LLMs 是有效的谈判者吗？LLMs 在谈判对话中多方面能力的系统评估
Are LLMs Effective Negotiators? Systematic Evaluation of the Multifaceted Capabilities of LLMs in Negotiation Dialogues
AI总结：
系统评估大型语言模型在谈判中的多方面能力，发现 GPT-4 表现优异，但在主观评估和生成策略性响应方面存在挑战。
摘要：
成功的谈判需要一系列能力，包括理解对话上下文、推断对方动机的心理理论（ToM）技能、策略推理和有效沟通，这对自动化系统来说具有挑战性。尽管 LLMs 在各种 NLP 任务中表现出色，但尚未对其在谈判中的能力进行系统评估。这样的评估对于推进 AI 谈判代理和谈判研究至关重要，范围从设计对话系统到提供教学反馈和扩大数据收集实践。本工作旨在系统分析 LLMs 在典型谈判互动各个阶段的多样化对话场景中的多方面能力。我们的分析强调了 GPT-4 在许多任务中的优越性能，同时指出了具体挑战，例如进行主观评估和生成上下文适当、策略上有利的响应。
英文摘要：
A successful negotiation requires a range of capabilities, including comprehension of the conversation context, Theory-of-Mind (ToM) skills to infer the partner's motives, strategic reasoning, and effective communication, making it challenging for automated systems. Despite the remarkable performance of LLMs in various NLP tasks, there is no systematic evaluation of their capabilities in negotiation. Such an evaluation is critical for advancing AI negotiation agents and negotiation research, ranging from designing dialogue systems to providing pedagogical feedback and scaling up data collection practices. This work aims to systematically analyze the multifaceted capabilities of LLMs across diverse dialogue scenarios throughout the stages of a typical negotiation interaction. Our analysis highlights GPT-4's superior performance in many tasks while identifying specific challenges, such as making subjective assessments and generating contextually appropriate, strategically advantageous responses.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
