MindFlow: Revolutionizing E-commerce Customer Support with Multimodal LLM Agents
This addresses complex multimodal customer support for e-commerce, but appears incremental as it builds on existing frameworks like CoALA.
The paper tackles the problem of limited multimodal capabilities in e-commerce customer service LLMs by introducing MindFlow, an open-source multimodal LLM agent, which achieved a 93.53% relative improvement in real-world deployments.
Recent advances in large language models (LLMs) have enabled new applications in e-commerce customer service. However, their capabilities remain constrained in complex, multimodal scenarios. We present MindFlow, the first open-source multimodal LLM agent tailored for e-commerce. Built on the CoALA framework, it integrates memory, decision-making, and action modules, and adopts a modular "MLLM-as-Tool" strategy for effect visual-textual reasoning. Evaluated via online A/B testing and simulation-based ablation, MindFlow demonstrates substantial gains in handling complex queries, improving user satisfaction, and reducing operational costs, with a 93.53% relative improvement observed in real-world deployments.