AIBullisharXiv – CS AI · 7h ago7/10
🧠
LayerRoute: Input-Conditioned Adaptive Layer Skipping via LoRA Fine-Tuning for Agentic Language Models
LayerRoute is a lightweight adapter that enables language models to dynamically skip transformer blocks based on input type, achieving 12.91% computational efficiency gains with minimal training overhead. By combining per-layer routers with LoRA fine-tuning, the system learns to skip 15.25% of computations for tool calls while maintaining full capacity for complex reasoning tasks, demonstrating significant potential for optimizing agentic AI systems.
🏢 Perplexity