Can LLM Agents Resolve Service Failures? Simulating Multi-Turn Complaint Handling under Information Asymmetry
LLM agents are widely adopted in service chatbots for rule-guided support and information access, yet emotionally demanding complaint handling still relies heavily on human agents. We introduce ServiceBench, to our knowledge the first benchmark dedicated to complaint handling, with 2,500 scenarios spanning 184 complaint categories and five service industries. We propose Asymmetric Progressive Complaint Simulation (APCS) to simulate realistic complaint handling, together with a justice-based evaluation framework. Our experiments reveal that even capable LLM agents struggle to handle complaints effectively. They lack the ability to proactively gather information and strategically guide conv...
| Authors | Wailing Ng, Mengze Hong, Chen Jason Zhang et al. |
|---|---|
| Primary category | cs.AI |
| Published | 17 October 2026 |
| Last updated at source | 17 October 2026 |
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