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arXiv:cs.AI· P N Bhargav Teja, Velpula Lokesh Reddy, Madhu Basumata, Susen Sarkar, Rajasekhara Reddy Duvvuru Muni·· 13 小时前

SmartSalesBench:面向 LLM 销售智能体的抗压多轮对话基准

SmartSalesBench: A Resistance-Aware Multi-Turn Benchmark for Evaluating LLM Sales Agents

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SmartSalesBench 是首个专门评估 LLM 销售智能体应对抗性买家角色的多轮对话基准,通过 RAG 生成智能体与买家角色,设置最多二十轮对话。

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Abstract:We present SmartSalesBench, the first multi-turn conversational benchmark explicitly designed to evaluate large language model (LLM) sales agents against psychologically grounded, resistant buyer personas. Existing task-oriented dialogue benchmarks assume cooperative users and measure task completion; SmartSalesBench inverts this assumption, placing agents against personas programmed to resist and challenge across conversations of up to twenty turns. The benchmark includes five agent profiles, twelve buyer personas, fifteen smartphone products across six price tiers, and four controlled experiments with 3 iterations totaling 13,680 sessions. Both sales-agent and buyer persona generations are grounded through retrieval-augmented generation (RAG). We introduce nine evaluation metrics grouped into three tiers: primary outcome metrics (CR, BRS, RIR), secondary quality metrics (SMS, PFS, ETI), and exploratory metrics planned for future reporting (ITS, ARI, SPI). Our evaluation combines automated LLM-as-judge scoring with internal human assessment (n = 50, \k{appa} = 0.71, Pearson r = 0.81 with BRS).
Comments: Request for review
Subjects: Artificial Intelligence (cs.AI); Computation and Language (cs.CL)
Cite as: arXiv:2610.12975 [cs.AI]
  (or arXiv:2610.12975v1 [cs.AI] for this version)
  https://doi.org/10.48550/arXiv.2610.12975

arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Susen Sarkar [view email]
[v1] Fri, 9 Oct 2026 04:21:12 UTC (2,962 KB)

来源:arXiv:cs.AI · arxiv.org