(2)由 Agent-as-a-Judge 驱动的飞轮效应 Agent-as-a-Judge 和被评估智能体之间的相互改进,通过不断的迭代反馈逐步演进,这一循环展示了广阔的发展前景。通过将 Agent-as-a-Judge 作为核心机制,或许能够催生出一种智能体自我博弈系统。...
该框架在 LLM-as-a-Judge 的基础上进行了升级,增加了中间反馈功能,确保任务的每个环节都能得到精准评估与优化,同时还能有效模拟并接近人类反馈。 论文标题:Agent-as-a-Judge: Evaluate Agents with Agents 论文地址:arxiv.org/pdf/2410.1093 项目地址:github.com/metauto-ai/a 为了克服现有基准存在的问题,并为 ...
论文标题:Agent-as-a-Judge: Evaluate Agents with Agents 论文地址:https://arxiv.org/pdf/2410.10934 项目地址:https://github.com/metauto-ai/agent-as-a-judge为了克服现有基准存在的问题,并为 Agent-as-a-Judge 提供一个概念验证测试平台,研究者还提出了 DevAI,一个包含 55 项现实自动人工智能开发任务的...
Agent-as-a-Judge 和被评估智能体之间的相互改进,通过不断的迭代反馈逐步演进,这一循环展示了广阔的发展前景。通过将 Agent-as-a-Judge 作为核心机制,或许能够催生出一种智能体自我博弈系统。随着 Agent-as-a-Judge 与被评估智能体的持续交互,这种过程可能会产生飞轮效应 —— 每次改进相互强化,从而不断推动性能...
该框架在 LLM-as-a-Judge 的基础上进行了升级,增加了中间反馈功能,确保任务的每个环节都能得到精准评估与优化,同时还能有效模拟并接近人类反馈。 论文标题:Agent-as-a-Judge: Evaluate Agents with Agents 论文地址:https://arxiv.org/pdf/2410.10934
随着Agent-as-a-Judge框架的完善,也许不久的将来,AI评估AI会成为行业新标准。 @article{Zhuge2024AgentasaJudgeAEA, title={Agent-as-a-Judge: Evaluate Agents with Agents}, author={Mingchen Zhuge and Changsheng Zhao and Dylan R. Ashley and Wenyi Wang and Dmitrii Khizbullin and Yunyang Xiong and ...
Agent-as-a-Judge:用智能体系统评估智能体系统 原文链接:https://arxiv.org/abs/2410.10934 代码链接:https://github.com/metauto-ai/agent-as-a-judge 数据集链接:https://huggingface.co/DEVAI-benchmark 参考文献:Agent-as-a-Judge: Evaluate Agents with Agents by Zhuge et al. arXiv:2410.10934 ...
Agent-as-a-Judge: Evaluate Agents with Agents From Persona to Personalization: A Survey on Role-Playing Language Agents From Persona to Personalization: A Survey on Role-Playing Language Agents Exchange-of-Thought: Enhancing Large Language Model Capabilitiesthrough Cross-Model Communication ...
大模型判定(LLM-as-a-judge,常用,但存在偏差) 程序判定(成本最低,准确率高,但场景局限) 人工标注(价格昂贵,耗时较长,需要质检) 任务类型(Task) RAG、聊天机器人、代码生成、Agent、内容创作等 应用评估(Applying evals) 单元测试:在线/离线单元测试
To address this, we introduce the Agent-as-a-Judge framework, wherein agentic systems are used to evaluate agentic systems. This is an organic extension of the LLM-as-a-Judge framework, incorporating agentic features that enable intermediate feedback for the entire task-solving process. We ...