When Do Causal World Models Help Modular LLM Agents
LLM agents increasingly act through modular systems, such as order, payment, inventory, and shipment services, where actions in one module change which transitions are valid in another. Standard world models usually fit observational traces, but this is not the quantity needed for intervention-time planning: a trace may show that payment precedes shipment without identifying whether payment authorizes shipment, inventory mediates the effect, or a hidden trigger explains both. We study this gap through FedCausalCompose, a causal world-model framework for modular LLM agents in which local actions provide intervention-response evidence for cross-module interfaces. We first show that observat...
| Authors | Xinyuan Song, Zekun Cai |
|---|---|
| Primary category | cs.AI |
| Published | 12 July 2026 |
| Last updated at source | 12 July 2026 |
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