mlsanityData to 7 Oct 2026

MindFlow: Revolutionizing E-commerce Customer Support with Multimodal LLM Agents

arXiv 2507.05330 ↗First posted 7 Jul 2025cs.CL cs.AIcited by 6

On the map: Multimodal LLMs / vision-language models → Document understanding and multimodal RAG

also in 1 more
Abstract (arXiv)

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.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Placed in Document understanding and multimodal RAG, one of 16 directions in Multimodal LLMs / vision-language models. Builds on 9 of its 18 references that are in the map. First posted on arXiv 7 Jul 2025.

Builds on

9 of 18 references.

References · 9

  1. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
  2. 2023A Survey on Large Language Model based Autonomous Agentscited by 2,203
  3. 2024SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineeringcited by 1,628
  4. 2023The Rise and Potential of Large Language Model Based Agents: A Surveycited by 1,422
  5. 2023CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Societycited by 1,348
  6. 2024τ-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domainscited by 1,280
  7. 2024eCeLLM: Generalizing Large Language Models for E-commerce from Large-scale, High-quality Instruction Datacited by 44
  8. 2024A survey on fairness of large language models in e-commerce: progress, application, and challengecited by 10
  9. 2024LiLiuM: eBay's Large Language Models for e-commercecited by 9

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 1; 2026: 5.

6 papers.

  1. 2026ShopSimulator: Evaluating and Exploring RL-Driven LLM Agent for Shopping Assistantscited by 9
  2. 2026SEAD: Self-Evolving Agent for Multi-Turn Service Dialoguecited by 6
  3. 2025Survey of Specialized Large Language Modelcited by 3
  4. 2026ProductResearch: Training E-Commerce Deep Research Agents via Multi-Agent Synthetic Trajectory Distillationcited by 3
  5. 2026Reinforcing Real-world Service Agents: Balancing Utility and Cost in Task-oriented Dialoguecited by 1
  6. 2026MESA: Prioritizing Vulnerable Communication Channels for Securing Multi-Agent Systemscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025MindFlow+: A Self-Evolving Agent for E-Commerce Customer Service
  2. 2026EComStage: Stage-wise and Orientation-specific Benchmarking for Large Language Models in E-commerce
  3. 2025ECom-Bench: Can LLM Agent Resolve Real-World E-commerce Customer Support Issues?
  4. 2025MemOrb: A Plug-and-Play Verbal-Reinforcement Memory Layer for E-Commerce Customer Service
  5. 2026Insight Agents: An LLM-Based Multi-Agent System for Data Insights
  6. 2025Agent-in-the-Loop: A Data Flywheel for Continuous Improvement in LLM-based Customer Support
  7. 2025FaMA: LLM-Empowered Agentic Assistant for Consumer-to-Consumer Marketplace
  8. 2026MerchantBench: Benchmarking LLM Agents for Long-Term Coherence in E-Commerce Operations