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English(EN) ToolRACER: A Robust Agentic Conversation Emulation Resource for Agent Training and Evaluation

新数据集 ToolRACER 通过对抗性对话增强代理的鲁棒性

研究人员推出了 ToolRACER,这是一个旨在创建更鲁棒的对话代理的合成数据生成管道。该管道模拟用户、助手和工具的交互,专注于现有基准通常忽略的现实和对抗性对话场景。由此产生的数据集 ToolRACERBench 包含 5.6K 个跨六个领域的已验证对话轨迹,其中大部分包含易出错的交互。在 ToolRACERBench 上训练的模型在既定的函数调用基准上显示出改进的代理准确性和鲁棒性。 AI

影响 通过提供现实的对抗性训练数据,增强了更可靠的对话式人工智能的开发。

排序理由 该集群描述了一篇介绍用于训练对话代理的数据集和方法的新学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新数据集 ToolRACER 通过对抗性对话增强代理的鲁棒性

本文如何被排名

Signal score
7 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
该集群描述了一篇介绍用于训练对话代理的数据集和方法的新学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
paper, product
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
Same-day
Cluster formed today. Ranking reflects the current source set at time of score.

完整方法见我们的编辑标准。

报道来源 [1]

  1. arXiv cs.CL TIER_1 English(EN) · Arkajyoti Chakraborty, Aryan Tayal, Ishika Agarwal, Tanner Sorensen, Justin Chiu, Alessandro Di Bari, Neha Gupta, Andreas Stolcke ·

    ToolRACER:用于 Agent 训练和评估的强大 Agentic 对话仿真资源

    arXiv:2610.09163v1 Announce Type: new Abstract: Task-oriented conversational agents remain fragile under real world conversation scenarios as they rarely follow a predictable script, especially when users exhibit non-cooperative behavior. Existing function-calling benchmarks ofte…