now learn durable skills instead of constantly "reinventing the wheel," thanks to SkillNet's infrastructure for creating, evaluating, and connecting AI skills at scale.
