Language Cognition and Language Computation -- Human and Machine Language Understanding
Institute of Automation, CAS（中国科学院自动化研究所）；University of Chinese Academy of Sciences（中国科学院大学）；Zhejiang University（浙江大学）；Zhejiang Lab（之江实验室）；Institute of Psychology（中国科学院心理研究所）
Shaonan Wang, Nai Ding, Nan Lin, Jiajun Zhang, Chengqing Zong
备注：
A survey of language comprehension in cognitive sciences and language understanding in computer sciences and their relations
Language understanding is a key scientific issue in the fields of cognitive and computer science. However, the two disciplines differ substantially in the specific research questions. Cognitive science focuses on analyzing the specific mechanism of the brain and investigating the brain's response to language; few studies have examined the brain's language system as a whole. By contrast, computer scientists focus on the efficiency of practical applications when choosing research questions but may ignore the most essential laws of language. Given these differences, can a combination of the disciplines offer new insights for building intelligent language models and studying language cognitive mechanisms? In the following text, we first review the research questions, history, and methods of language understanding in cognitive and computer science, focusing on the current progress and challenges. We then compare and contrast the research of language understanding in cognitive and computer sciences. Finally, we review existing work that combines insights from language cognition and language computation and offer prospects for future development trends.
Memorization $\neq$ Understanding: Do Large Language Models Have the Ability of Scenario Cognition?
School of Computer and Information Technology, Shanxi University（山西大学计算机与信息学院）；Information Systems Technology and Design, Singapore University of Technology and Design（新加坡科技设计大学信息系统技术与设计）
How Deep is Love in LLMs' Hearts? Exploring Semantic Size in Human-like Cognition
Shanghai Jiao Tong University（上海交通大学）；Shanghai Key Laboratory of Trusted Data Circulation and Governance in Web3（上海Web3可信数据流通与治理重点实验室）；Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering（上海市教委智能交互与认知工程重点实验室）
From Human Cognition to Neural Activations: Probing the Computational Primitives of Spatial Reasoning in LLMs
School of Information Science, Beijing Language and Culture University（北京语言大学信息科学学院）；School of Artificial Intelligence, Beijing Normal University（北京师范大学人工智能学院）
Psychomatics -- A Multidisciplinary Framework for Understanding Artificial Minds
Catholic University of Sacred Heart（圣心天主教大学）；Istituto Auxologico Italiano IRCCS（意大利奥索洛吉科研究所）；University of Milano - Bicocca（米兰比可卡大学）；Virtual Reality Medical Center（虚拟现实医疗中心）；Interactive Media Institute（交互媒体研究所）
Between Sense and Sensibility: Declarative narrativisation of mental models as a basis and benchmark for visuo-spatial cognition and computation focussed collaborative cognitive systems
University of Bremen（不来梅大学）
“\emph{sensing}”和“\emph{sensibility}”之间有什么区别？换句话说，什么样的认知过程介导了感知能力和可感知印象的形成-例如，抽象，类比，假设和理论的形成，信念和他们的修正，论点的形成-在特定领域的问题解决中，还是在日常生活，工作和简单地在环境中走动的常规活动中？如何才能知识和推理的能力，表现出人类在特定的问题背景下，被用来作为一个模型和基准的发展与人类的援助，保证和授权的协作认知（互动）系统？我们提出这些问题的背景下，一系列的辅助技术与\emph{visuo-spatial perception and cognition}任务，包括方面，如常识，创造力，专业领域的知识和解决问题的思维过程的应用。正在考虑的辅助技术包括：（a）人类活动解释;（b）高级认知旋转;（c）建筑和数字媒体创作等领域以人为本的创造性设计;（d）地理信息系统的定性分析。计算叙事不仅提供了丰富的认知基础，但他们也作为一个基准的功能性能在我们的发展计算认知辅助系统。我们认为，有关空间，行动和变化的计算叙事提供了一个有用的模型\emph{visual}和\emph{spatio-temporal thinking}在广泛的解决问题的任务和应用领域，协作认知系统可以提供一个辅助和授权功能。
CogTree: Cognition Tree Loss for Unbiased Scene Graph Generation
Institute of Information Engineering, Chinese Academy of Sciences（中国科学院信息工程研究所）；Peking University（北京大学）；University of Adelaide（阿德莱德大学）；Beihang University（北京航空航天大学）
Rate-Coding Bundle Memory: A Unified Model of Memory and Control for Symbolic Computation in the Brain
Max Planck Institute for Psycholinguistics（马克斯·普朗克心理语言学研究所）；Donders Institute for Brain, Cognition and Behaviour（唐德斯大脑、认知与行为研究所）；Radboud University（拉德堡德大学）
