It is found that current frontier models can improve on the given baselines, usually by finding better hyperparameters, but do not generate novel hypotheses, algorithms, architectures, or substantial improvements.
It is found that participation in shared artistic experience was associated with lower levels of depression and anxiety, and group arts are an effective intervention for addressing depression and anxiety among older adults.
This study highlights several challenges, including adapting models for task-specific methodology, accounting for environmental factors influencing aesthetics, the lack of substantial datasets with appropriate labels, imbalanced data, preserving image aspect ratio and integrity in network architecture design, and the need for explainable AI to understand the causative factors behind aesthetic judgments.
This book discusses Peter Maximoff's childhood, sibling Bonding, Star Trek TOS References, and more about Peter and Erik Lehnsherr.
A vigilant approach is recommended towards the use of AI-generated imagery in medical education at present, underscoring the imperative for thorough validation and the importance of collaboration across disciplines.
This paper investigates the emerging use of 3D generative artificial intelligence models, particularly Gaussian Splatting (GS), for creating immersive virtual environments in architectural heritage contexts and assesses how GS can transform historical sites into immersive experiences by combining photorealism with artistic expression.
Results showed that the ChatGPT-driven system provided personalised responses and immediate feedback, significantly enhancing student achievement, motivation, and self-efficacy, underscore the feasibility of integrating GenAI into design and art education and offer valuable insights for educators and curriculum developers.
This paper unravels the potential of sketches for diffusion models, addressing the deceptive promise of direct sketch control in generative AI, and introduces an abstraction-aware framework, using a sketch adapter, adaptive time-step sampling, and discriminative guidance from a pre-trained fine-grained sketch-based image retrieval model, working synergistically to reinforce fine-grained sketch-photo association.
This work introduces a new bipedal robot, designed with a focus on character-driven mechanical features, and presents a reinforcement learning-based control architecture to robustly execute artistic motions conditioned on command signals.
The revised RG-MBI checklist has a total of 12-items that pertain to eight different components of MBI interventions including name, theory/scientific rationale, content, interventionist, individual/group, setting, delivery schedule, and treatment fidelity and is recommended to accelerate and improve the scientific rigor of MBI research.
The results indicate that the AI-generated virtual instructor significantly enhances affective engagement and has a comparably beneficial effect on academic performance and cognitive load compared to the human instructor, and the conversational teaching style considerably improves students’ academic performance, reduces cognitive load, and fosters engagement.
The findings suggest that GANs with spectrograms and RNNs with MIDI data are particularly effective for generating multi-track music, while autoregressive models like MusicGen and transformer models demonstrate superior performance in capturing long-term dependencies in music generation.
Results highlighted the effectiveness of the GAI-powered ABL learning system in enhancing students’ historical knowledge and motivation and reducing cognitive load.
This work introduces a framework to evaluate cultural competence of T2I models along two crucial dimensions: cultural awareness and cultural diversity, and presents a scalable approach using a combination of structured knowledge bases and large language models to build a large dataset of cultural artifacts to enable this evaluation.
The Emotion questionnaire validates the impact of virtual museum tours on emotional states, including positive, negative, and boredom, compared to traditional methods, and suggests that VR can revolutionize heritage experiences by deepening visitor understanding.
RoomDreaming empowers owners and designers to rapidly and efficiently iterate through a broad range of AI-generated, photo-realistic design alternatives, each uniquely tailored to fit actual space layouts and individual design preferences.
Science × art collaborations can effectively convey scientific insights to a wide audience and hold potential as valuable tools for understanding biodiversity.
The results of this study concluded that there are various aesthetic values in the use of Arabic calligraphy that can be used to create contemporary furniture designs using artificial intelligence techniques to preserve its sustainability.
A comprehensive review of generative AI’s evolution, significance, and applications, including the foundational architectures such as generative adversarial networks, variational autoencoders, autoregressive models, flow‐based models, and diffusion models, are provided.
The study concluded that AR technology significantly improved student performance, flow state, and reduced cognitive load, highlighting its potential to enhance visual arts education.
This review aims to investigate the opportunities that soundscape design and advanced sonic interactions in virtual and augmented environments can bring to cultural heritage sites and museums in terms of presence, emotional content, and cultural dissemination.
An in-depth examination of the intersection of sustainable technologies, pedagogical theories, and assessment methods within visual art education indicates that the use of technology in art education is still in its nascent stages, yet it holds significant potential for sustainable development.
This paper introduces Drawing of THINGS, a novel dataset of 28,627 human drawings of 1854 diverse object concepts sampled systematically from concrete picturable and nameable nouns in the American English language, mirroring the structure of the THINGS image database.
ART3mis is a general-purpose, user-friendly, interactive textual annotation tool for 3D objects that can handle detailed 3D cultural objects in real-time and store textual annotations for multiple complex regions in JSON data format.
An interactive application called SMKExplore is presented, which allows users to explore a museum’s digital collection of paintings by browsing through objects detected in the images, as a novel form of open-ended exploration.
The finding indicates that the current conceptualization of ML as a design material needs to reframe the ML process as design elements, instead of technical details, and offers reflections on commonly held assumptions in HCI about ML uncertainty, dependability, and explainability.
A novel ontology named the Reactive Digital Twin Ontology is described, in which sensors, activators, and the decision processes are also semantically described, turning the previous synchronic approach to cultural heritage documentation into a diachronic one.
An 11-week diary study with 20 amateur filmmakers of 15 AI-infused films, investigating the emerging space of generative cinema as a critical technical practice and discussing how four critical approaches to negotiating AI use in filmmaking suggest the potential for underground filmmaking cultures to form around AI.
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