MindFlow: Revolutionizing E-commerce Customer Support with Multimodal LLM Agents
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866911044507533312 |
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| author | Gong, Ming Huang, Xucheng Yang, Chenghan Peng, Xianhan Wang, Haoxin Liu, Yang Jiang, Ling |
| author_facet | Gong, Ming Huang, Xucheng Yang, Chenghan Peng, Xianhan Wang, Haoxin Liu, Yang Jiang, Ling |
| contents | 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. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2507_05330 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | MindFlow: Revolutionizing E-commerce Customer Support with Multimodal LLM Agents Gong, Ming Huang, Xucheng Yang, Chenghan Peng, Xianhan Wang, Haoxin Liu, Yang Jiang, Ling Computation and Language Artificial Intelligence 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. |
| title | MindFlow: Revolutionizing E-commerce Customer Support with Multimodal LLM Agents |
| topic | Computation and Language Artificial Intelligence |
| url | https://arxiv.org/abs/2507.05330 |