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相关论文: GPT-4 Can't Reason

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Large language models, pivotal in artificial intelligence, find diverse applications. ChatGPT (Chat Generative Pre-trained Transformer), an OpenAI creation, stands out as a widely adopted, powerful tool. It excels in chatbots, content…

计算与语言 · 计算机科学 2025-05-28 Walid Hariri

OpenAI released version GPT-4 on March 14, 2023, following the success of ChatGPT, which was announced in November 2022. In addition to the existing GPT-3 features, GPT-4 can interpret images. To achieve this, the processing power and model…

计算机视觉与模式识别 · 计算机科学 2025-02-04 Omer Aydin , Enis Karaarslan

This study comprehensively evaluates the translation quality of Large Language Models (LLMs), specifically GPT-4, against human translators of varying expertise levels across multiple language pairs and domains. Through carefully designed…

计算与语言 · 计算机科学 2024-07-08 Jianhao Yan , Pingchuan Yan , Yulong Chen , Judy Li , Xianchao Zhu , Yue Zhang

GPT-4 is often heralded as a leading commercial AI offering, sparking debates over its potential as a steppingstone toward artificial general intelligence. But does it possess consciousness? This paper investigates this key question using…

人工智能 · 计算机科学 2024-07-16 Izak Tait , Joshua Bensemann , Ziqi Wang

Recent advances in large language models (LLMs) have enabled general-purpose systems to perform increasingly complex domain-specific reasoning without extensive fine-tuning. In the medical domain, decision-making often requires integrating…

计算与语言 · 计算机科学 2025-08-14 Shansong Wang , Mingzhe Hu , Qiang Li , Mojtaba Safari , Xiaofeng Yang

Large Language Models (LLMs) have recently achieved impressive performance in math and reasoning benchmarks. However, they often struggle with logic problems and puzzles that are relatively easy for humans. To further investigate this, we…

人工智能 · 计算机科学 2025-09-16 Nasim Borazjanizadeh , Roei Herzig , Trevor Darrell , Rogerio Feris , Leonid Karlinsky

It has been suggested that large language models such as GPT-4 have acquired some form of understanding beyond the correlations among the words in text including some understanding of mathematics as well. Here, we perform a critical inquiry…

机器学习 · 计算机科学 2023-11-15 Roozbeh Yousefzadeh , Xuenan Cao

Large language models (LLMs) show impressive abilities via few-shot prompting. Commercialized APIs such as OpenAI GPT-3 further increase their use in real-world language applications. However, the crucial problem of how to improve the…

计算与语言 · 计算机科学 2023-02-16 Chenglei Si , Zhe Gan , Zhengyuan Yang , Shuohang Wang , Jianfeng Wang , Jordan Boyd-Graber , Lijuan Wang

Large language models (LLMs) are now highly capable at a diverse range of tasks. This paper studies whether or not GPT-4, one such LLM, is capable of assisting researchers in the field of adversarial machine learning. As a case study, we…

密码学与安全 · 计算机科学 2023-07-28 Nicholas Carlini

OpenAI has released the Chat Generative Pre-trained Transformer (ChatGPT) and revolutionized the approach in artificial intelligence to human-model interaction. Several publications on ChatGPT evaluation test its effectiveness on well-known…

Commonsense reasoning is a difficult task for a computer, but a critical skill for an artificial intelligence (AI). It can enhance the explainability of AI models by enabling them to provide intuitive and human-like explanations for their…

人工智能 · 计算机科学 2024-07-08 Stefanie Krause , Frieder Stolzenburg

Large language models (LLMs) demonstrate impressive capabilities in mathematical reasoning. However, despite these achievements, current evaluations are mostly limited to specific mathematical topics, and it remains unclear whether LLMs are…

计算与语言 · 计算机科学 2025-04-01 Arash Gholami Davoodi , Seyed Pouyan Mousavi Davoudi , Pouya Pezeshkpour

This study presents the first examination of the ability of Large Language Models (LLMs) to follow reasoning strategies that are used to guide Automated Theorem Provers (ATPs). We evaluate the performance of GPT4, GPT3.5 Turbo and Google's…

计算与语言 · 计算机科学 2024-07-31 Lachlan McGinness , Peter Baumgartner

Large language models (LLMs) have demonstrated remarkable capabilities in natural language understanding and generation across various domains, including medicine. We present a comprehensive evaluation of GPT-4, a state-of-the-art LLM, on…

计算与语言 · 计算机科学 2023-04-13 Harsha Nori , Nicholas King , Scott Mayer McKinney , Dean Carignan , Eric Horvitz

Generative AI models garnered a large amount of public attention and speculation with the release of OpenAIs chatbot, ChatGPT. At least two opinion camps exist: one excited about possibilities these models offer for fundamental changes to…

人工智能 · 计算机科学 2024-06-28 Ann Speed

Large Language Models (LLMs) have garnered considerable interest within both academic and industrial. Yet, the application of LLMs to graph data remains under-explored. In this study, we evaluate the capabilities of four LLMs in addressing…

人工智能 · 计算机科学 2023-09-12 Chang Liu , Bo Wu

Since its introduction to the public, ChatGPT has had an unprecedented impact. While some experts praised AI advancements and highlighted their potential risks, others have been critical about the accuracy and usefulness of Large Language…

人工智能 · 计算机科学 2024-12-13 Anthony C. Constantinou , Neville K. Kitson , Alessio Zanga

Large language models (LLMs) have demonstrated remarkable capabilities in natural language understanding, reasoning, and problem-solving across various domains. However, their ability to perform complex, multi-step reasoning task-essential…

Lately, Large Language Models have been widely used in code generation. GPT4 is considered the most potent Large Language Model from Openai. In this paper, we examine GPT3.5 and GPT4 as coding assistants. More specifically, we have…

人工智能 · 计算机科学 2023-09-25 Lefteris Moussiades , George Zografos

Large Language Models (LLMs) have demonstrated exceptional capabilities in various natural language tasks, often achieving performances that surpass those of humans. Despite these advancements, the domain of mathematics presents a…

计算与语言 · 计算机科学 2024-04-02 Ankit Satpute , Noah Giessing , Andre Greiner-Petter , Moritz Schubotz , Olaf Teschke , Akiko Aizawa , Bela Gipp