关键之处在于,大语言模型引入一种基于文本和元数据(也就是变量名)的新推理方式来实现这一目标,称之为基于知识的因果推理(knowledge-based causal reasoning),这与现有的基于数据的方法有所不同。 具体而言,大语言模型拥有迄今为止被认为只有人类才具有的能力,如使用知识生成因果图,或从自然语言中识别背景因果关系。
The causal capabilities of large language models (LLMs) is a matter of significant debate, with critical implications for the use of LLMs in societally impactful domains such as medicine, science, law, and policy. We further our understanding of LLMs and their...
whose paper “Causal Reasoning and Large Language Models: Opening a New Frontier for Causality” examines the causal capabilities of large language models (LLMs) and their implications. Kiciman and Sharma break down the study of cause and effect; recount their respective ongoin...
Tuebingen cause-effect pairs dataset (Original) Distinguishing cause from effect using observational data: methods and benchmarks(LLM) Causal Reasoning and Large Language Models: Opening a New Frontier for Causality https://github.com/amit-sharma/chatgpt-causality-pairs/tree/mainAbout...
Moreover, recent papers have argued that complex behaviors, such as writing code, generating long stories, and even some reasoning capabilities, can emerge from such large-scale training (Wei et al., 2022; Rozi` ere et al., 2023; Zhao et al., 2023; Yao et al., 2023). 最新研究认为大...
(2024 TMLR) Causal Reasoning and Large Language Models: Opening a New Frontier for Causality. Emre Kıcıman, Robert Ness, Amit Sharma, Chenhao Tan. [pdf] (2024 ACL Findings) Are LLMs Capable of Data-based Statistical and Causal Reasoning? Benchmarking Advanced Quantitative Reasoning with...
We found that metacognitive prompting does not necessarily make LLMs perform deep insights and that they may only pretend to perform deep insights. 展开 关键词: Large language models Focusing Cognition Task analysis 会议名称: 2024 IEEE Conference on Artificial Intelligence (CAI) 主办单位: IEEE ...
Eventually, this reasoning AI could analyze scientific processes and improve global issues, such as the supply chain, according to Hebner. “One of the challenges with today’s large language models and generative AI in general is that it’s based on a correlative design,” he said. “It ...
Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models,. arXiv Google Scholar [17] Pearl J. Causality. Cambridge university press, 2009. Google Scholar [18] Gao C, Zheng Y, Wang W, et al. Causal inference in recommender systems: A ...
断点回归不是去真的“干预”，而是寻找一种自然发生的、类似于随机对照试验的设置。这种设置通常是某种...