Bao Ge

Exploring ChatGPT's potential in dialogic teaching: A comparative neurocognitive study of AI and human instruction

Jiayue Zhang, Bochen Xu, Liu Y, Wenqi Cai et autres

Recent advances in large language models (LLMs) have intensified interest in using ChatGPT for educational dialogue. This study examined whether ChatGPT can function as an instructional partner in dialogic teaching and how it differs from a human instructor in learning outcomes and …

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The performances of the Chinese and U.S. Large Language Models on the Topic of Chinese Culture

Feiyan Liu, Siyan Zhao, Chenxun Zhuo, Tianming Liu et autres

Cultural backgrounds shape individuals' perspectives and approaches to problem-solving. Since the emergence of GPT-1 in 2018, large language models (LLMs) have undergone rapid development. To date, the world's ten leading LLM developers are primarily based in China and the United States. To …

The performances of the Chinese and U.S. Large Language Models on the Topic of Chinese Culture

Feiyan Liu, Siyan Zhao, Chenxun Zhuo, Tianming Liu et autres

Cultural backgrounds shape individuals' perspectives and approaches to problem-solving. Since the emergence of GPT-1 in 2018, large language models (LLMs) have undergone rapid development. To date, the world's ten leading LLM developers are primarily based in China and the United States. To …

Prompt engineering for healthcare: Methodologies and applications

Jiaqi Wang, Enze Shi, Sigang Yu, Zihao Wu et autres

Prompt engineering is a critical technique in the field of natural language processing (NLP) that involves designing and optimizing the prompts used to input information into models, aiming to enhance their performance on specific tasks. With the recent advancements in large language …

Simultaneous formaldehyde/benzene adsorption on functionalized metal-organic framework UIO-66-NH2

Shengwang Pan, Dixiong Li, Bao Ge, Lin Ju et autres

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3D masked autoencoder with spatiotemporal transformer for modeling of 4D fMRI data

Jie Gao, Bao Ge, Ning Qiang, Shijie Zhao

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Brain-Inspired Exploration of Functional Networks and Key Neurons in Large Language Models

Yiheng Liu, Haiyang Sun, Xiaohui Gao, Bao Ge et autres

In recent years, the rapid advancement of large language models (LLMs) in natural language processing has sparked significant interest among researchers to understand their mechanisms and functional characteristics. Although prior studies have attempted to explain LLM functionalities by identifying and interpreting specific …

Large language models for robotics: Opportunities, challenges, and perspectives

Jiaqi Wang, Enze Shi, Huawen Hu, Chong Ma et autres

Large language models (LLMs) have undergone significant expansion and have been increasingly integrated across various domains. Notably, in the realm of robot task planning, LLMs harness their advanced reasoning and language comprehension capabilities to formulate precise and efficient action plans based on …

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Understanding LLMs: A comprehensive overview from training to inference

Yiheng Liu, Hao He, Tianle Han, Xu Zhang et autres

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A Survey of Foundation Models for Music Understanding

Wenjun Li, Ying Cai, Ziyang Wu, Wenyi Zhang et autres

Music is essential in daily life, fulfilling emotional and entertainment needs, and connecting us personally, socially, and culturally. A better understanding of music can enhance our emotions, cognitive skills, and cultural connections. The rapid advancement of artificial intelligence (AI) has introduced new …

Exploring New Frontiers in Agricultural NLP: Investigating the Potential of Large Language Models for Food Applications

Saed Rezayi, Zhengliang Liu, Zihao Wu, Chandra Dhakal et autres

This paper explores new frontiers in agricultural natural language processing (NLP) by investigating the effectiveness of food-related text corpora for pretraining transformer-based language models. Specifically, we focus on semantic matching, establishing mappings between food descriptions and nutrition data through fine-tuning AgriBERT with …

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A Comprehensive Review of Multimodal Large Language Models: Performance and Challenges Across Different Tasks

Jiaqi Wang, Hanqi Jiang, Yiheng Liu, Chong Ma et autres

In an era defined by the explosive growth of data and rapid technological advancements, Multimodal Large Language Models (MLLMs) stand at the forefront of artificial intelligence (AI) systems. Designed to seamlessly integrate diverse data types-including text, images, videos, audio, and physiological sequences-MLLMs …