This paper introduces how human languages can be studied in light of recent development of network theories. There are two directions of exploration. One is to study networks existing in the language system. Various lexical networks can be built based on different relationships between words, being semantic or syntactic. Recent studies have shown that these lexical networks exhibit small-world and scale-free features. The other direction of exploration is to study networks of language users (i.e. social networks of people in the linguistic community), and their role in language evolution. Social networks also show small-world and scale-free features, which cannot be captured by random or regular network models. In the past, computational models of language change and language emergence often assume a population to have a random or regular structure, and there has been little discussion how network structures may affect the dynamics. In the second part of the paper, a series of simulation models of diffusion of linguistic innovation are used to illustrate the importance of choosing realistic conditions of population structure for modeling language change. Four types of social networks are compared, which exhibit two categories of diffusion dynamics. While the questions about which type of networks are more appropriate for modeling still remains, we give some preliminary suggestions for choosing the type of social networks for modeling.
Shaping Shared Languages: Human and Large Language Models' Inductive Biases in Emergent Communication
Leiden Institute of Advanced Computer Science, Leiden University, Netherlands（莱顿高级计算机科学研究所，莱顿大学，荷兰）；School of Computing, University of Kent, United Kingdom（计算学院，肯特大学，英国）；Cognitive Psychology Unit, Institute of Psychology, Leiden, the Netherlands（认知心理学单元，心理学研究所，莱顿，荷兰）
What makes a language easy to deep-learn? Deep neural networks and humans similarly benefit from compositional structure
University of Southern Denmark（南丹麦大学）；Max Planck Institute for Psycholinguistics（马克斯·普朗克心理语言学研究所）；Tel Aviv University（特拉维夫大学）；University of Glasgow（格拉斯哥大学）
Cultural Biases of Large Language Models and Humans in Historical Interpretation
Research & Development Department of Information Security and Communication Technology（信息安全和通信技术研发部）；Maggioli SpA（Maggioli股份公司）；Norwegian University of Science and Technology - NTNU（挪威科技大学）
Quantifier Scope Interpretation in Language Learners and LLMs
Department of English, Purdue University（英语系，普渡大学）；Department of Linguistics, Purdue University（语言学系，普渡大学）；School of Languages and Cultures, Purdue University（语言与文化学院，普渡大学）
Human-like fleeting memory improves language learning but impairs reading time prediction in transformer language models
University of Amsterdam, Amsterdam Brain and Cognition（阿姆斯特丹大学，阿姆斯特丹脑与认知中心）；Vrije Universiteit Amsterdam, Department of Informatics（阿姆斯特丹自由大学，信息学院）；Max Planck Institute for Psycholinguistics（马克斯·普朗克心理学语言学研究所）
False perspectives on human language: why statistics needs linguistics
University School for Advanced Studies IUSS Pavia（帕维亚高等研究院大学）；Ecole Polytechnique Federale de Lausanne（洛桑联邦理工学院）；University of Geneva（日内瓦大学）；Yale University（耶鲁大学）
A fine-grained comparison of pragmatic language understanding in humans and language models
Massachusetts Institute of Technology（麻省理工学院）；Sarah Lawrence College（莎拉·劳伦斯学院）；Carleton University（卡尔顿大学）；McGovern Institute for Brain Research, Massachusetts Institute of Technology（麻省理工学院麦戈文脑科学研究所）
Statistical patterns of word frequency suggesting the probabilistic nature of human languages
Beijing Language and Culture University（北京语言大学）；Anhui Jianzhu University（安徽建筑大学）；Zhejiang University（浙江大学）；Guangdong University of Foreign Studies（广东外语外贸大学）
When the LM misunderstood the human chuckled: Analyzing garden path effects in humans and language models
Blavatnik School of Computer Science, Tel Aviv University（特拉维夫大学布拉瓦尼克计算机科学学院）；Department of Linguistics, Tel Aviv University（特拉维夫大学语言学系）；Sagol School of Neuroscience, Tel Aviv University（特拉维夫大学萨戈尔神经科学学院）
Parallels of human language in the behavior of bottlenose dolphins
Universitat Politècnica de Catalunya（加泰罗尼亚理工大学）；University of Aberdeen（阿伯丁大学）；Technical University of Denmark（丹麦技术大学）；University of California, Davis（加州大学戴维斯分校）
