大型语言模型可以推理和规划吗?
1School of Computing & Augmented Intelligence, Arizona State University.
Annals of the New York Academy of Sciences
|March 6, 2024
概括
大型语言模型 (LLM) 不能像人类那样自我批评和纠正错误. 目前的研究表明,AI语言模型中没有自我纠正能力的证据.
科学领域:
- 人工智能的人工智能
- 认知科学 认知科学
- 自然语言处理自然语言处理.
背景情况:
- 人类拥有自我纠正的能力,通过批判性自我评估来完善自己的错误判断.
- 人工智能,特别是大型语言模型 (LLM) 的自我批评能力仍然是一个悬而未决的问题.
研究的目的:
- 调查大型语言模型 (LLM) 是否表现出类似于人类认知功能的自我批评和错误纠正能力.
- 为了确定当前的LLM架构是否为自我生成的错误纠正提供了基础.
主要方法:
- 对自我识别错误实例的LLM输出进行分析.
- 人类与LLM错误纠正机制的比较研究.
- 检查内部LLM流程的自我监控功能.
主要成果:
- 没有证据支持LLM可以自我批评和纠正他们自己的错误输出的假设.
- 目前,LLM的行为并不反映人类的自我纠正过程.
结论:
- 人类常见的自我批评和错误纠正能力在当前的大型语言模型 (LLM) 中没有得到证明.
- 需要进一步的研究来探索潜在的未来发展或替代架构,这些架构可能使人工智能具有这种能力.
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