Xiu‐Qing Li

Reasoning and Tool-use Compete in Agentic RL:From Quantifying Interference to Disentangled Tuning

This paper proposes Disentangled Action--Reasoning Tuning (DART), a simple and efficient framework that explicitly decouples parameter updates for reasoning and tool use via separate low-rank adaptation modules, further supporting the finding of capability interference under shared optimization.