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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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Showing 2025Show all

6 papers · 1 filter

cs.AI2025

Japanese AI Agent System on Human Papillomavirus Vaccination: System Design

Junyu Liu, Siwen Yang, Dexiu Ma +4

Human papillomavirus (HPV) vaccine hesitancy poses significant public health challenges, particularly in Japan where proactive vaccination recommendations were suspended from 2013…

cs.CL2025★ 1 cited

KokushiMD-10: Benchmark for Evaluating Large Language Models on Ten Japanese National Healthcare Licensing Examinations

Junyu Liu, Kaiqi Yan, Tianyang Wang +3

Recent advances in large language models (LLMs) have demonstrated notable performance in medical licensing exams. However, comprehensive evaluation of LLMs across various healthcar…

q-bio.BM2025

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…

cs.LG2025

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…

q-bio.GN2025★ 2 cited

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…

cs.AI2025★ 9 cited

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…