collaborators

5 papers

cs.AI2026

EcoAgent-Bench: Evaluating Economic Decision-Making in Budget-Constrained LLM Agents

Jie Wu, Ming Gong, Feixiang Cheng +1

Agent benchmarks usually measure task completion and treat resource use as an auxiliary statistic. In deployment, however, the choice among a local lookup, broad search, composite…

cs.MA2026

Beyond Single-Agent Alignment: Preventing Context-Fragmented Violations in Multi-Agent Systems

Jie Wu, Ming Gong

We identify and formalize a novel security risk: Context-Fragmented Violations (CFVs) - a class of policy breaches where individual agent actions appear locally safe and reasonable…

cs.AI2026

Policy-Invisible Violations in LLM-Based Agents

Jie Wu, Ming Gong

LLM-based agents can execute actions that are syntactically valid, user-sanctioned, and semantically appropriate, yet still violate organizational policy because the facts needed f…

cs.CL2025

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…

cs.CL2025

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…