DICE-BENCH

该数据集名为DICE-BENCH，它通过构建一个工具图来合成对话，这个工具图能够在多轮对话中维持依赖关系，并结合一个具有不同角色的多代理系统，以增强对话的自然度。该数据集包含高DICE-SCORE实例，旨在评估大型语言模型在现实多轮对话中的表现。其规模为1,607个实例，任务是对大型语言模型在多轮、多方对话中使用工具的能力进行评估。The dataset is named DICE-BENCH. It synthesizes dialogues by constructing a tool graph that maintains dependencies across multi-turn conversations, and incorporates a multi-agent system with diverse roles to enhance the naturalness of the dialogues. This dataset includes high DICE-SCORE instances, which is designed to evaluate the performance of large language models (LLMs) in realistic multi-turn conversations. It comprises 1,607 instances in total, with the core task of assessing the tool-use capabilities of large language models in multi-turn, multi-party conversations.

搜集汇总

背景与挑战

背景概述

DICE-BENCH是一个包含1,607个实例的数据集，通过工具图合成多轮对话以维持依赖关系，并利用多代理系统提升自然度，旨在评估大型语言模型在现实多轮、多方对话中使用工具的表现。