2 papers
cs.AI2026
How Do Agentic LLMs Decide to Call Tools? A Tool-Call Vector Shaped by Suppression
Xijie Gong, Tingxu Han, Jiahao Zhang +5
Tool calling, invoking external tools on demand, is central to agentic LLMs, yet the mechanism that decides whether a model calls a tool or responds directly remains poorly underst…
cs.RO2026
EmbodiedClaw: Conversational Workflow Execution for Embodied AI Development
Xueyang Zhou, Yihan Sun, Xijie Gong +4
Embodied AI research is increasingly moving beyond single-task, single-environment policy learning toward multi-task, multi-scene, and multi-model settings. This shift substantiall…