4 papers
ECom-Bench: Can LLM Agent Resolve Real-World E-commerce Customer Support Issues?
Haoxin Wang, Xianhan Peng, Xucheng Huang +5
In this paper, we introduce ECom-Bench, the first benchmark framework for evaluating LLM agent with multimodal capabilities in the e-commerce customer support domain. ECom-Bench fe…
MindFlow+: A Self-Evolving Agent for E-Commerce Customer Service
Ming Gong, Xucheng Huang, Ziheng Xu +1
High-quality dialogue is crucial for e-commerce customer service, yet traditional intent-based systems struggle with dynamic, multi-turn interactions. We present MindFlow+, a self-…
MindFlow: Revolutionizing E-commerce Customer Support with Multimodal LLM Agents
Ming Gong, Xucheng Huang, Chenghan Yang +4
Recent advances in large language models (LLMs) have enabled new applications in e-commerce customer service. However, their capabilities remain constrained in complex, multimodal…
Xmodel-LM Technical Report
Yichuan Wang, Yang Liu, Yu Yan +3
We introduce Xmodel-LM, a compact and efficient 1.1B language model pre-trained on around 2 trillion tokens. Trained on our self-built dataset (Xdata), which balances Chinese and E…