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相关论文: A Pilot Evaluation of ChatGPT and DALL-E 2 on Deci…

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This paper aims to investigate the mathematical problem-solving capabilities of Chat Generative Pre-Trained Transformer (ChatGPT) in case of Bayesian reasoning. The study draws inspiration from Zhu & Gigerenzer's research in 2006, which…

人工智能 · 计算机科学 2023-08-29 Renato A. Krohling

Generative AI systems such as ChatGPT challenge traditional assumptions about academic assessment by enabling students to generate explanations, code, and solutions in real time. Rather than attempting to restrict AI use, this study…

计算机与社会 · 计算机科学 2026-05-13 Qusay H. Mahmoud

In this study we compared how well DALL-E 2 visually represented the meaning of linguistic prompts also given to young children in comprehension tests. Sentences representing fundamental components of grammatical knowledge were selected…

计算与语言 · 计算机科学 2024-03-20 Elliot Murphy , Jill de Villiers , Sofia Lucero Morales

This research paper presents the findings of two experimental studies that explore the use of ChatGPT as a tool for theory prototyping. The objective of the studies is to assess ChatGPT's ability to comprehend theoretical concepts and…

人机交互 · 计算机科学 2023-07-13 Tiong-Thye Goh

Despite the significant advancements in natural language processing capabilities demonstrated by large language models such as ChatGPT, their proficiency in comprehending and processing spatial information, especially within the domains of…

计算与语言 · 计算机科学 2023-12-07 He Yan , Xinyao Hu , Xiangpeng Wan , Chengyu Huang , Kai Zou , Shiqi Xu

Artificial intelligence (AI) has made remarkable progress across various domains, with large language models like ChatGPT gaining substantial attention for their human-like text-generation capabilities. Despite these achievements, spatial…

人工智能 · 计算机科学 2024-01-11 Fangjun Li , David C. Hogg , Anthony G. Cohn

This paper proposes a framework for quantitatively evaluating interactive LLMs such as ChatGPT using publicly available data sets. We carry out an extensive technical evaluation of ChatGPT using 23 data sets covering 8 different common NLP…

Despite remarkable progress in multi-modal AI research, there is a salient domain in which modern AI continues to lag considerably behind even human children: the reliable deployment of logical operators. Here, we examine three forms of…

计算机视觉与模式识别 · 计算机科学 2024-11-27 Colin Conwell , Rupert Tawiah-Quashie , Tomer Ullman

Explanatory inference is the creation and evaluation of hypotheses that provide explanations, and is sometimes known as abduction or abductive inference. Generative AI is a new set of artificial intelligence models based on novel algorithms…

人工智能 · 计算机科学 2024-09-20 Paul Thagard

Large language models (LLMs) such as ChatGPT and GPT-4 have shown impressive performance in complex reasoning tasks. However, it is difficult to know whether the models are reasoning based on deep understandings of truth and logic, or…

计算与语言 · 计算机科学 2023-10-11 Boshi Wang , Xiang Yue , Huan Sun

Machine intelligence is increasingly being linked to claims about sentience, language processing, and an ability to comprehend and transform natural language into a range of stimuli. We systematically analyze the ability of DALL-E 2 to…

计算与语言 · 计算机科学 2022-10-26 Evelina Leivada , Elliot Murphy , Gary Marcus

Recent studies have demonstrated the emerging capabilities of foundation models like ChatGPT in several fields, including affective computing. However, accessing these emerging capabilities is facilitated through prompt engineering. Despite…

计算与语言 · 计算机科学 2024-03-22 Mostafa M. Amin , Björn W. Schuller

Harnessing logical reasoning ability is a comprehensive natural language understanding endeavor. With the release of Generative Pretrained Transformer 4 (GPT-4), highlighted as "advanced" at reasoning tasks, we are eager to learn the GPT-4…

计算与语言 · 计算机科学 2023-05-08 Hanmeng Liu , Ruoxi Ning , Zhiyang Teng , Jian Liu , Qiji Zhou , Yue Zhang

Recently, DALL-E, a multimodal transformer language model, and its variants, including diffusion models, have shown high-quality text-to-image generation capabilities. However, despite the realistic image generation results, there has not…

计算机视觉与模式识别 · 计算机科学 2023-09-01 Jaemin Cho , Abhay Zala , Mohit Bansal

Recently, ChatGPT has attracted great attention, as it can generate fluent and high-quality responses to human inquiries. Several prior studies have shown that ChatGPT attains remarkable generation ability compared with existing models.…

计算与语言 · 计算机科学 2023-03-03 Qihuang Zhong , Liang Ding , Juhua Liu , Bo Du , Dacheng Tao

Recent advances in generative AI make it convenient to create different types of content, including text, images, and code. In this paper, we explore the generation of images in the style of paintings in the surrealism movement using…

计算机视觉与模式识别 · 计算机科学 2024-12-20 Elif Ayten , Shuai Wang , Hjalmar Snoep

While large language models have made strides in natural language processing, their proficiency in complex reasoning tasks requiring formal language comprehension, such as chess, remains less investigated. This paper probes the performance…

计算与语言 · 计算机科学 2023-08-30 Mu-Tien Kuo , Chih-Chung Hsueh , Richard Tzong-Han Tsai

ChatGPT has shown its great power in text processing, including its reasoning ability from text reading. However, there has not been any direct comparison between human readers and ChatGPT in reasoning ability related to text reading. This…

计算与语言 · 计算机科学 2023-11-20 Tongquan Zhou , Yao Zhang , Siyi Cao , Yulu Li , Tao Wang

The recently released ChatGPT has demonstrated surprising abilities in natural language understanding and natural language generation. Machine translation relies heavily on the abilities of language understanding and generation. Thus, in…

计算与语言 · 计算机科学 2023-04-24 Yuan Gao , Ruili Wang , Feng Hou

Vision Language Models (VLMs) have demonstrated remarkable performance in 2D vision and language tasks. However, their ability to reason about spatial arrangements remains limited. In this work, we introduce Spatial Region GPT (SpatialRGPT)…

计算机视觉与模式识别 · 计算机科学 2024-10-16 An-Chieh Cheng , Hongxu Yin , Yang Fu , Qiushan Guo , Ruihan Yang , Jan Kautz , Xiaolong Wang , Sifei Liu
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