MACS: A Hybrid Multi-Agent Framework for Reliable Conversational E-Commerce Recommendation
Conversational recommendation for e-commerce is increasingly mediated by large language models (LLMs), yet many real-world deployments operate under a stricter requirement: recommendations must be drawn only from a merchant's fixed catalog, without web search or unsupported product claims. In this setting, the main challenge is reliability under hard constraints: the system must satisfy user requirements, remain grounded in available inventory, and preserve preferences across multiple conversational turns. We present MACS (Multi-Agent Commerce System), a hybrid multi-agent framework for reliable conversational recommendation in fixed-catalog settings. MACS uses LLMs for language-facing ta...
| Authors | Juli Huang, Hannah Clay, Sajjad Beygi et al. |
|---|---|
| Primary category | cs.IR |
| Published | 14 August 2026 |
| Last updated at source | 14 August 2026 |
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