papers

Publications (8)

cs.AI2025

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…

cs.CY2025

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…

q-bio.GN2026

From In Silico to In Vitro: A Comprehensive Guide to Validating Bioinformatics Findings

Tianyang Wang, Silin Chen, Yunze Wang +18

The integration of bioinformatics predictions and experimental validation plays a pivotal role in advancing biological research, from understanding molecular mechanisms to developi…

cs.CY2026

From Bench to Bedside: A Review of Clinical Trials in Drug Discovery and Development

Tianyang Wang, Ming Liu, Benji Peng +17

Clinical trials are an indispensable part of the drug development process, bridging the gap between basic research and clinical application. During the development of new drugs, cl…

cs.CL2025

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.CL2025

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.AI2025

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…

cs.CL2025

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…