Reasoning is a fundamental aspect of human intelligence that plays a crucial role in
activities such as problem solving, decision making, and critical thinking. In recent years …

Large language models (LLMs) have pushed the limits of natural language understanding
and exhibited excellent problem-solving ability. Despite the great success, most existing …

The surprising ability of Large Language Models (LLMs) to perform well on complex
reasoning with only few-shot chain-of-thought prompts is believed to emerge only in very …

Reasoning, as an essential ability for complex problem-solving, can provide back-end
support for various real-world applications, such as medical diagnosis, negotiation, etc. This …

Recent works have shown that chain-of-thought (CoT) prompting can elicit language models
to solve complex reasoning tasks, step-by-step. However, prompt-based CoT methods are …

Chain of thought prompting successfully improves the reasoning capabilities of large
language models, achieving state of the art results on a range of datasets. However, these …

Large Language Models (LLMs) have revolutionized natural language processing tasks with
remarkable success. However, their formidable size and computational demands present …

Large models based on the Transformer architecture play increasingly vital roles in artificial
intelligence, particularly within the realms of natural language processing (NLP) and …

Step-by-step reasoning approaches like chain of thought (CoT) have proved to be very
effective in inducing reasoning capabilities in large language models. However, the success …

Chain-of-thought prompting (eg," Let's think step-by-step") primes large language models to
verbalize rationalization for their predictions. While chain-of-thought can lead to dramatic …