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Related papers: The Cultural Transmission of Tacit Knowledge

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A defining feature of human culture is that knowledge and technology continually improve over time. Such cumulative cultural evolution (CCE) probably depends far more heavily on how reliably information is preserved than on how efficiently…

Physics and Society · Physics 2020-10-07 Marcel Montrey , Thomas R. Shultz

How do people acquire rich, flexible knowledge about their environment from others despite limited cognitive capacity? Humans are often thought to rely on computationally costly mentalizing, such as inferring others' beliefs. In contrast,…

Artificial Intelligence · Computer Science 2026-05-11 Silja Keßler , Miriam Bautista-Salinero , Claudio Tennie , Charley M. Wu

Despite the growing demand for professional graphic design knowledge, the tacit nature of design inhibits knowledge sharing. However, there is a limited understanding on the characteristics and instances of tacit knowledge in graphic…

Human-Computer Interaction · Computer Science 2024-03-12 Kihoon Son , DaEun Choi , Tae Soo Kim , Juho Kim

Motivated by concerns that AI-driven entry-level automation may deprive new generations of valuable work experience, this paper studies how technological change affects the intergenerational transmission of tacit knowledge -- practical,…

General Economics · Economics 2026-04-03 Enrique Ide

Imitation learning aims to extract knowledge from human experts' demonstrations or artificially created agents in order to replicate their behaviors. Its success has been demonstrated in areas such as video games, autonomous driving,…

Machine Learning · Computer Science 2022-10-24 Boyuan Zheng , Sunny Verma , Jianlong Zhou , Ivor Tsang , Fang Chen

Knowledge distillation is a simple but powerful way to transfer knowledge between a teacher model to a student model. Existing work suffers from at least one of the following key limitations in terms of direction and scope of transfer which…

Machine Learning · Computer Science 2024-02-12 Michael Livanos , Ian Davidson , Stephen Wong

One of the common ways children learn is by mimicking adults. Imitation learning focuses on learning policies with suitable performance from demonstrations generated by an expert, with an unspecified performance measure, and unobserved…

Machine Learning · Computer Science 2022-08-15 Junzhe Zhang , Daniel Kumor , Elias Bareinboim

Tacit knowledge embedded in expert practice remains difficult to capture, formalise, and scale. While AI-driven educational systems have advanced personalisation, learner modelling, affective support, and self-regulated learning, they less…

Human-Computer Interaction · Computer Science 2026-05-12 Annie Yuan , Xiaohua Chen , Kalina Yacef , Judy Kay

Humans ability to transfer knowledge through teaching is one of the essential aspects for human intelligence. A human teacher can track the knowledge of students to customize the teaching on students needs. With the rise of online education…

Computers and Society · Computer Science 2022-01-19 Ghodai Abdelrahman , Qing Wang , Bernardo Pereira Nunes

Domain adaptation is crucial in many real-world applications where the distribution of the training data differs from the distribution of the test data. Previous Deep Learning-based approaches to domain adaptation need to be trained jointly…

Computation and Language · Computer Science 2017-02-08 Sebastian Ruder , Parsa Ghaffari , John G. Breslin

In computer simulation of the learning process is usually assumed that all elements of the training material are assimilated equally durable. But in practice, the knowledge, which a student uses in its operations, are remembered much…

Computers and Society · Computer Science 2013-12-20 Robert V Mayer

Many cultural traits characterizing intelligent behaviors are now thought to be transmitted through statistical learning, motivating us to study its effects on cultural evolution. We conduct a large-scale music data analysis and observe…

Physics and Society · Physics 2021-09-29 Eita Nakamura

Methods of transfer learning try to combine knowledge from several related tasks (or domains) to improve performance on a test task. Inspired by causal methodology, we relax the usual covariate shift assumption and assume that it holds true…

Machine Learning · Statistics 2018-09-25 Mateo Rojas-Carulla , Bernhard Schölkopf , Richard Turner , Jonas Peters

Despite substantial research efforts evaluating how well large language models~(LLMs) handle global cultural diversity, the mechanisms behind their cultural knowledge acquisition, particularly in multilingual settings, remain unclear. We…

Computation and Language · Computer Science 2025-06-03 Chen Zhang , Zhiyuan Liao , Yansong Feng

Cultural transmission is the domain-general social skill that allows agents to acquire and use information from each other in real-time with high fidelity and recall. In humans, it is the inheritance process that powers cumulative cultural…

This paper discusses the important process of knowledge and its management, and differences between tacit and explicit knowledge and understanding the culture as a key issue for the successful implementation of knowledge management, in…

Other Computer Science · Computer Science 2010-03-10 Mohsen Gerami

Transfer learning aims to transfer knowledge or information from a source domain to a relevant target domain. In this paper, we understand transfer learning from the perspectives of knowledge transferability and trustworthiness. This…

Machine Learning · Computer Science 2025-11-13 Jun Wu , Jingrui He

The evolution and function of imitation have always been placed within the confines of animal learning and associated with its crucial role in cultural transmission and cultural evolution. Can imitation evolve as a form of phenotypic…

Populations and Evolution · Quantitative Biology 2021-10-22 Lee Altenberg , Susanne Still , Christopher J. Watkins

Knowledge distillation addresses the problem of transferring knowledge from a teacher model to a student model. In this process, we typically have multiple types of knowledge extracted from the teacher model. The problem is to make full use…

Computation and Language · Computer Science 2023-02-02 Chenglong Wang , Yi Lu , Yongyu Mu , Yimin Hu , Tong Xiao , Jingbo Zhu

We study subliminal learning, a surprising phenomenon where language models transmit behavioral traits via semantically unrelated data. In our main experiments, a "teacher" model with some trait T (such as liking owls or being misaligned)…

Machine Learning · Computer Science 2025-07-22 Alex Cloud , Minh Le , James Chua , Jan Betley , Anna Sztyber-Betley , Jacob Hilton , Samuel Marks , Owain Evans
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