Large Language Models (LLMs) represent a landmark achievement in Artificial Intelligence (AI), demonstrating unprecedented proficiency in procedural tasks such as text generation, code completion, and conversational coherence. These capabilities stem from their architecture, which mirrors human procedural memory -- the brain's ability to automate repetitive, pattern-driven tasks through practice. However, as LLMs are increasingly deployed in real-world applications, it becomes impossible to ignore their limitations operating in complex, unpredictable environments. This paper argues that LLMs, while transformative, are fundamentally constrained by their reliance on procedural memory. To create agents capable of navigating ``wicked'' learning environments -- where rules shift, feedback is ambiguous, and novelty is the norm -- we must augment LLMs with semantic memory and associative learning systems. By adopting a modular architecture that decouples these cognitive functions, we can bridge the gap between narrow procedural expertise and the adaptive intelligence required for real-world problem-solving.
Meta-Cognitive Analysis: Evaluating Declarative and Procedural Knowledge in Datasets and Large Language Models
University of Chinese Academy of Sciences(中国科学院大学);Chinese Information Processing Laboratory(中文信息处理实验室);State Key Laboratory of Computer Science(计算机科学国家重点实验室);Institute of Software, Chinese Academy of Sciences(中国科学院软件研究所)
Conversational Education at Scale: A Multi-LLM Agent Workflow for Procedural Learning and Pedagogic Quality Assessment
Vrije University of Amsterdam(阿姆斯特丹自由大学);University College London(伦敦大学学院);University of Amsterdam(阿姆斯特丹大学);National Institute of Informatics(日本信息处理学会);Shandong University(山东大学);Guangzhou University(广州大学)
The Pragmatic Persona: Discovering LLM Persona through Bridging Inference
Department of Artificial Intelligence, Chung-Ang University, Seoul, 06974, Republic of Korea(Chung-Ang大学人工智能系);Department of Computer Science, University of British Columbia, Vancouver, BC V6T 1Z4, Canada(不列颠哥伦比亚大学计算机科学系);Van Lang University, Ho Chi Minh City, Vietnam(文-lang大学)
MedCoG: Maximizing LLM Inference Density in Medical Reasoning via Meta-Cognitive Regulation
College of Computer Science, VCIP, DISSec Center, Nankai University, China 300350(南开大学计算机学院、VCIP、DISSec中心、中国300350);Generative AI Lab, College of Computing and Data Science(生成式人工智能实验室、计算与数据科学学院);Nanyang Technological University, Singapore 639798(南洋理工大学,新加坡639798)
Cognitive Mismatch in Multimodal Large Language Models for Discrete Symbol Understanding
Tsinghua University(清华大学);Sun Yat-sen University(中山大学);Independent Researcher(独立研究员);The Hong Kong Polytechnic University(香港理工大学);Guangdong Laboratory of AI and Digital Economy (SZ)(广东省人工智能与数字经济实验室(深圳));University of Illinois Chicago(伊利诺伊大学芝加哥分校)
SurgBox: Agent-Driven Operating Room Sandbox with Surgery Copilot
CAIR, HKISI, CAS(中国科学院香港中文大学信息安全研究所智能计算研究中心);MAIS, Institute of Automation, Chinese Academy of Sciences(中国科学院自动化研究所多模态人工智能系统实验室);Peking Union Medical College Hospital(北京协和医院)
Cognitive Chain-of-Thought (CoCoT): Structured Multimodal Reasoning about Social Situations
Seoul National University(首尔国立大学);Human-Computer Interaction Institute, Carnegie Mellon University(人机交互研究所,卡内基梅隆大学);Language Technologies Institute, Carnegie Mellon University(语言技术研究所,卡内基梅隆大学)
Towards Unified Surgical Scene Understanding:Bridging Reasoning and Grounding via MLLMs
Southern University of Science and Technology(南方科技大学);Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences(深圳先进技术研究院,中国科学院);Northwestern University(西北大学);University of Alberta(阿尔伯塔大学);Yale University(耶鲁大学);Nanfang Hospital(南华医院);Shenzhen University of Advanced Technology(深圳大学先进技术研究院)
CLiViS: Unleashing Cognitive Map through Linguistic-Visual Synergy for Embodied Visual Reasoning
School of Computer Science and Technology, East China Normal University(东华大学计算机科学与技术学院);King Abdullah University of Science and Technology(科廷大学);Fudan University(复旦大学)
Bridging LSTM Architecture and the Neural Dynamics during Reading
Shanghai Key Laboratory of Intelligent Information Processing, Fudan University(复旦大学上海市智能信息处理重点实验室);School of Computer Science, Fudan University(复旦大学计算机科学技术学院)
Bridging Cognitive Neuroscience and Graph Intelligence: Hippocampus-Inspired Multi-View Hypergraph Learning for Web Finance Fraud
School of Computer Science and Technology, Tongji University(同济大学计算机科学与技术学院);School of Computer Science and Technology, Donghua University(东华大学计算机科学与技术学院)
PonsRAG: A Pons-Inspired RAG Bridging Cognitive Islands for Coordinated Long Narrative Reasoning
School of Future Technology, South China University of Technology(华南理工大学未来技术学院);TikTok Inc(字节跳动公司);School of Artificial Intelligence, Sun Yat-sen University(中山大学人工智能学院);School of Software Engineering, Sun Yat-sen University(中山大学软件工程学院)
Bridging the Cognitive Gap: A Unified Memory Paradigm for 6G Agentic AI-RAN
Sun Yat-sen University, China(中山大学,中国);Zhejiang University, China(浙江大学,中国);University of Exeter, U.K.(埃克塞特大学,英国);Singapore University of Technology and Design, Singapore(新加坡科技设计大学,新加坡);Purple Mountain Laboratories, Nanjing, China(紫金山实验室,南京,中国)
Bridging Values and Behavior: A Hierarchical Framework for Proactive Embodied Agents
State Key Laboratory of General Artificial Intelligence, BIGAI(通用人工智能国家重点实验室,BIGAI);School of Computer Science, Peking University(北京大学计算机学院);Tsinghua University(清华大学);Nat’l Eng. Research Center of Visual Technology, Peking University(北京大学视觉技术国家工程研究中心);Institute for AI, Peking University(北京大学人工智能研究院);State Key Laboratory of General Artificial Intelligence, Peking University(通用人工智能国家重点实验室,北京大学)
Craftium: Bridging Flexibility and Efficiency for Rich 3D Single- and Multi-Agent Environments
Department of Computer Science and Artificial Intelligence, University of the Basque Country UPV/EHU(计算机科学与人工智能系,巴斯克国家大学UPV/EHU);Basque Center for Applied Mathematics (BCAM)(巴斯克应用数学中心)