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20242026
most citedLarge Language Models and Cognitive Science: A Comprehensive Review of Similarities, Differences, and Challenges

10 citations · 68 across the 30 of their papers we have counts for

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22 papers · 1 filter

cs.CR2024★ 2 cited

Deep Learning Model Security: Threats and Defenses

Tianyang Wang, Ziqian Bi, Yichao Zhang +24

Deep learning has transformed AI applications but faces critical security challenges, including adversarial attacks, data poisoning, model theft, and privacy leakage. This survey e…

cs.LG2024★ 8 cited

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs

Weiche Hsieh, Ziqian Bi, Chuanqi Jiang +24

Explainable Artificial Intelligence (XAI) addresses the growing need for transparency and interpretability in AI systems, enabling trust and accountability in decision-making proce…

cs.LG2024

Deep Learning, Machine Learning, Advancing Big Data Analytics and Management

Weiche Hsieh, Ziqian Bi, Keyu Chen +23

Advancements in artificial intelligence, machine learning, and deep learning have catalyzed the transformation of big data analytics and management into pivotal domains for researc…

cs.CV2024★ 1 cited

From Pixels to Prose: Advancing Multi-Modal Language Models for Remote Sensing

Xintian Sun, Benji Peng, Charles Zhang +10

Remote sensing has evolved from simple image acquisition to complex systems capable of integrating and processing visual and textual data. This review examines the development and…

cs.CL2024★ 6 cited

From Word Vectors to Multimodal Embeddings: Techniques, Applications, and Future Directions For Large Language Models

Charles Zhang, Benji Peng, Xintian Sun +14

Word embeddings and language models have transformed natural language processing (NLP) by facilitating the representation of linguistic elements in continuous vector spaces. This r…

cs.CL2024

Deep Learning and Machine Learning -- Natural Language Processing: From Theory to Application

Keyu Chen, Cheng Fei, Ziqian Bi +23

With a focus on natural language processing (NLP) and the role of large language models (LLMs), we explore the intersection of machine learning, deep learning, and artificial intel…

cs.CL2024★ 4 cited

Large Language Model Benchmarks in Medical Tasks

Lawrence K. Q. Yan, Qian Niu, Ming Li +16

With the increasing application of large language models (LLMs) in the medical domain, evaluating these models' performance using benchmark datasets has become crucial. This paper…

cs.CV2024★ 1 cited

Deep Learning, Machine Learning -- Digital Signal and Image Processing: From Theory to Application

Weiche Hsieh, Ziqian Bi, Junyu Liu +16

Digital Signal Processing (DSP) and Digital Image Processing (DIP) with Machine Learning (ML) and Deep Learning (DL) are popular research areas in Computer Vision and related field…

cs.LG2024★ 1 cited

Deep Learning and Machine Learning -- Python Data Structures and Mathematics Fundamental: From Theory to Practice

Silin Chen, Ziqian Bi, Junyu Liu +15

This book provides a comprehensive introduction to the foundational concepts of machine learning (ML) and deep learning (DL). It bridges the gap between theoretical mathematics and…

cs.CV2024★ 3 cited

Deep Learning and Machine Learning -- Object Detection and Semantic Segmentation: From Theory to Applications

Jintao Ren, Ziqian Bi, Qian Niu +16

An in-depth exploration of object detection and semantic segmentation is provided, combining theoretical foundations with practical applications. State-of-the-art advancements in m…

cs.CR2024

Mastering AI: Big Data, Deep Learning, and the Evolution of Large Language Models -- Blockchain and Applications

Pohsun Feng, Ziqian Bi, Lawrence K. Q. Yan +14

A detailed exploration of blockchain technology and its applications across various fields is provided, beginning with an introduction to cryptography fundamentals, including symme…

cs.LG2024★ 2 cited

Mastering AI: Big Data, Deep Learning, and the Evolution of Large Language Models -- AutoML from Basics to State-of-the-Art Techniques

Pohsun Feng, Ziqian Bi, Yizhu Wen +13

A comprehensive guide to Automated Machine Learning (AutoML) is presented, covering fundamental principles, practical implementations, and future trends. The paper is structured to…

cs.DC2024★ 4 cited

Deep Learning and Machine Learning with GPGPU and CUDA: Unlocking the Power of Parallel Computing

Ming Li, Ziqian Bi, Tianyang Wang +14

General Purpose Graphics Processing Unit (GPGPU) computing plays a transformative role in deep learning and machine learning by leveraging the computational advantages of parallel…

cs.SE2024★ 1 cited

Deep Learning and Machine Learning: Advancing Big Data Analytics and Management with Design Patterns

Keyu Chen, Ziqian Bi, Tianyang Wang +12

This book, Design Patterns in Machine Learning and Deep Learning: Advancing Big Data Analytics Management, presents a comprehensive study of essential design patterns tailored for…

cs.CY2024★ 3 cited

From Text to Multimodality: Exploring the Evolution and Impact of Large Language Models in Medical Practice

Qian Niu, Keyu Chen, Ming Li +16

Large Language Models (LLMs) have rapidly evolved from text-based systems to multimodal platforms, significantly impacting various sectors including healthcare. This comprehensive…

cs.CL2024★ 1 cited

Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Unveiling AI's Potential Through Tools, Techniques, and Applications

Pohsun Feng, Ziqian Bi, Yizhu Wen +14

Artificial intelligence (AI), machine learning, and deep learning have become transformative forces in big data analytics and management, enabling groundbreaking advancements acros…

cs.CL2024

Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Object-Oriented Programming

Tianyang Wang, Ziqian Bi, Keyu Chen +12

Object-Oriented Programming (OOP) has become a crucial paradigm for managing the growing complexity of modern software systems, particularly in fields like machine learning, deep l…

cs.CL2024★ 1 cited

Surveying the MLLM Landscape: A Meta-Review of Current Surveys

Ming Li, Keyu Chen, Ziqian Bi +12

The rise of Multimodal Large Language Models (MLLMs) has become a transformative force in the field of artificial intelligence, enabling machines to process and generate content ac…

cs.CL2024

Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Handy Appetizer

Benji Peng, Xuanhe Pan, Yizhu Wen +13

This book explores the role of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) in driving the progress of big data analytics and management. The book fo…

cs.LG2024★ 1 cited

Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Tensorflow Pretrained Models

Keyu Chen, Ziqian Bi, Qian Niu +12

The application of TensorFlow pre-trained models in deep learning is explored, with an emphasis on practical guidance for tasks such as image classification and object detection. T…

cs.CR2024★ 7 cited

Securing Large Language Models: Addressing Bias, Misinformation, and Prompt Attacks

Benji Peng, Keyu Chen, Ming Li +5

Large Language Models (LLMs) demonstrate impressive capabilities across various fields, yet their increasing use raises critical security concerns. This article reviews recent lite…

cs.AI2024★ 10 cited

Large Language Models and Cognitive Science: A Comprehensive Review of Similarities, Differences, and Challenges

Qian Niu, Junyu Liu, Ziqian Bi +16

This comprehensive review explores the intersection of Large Language Models (LLMs) and cognitive science, examining similarities and differences between LLMs and human cognitive p…