Conceptual entanglement is a crucial phenomenon in quantum cognition because it implies that classical probabilities cannot model non--compositional conceptual phenomena. While several psychological experiments have been developed to test conceptual entanglement, this has not been explored in the context of Natural Language Processing. In this paper, we apply the hypothesis that words of a document are traces of the concepts that a person has in mind when writing the document. Therefore, if these concepts are entangled, we should be able to observe traces of their entanglement in the documents. In particular, we test conceptual entanglement by contrasting language simulations with results obtained from a text corpus. Our analysis indicates that conceptual entanglement is strongly linked to the way in which language is structured. We discuss the implications of this finding in the context of conceptual modeling and of Natural Language Processing.
Concept than Document: Context Compression via AMR-based Conceptual Entropy
University of Southern Queensland（南方昆士兰大学）；University of Technology Sydney（技术悉尼大学）；The Hong Kong Polytechnic University（香港理工大学）；Wuhan University of Technology（武汉理工大学）；National University of Singapore（新加坡国立大学）；The Education University of Hong Kong（香港教育大学）
HiTR: Hierarchical Topic Model Re-estimation for Measuring Topical Diversity of Documents
Informatics Institute, University of Amsterdam（阿姆斯特丹大学信息学研究所）；Institute for Logic, Language, and Computation, University of Amsterdam（阿姆斯特丹大学逻辑、语言与计算研究所）
Estranged Predictions: Measuring Semantic Category Disruption with Masked Language Modelling
School of Arts, Queen Mary University of London（艺术学院，伦敦女王学院）；School of Electronic Engineering and Computer Science, Queen Mary University of London（电子工程与计算机科学学院，伦敦女王学院）
When More Documents Hurt RAG: Measuring and Reducing Vector Search Dilution with Domain-Scoped Retrieval
Dept. of Electrical Engineering & Computer Science, University of Wyoming（怀俄明大学电气工程与计算机科学系）；Dept. of Civil, Architectural Engineering & Construction Management, University of Wyoming（怀俄明大学土木、建筑工程与施工管理系）
Methods for Computing Legal Document Similarity: A Comparative Study
Indian Institute of Technology Kharagpur（印度理工学院克勒格布尔分校）；Tata Research Development and Design Centre (TRDDC)（塔塔研究开发与设计中心（TRDDC））；Data61, CSIRO（澳大利亚联邦科学与工业研究组织 Data61）；Cyber Security CRC（网络安全合作研究中心）
One fish, two fish, but not the whole sea: Alignment reduces language models' conceptual diversity
School of Engineering and Applied Sciences, Harvard University（哈佛大学工程与应用科学学院）；Kempner Institute for the Study of Natural and Artificial Intelligence, Harvard University（哈佛大学自然与人工智能研究学院）；Department of Psychology, Harvard University（哈佛大学心理学系）
