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cs.AI2025
AutoSurvey2: Empowering Researchers with Next Level Automated Literature Surveys
Siyi Wu, Chiaxin Liang, Ziqian Bi +7
The rapid growth of research literature, particularly in large language models (LLMs), has made producing comprehensive and current survey papers increasingly difficult. This paper…
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…
cs.AI2024
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…