Adaptive Latent Agentic Reasoning

This research introduces Adaptive Latent Agentic Reasoning (ALAR), a dual-mode framework designed to enhance the efficiency of LLM agents. ALAR uses compact latent reasoning for routine tasks and escalates to explicit chain-of-thought when deeper deliberation is required, leading to comparable or better task accuracy with substantial efficiency gains.