9 citations · 38 across the 13 of their papers we have counts for
13 papers
Advanced Deep Learning Methods for Protein Structure Prediction and Design
Yichao Zhang, Ningyuan Deng, Xinyuan Song +25
After AlphaFold won the Nobel Prize, protein prediction with deep learning once again became a hot topic. We comprehensively explore advanced deep learning methods applied to prote…
Generative Adversarial Networks Bridging Art and Machine Intelligence
Junhao Song, Yichao Zhang, Ziqian Bi +25
Generative Adversarial Networks (GAN) have greatly influenced the development of computer vision and artificial intelligence in the past decade and also connected art and machine i…
From In Silico to In Vitro: A Comprehensive Guide to Validating Bioinformatics Findings
Tianyang Wang, Silin Chen, Yunze Wang +18
Translating computational predictions into experimentally validated biological knowledge remains one of the central challenges in modern bioinformatics. This review critically exam…
From Aleatoric to Epistemic: Exploring Uncertainty Quantification Techniques in Artificial Intelligence
Tianyang Wang, Yunze Wang, Jun Zhou +16
Uncertainty quantification (UQ) is a critical aspect of artificial intelligence (AI) systems, particularly in high-risk domains such as healthcare, autonomous systems, and financia…
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…
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…
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…
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…
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…
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…
Jailbreaking and Mitigation of Vulnerabilities in Large Language Models
Benji Peng, Hanxuan Chen, Keyu Chen +12
Large Language Models (LLMs) have transformed artificial intelligence by advancing natural language understanding and generation, enabling applications across fields beyond healthc…
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…
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…