# 评估交互式AI代理的认知年龄对齐

- 来源：HuggingFace Daily Papers（社区热门论文）
- 发布时间：2026-05-18 08:00
- AIHOT 分数：53
- AIHOT 链接：https://aihot.virxact.com/items/cmpcn5wm003qbslae05rd9bt8
- 原文链接：https://arxiv.org/abs/2605.17894

## AI 摘要

尽管具身化AI及多模态大语言模型在推理任务中表现出潜力，但与人类智能仍存显著差距。现有先进代理常无法完成儿童能轻松解决的基础任务。受韦氏儿童智力量表启发，本研究推出ChildAgentEval——首个基于心理测量学的交互式基准，用于评估多模态大语言模型代理的认知年龄对齐程度。该基准通过系统比较各类交互式代理的推理能力与人类特定年龄发展阶段，揭示了当前AI系统在模拟年龄特异性认知行为上的能力边界。

## 正文

While agentic AI and its core multimodal large language models (MLLMs) have demonstrated remarkable promise in language and visual reasoning across domains ranging from daily life to advanced scientific research, a profound gap remains between artificial and human intelligence. Despite the integration of powerful tools and advanced MLLMs, state-of-the-art AI agents frequently fail at foundational, seemingly simple tasks that a child can resolve with ease. Inspired by the Wechsler Intelligence Scale for Children (WISC), we introduce ChildAgentEval, the first psychometrically grounded interactive benchmark for evaluating cognitive age alignment in MLLM-based agents. ChildAgentEval systematically compares the reasoning performance of various MLLM-based interactive agents against age-specific human developmental stages, exposing where current agentic AI systems can and cannot simulate age-specific cognitive behavior.