Large Language Models (LLMs) have emerged as powerful tools, not just for their ability to process and generate text, but for their increasingly sophisticated reasoning capabilities. This article explores how the reasoning power of LLMs is transformingsocial consumer insightbusinesses, enabling...
large language model (the text-davinci-003 variant of Generative Pre-trained Transformer (GPT)-3) on a range of analogical tasks, including a non-visual matrix reasoning task based on the rule structure of Raven’s Standard Progressive Matrices. We found that GPT-3 displayed a surprisingly ...
There have been a large number of studies on reasoning abilities in LLMs74,75,76. Previous studies have focused, among others, on testing LLMs’ cognitive abilities in model-based planning73, analogical reasoning tests77, exploration tasks78, systematic reasoning tests79,80, psycholinguistic complet...
and version 4, which was the state-of-the-art model with enhanced reasoning, creativity and comprehension relative to previous models (https://chat.openai.com/). Each test was delivered in a separate chat: GPT is capable of learning within a chat session, as it can...
There have been a large number of studies on reasoning abilities in LLMs74,75,76. Previous studies have focused, among others, on testing LLMs’ cognitive abilities in model-based planning73, analogical reasoning tests77, exploration tasks78, systematic reasoning tests79,80, psycholinguistic complet...
Optimizing Language Model's Reasoning Abilities with Weak Supervision Yongqi Tong, Sizhe Wang, Dawei Li, Yifan Wang, Simeng Han, Zi Lin, Chengsong Huang, Jiaxin Huang, Jingbo Shang 2024 LLMaAA: Making Large Language Models as Active Annotators Ruoyu Zhang, Yanzeng Li, Yongliang Ma, Ming Zhou...
CoT prompting, as introduced in arecent paper, is a method that encourages LLMs to explain their reasoning process. This is achieved by providing the model with a few-shot exemplars where the reasoning process is explicitly outlined. The LLM is then expected to follow a similar reasoning proces...
This repo provides the source code & data of our paper: Unleashing the Potential of Large Language Models as Prompt Optimizers: An Analogical Analysis with Gradient-based Model Optimizers.😀 OverviewHighlights:1️⃣ We are the first to conduct a systematic study for LLM-based prompt optimizers...
We speculate that this is due to the hallucination within the model. 🔎Citation If you find Self-Demos useful or relevant to your project and research, please kindly cite our paper: @misc{he2024selfdemos, title={Self-Demos: Eliciting Out-of-Demonstration Generalizability in Large Language ...
Webb, T., Holyoak, K. J. & Lu, H. Emergent analogical reasoning in large language models.Nat. Hum. Behav.7, 1526–1541 (2023). Frank, M. C. Openly accessible LLMs can help us to understand human cognition.Nat. Hum. Behav.7, 1825–1827 (2023). ...