28 papers · ranked by Valyu relevance
Muhammad Raees, Inge Meijerink, Ioanna Lykourentzou, Vassilis-Javed Khan + 1 more
Trends in Human-AI Interaction Authors: ['Muhammad Raees' 'Inge Meijerink' 'Ioanna Lykourentzou' 'Vassilis-Javed Khan' 'Konstantinos Papagelis'] AI systems are increasingly being adopted across various domains and application areas. With this surge, there is a growing research focus and societal concern for actively…
Xingyu Liu, Haijun Xia, Xiang Chen
We envision the concept of Thoughtful AI, a new human–AI interaction paradigm in which the AI behaves as a continuously thinking entity. Unlike conventional AI systems that operate on a turn-based, input-output model, Thoughtful AI autonomously generates, iterates, and communicates its intermediate thought process…
Mark Steyvers, Aakriti Kumar
Artificial intelligence (AI) has the potential to improve human decision-making by providing decision recommendations and problem-relevant information to assist human decision-makers. However, the full realization of the potential of human-AI collaboration continues to face several challenges. First, the conditions…
Zhuoyue Lyu, Jiannan Li, Bryan Wang
—Artificial Intelligence (AI), especially Neural Networks (NNs), has become increasingly popular. However, people usually treat AI as a tool, focusing on improving outcome, accuracy, and performance while paying less attention to the representation of AI itself. We present AIive, an interactive visualization of AI in…
Giovanni Pezzulo, Thomas Parr, Karl J Friston
This article explores the training of embodied AI systems and robots through engagement with physical and social environments, drawing parallels with living organisms. We examine key challenges in developing embodied AI systems that learn through prediction, interaction and modification of their environments and…
Ranjay Krishna, Donsuk Lee, Li Fei-Fei, Michael S. Bernstein
Title: Significance Humans have long demonstrated an ability to learn from interactions with others. However, artificial intelligence (AI) agents learn in social isolation. To create intelligent systems that understand more than a fixed slice of the world, our article formalizes socially situated AI-a framework that…
Nate Breznau, Hung H.V. Nguyen
General overview of artificial intelligence (AI) designed for academic students, workers, researchers, and teachers. A less technical introduction for those not familiar with computer science. It focuses primarily on generative AI (Gen AI), as this is the tool rapidly transforming every aspect of academic work. This…
Jacqueline Beinecke, Anna Saranti, Alessa Angerschmid, Bastian Pfeifer + 3 more
Lack of trust in artificial intelligence (AI) models in medicine is still the key blockage for the use of AI in clinical decision support systems (CDSS). Although AI models are already performing excellently in systems medicine, their black-box nature entails that patient-specific decisions are incomprehensible for the…
Carolin Wienrich, Marc Erich Latoschik
Artificial Intelligence (AI) covers a broad spectrum of computational problems and use cases. Many of those implicate profound and sometimes intricate questions of how humans interact or should interact with AIs. Moreover, many users or future users do have abstract ideas of what AI is, significantly depending on the…
Xiangui Bu, Wenqi Wang, Xuesong Ji, Yanjun Huang + 1 more
Objective Apart from progress in productivity, the rise of artificial intelligence (AI) technologies has increased requirements for talent cultivation in colleges and universities. Despite the rapid integration of artificial intelligence in higher education, the mechanisms through which AI literacy influences students'…
Mustafa Demir, Sean M. Leahy, Punya Mishra, Chun Kit Chen + 1 more
Artificial Intelligence (AI) can be easily integrated into virtual education to drive adaptive instruction and real-time constructive feedback to students, offering a possible conduit for fostering discovery curiosity in learners. This study examines and characterizes Human-AI-Teaming (HAT) coordination dynamics to…
Catalina Gómez, Sue Min Cho, Shichang Ke, Chien‐Ming Huang + 1 more
'Mathias Unberath'] Leveraging Artificial Intelligence (AI) in decision support systems has disproportionately focused on technological advancements, often overlooking the alignment between algorithmic outputs and human expectations. A human-centered perspective attempts to alleviate this concern by designing AI…
Virginia Gonzalez, Tristan Yang, Sebastian Bassi
The General Feature Format (GFF) is widely used to represent genomic annotations, but its hierarchical, multi-attribute structure makes manual querying and analysis challenging. Existing libraries such as gffutils provide programmatic interfaces, yet they require coding proficiency. gffutilsAI is a novel AI-powered…
Wei Xu
Recently, much progress has been made in artificial intelligence (AI) and machine-learning (ML); such progress has also enabled human-computer interaction (HCI) and user experience (UX) professionals to deliver solutions with better UX (Lu et al., 2022; Yang et al., 2018; Kuniavsky et al., 2017). The use of AI/ML…
Nicholas Novelli, Shannon Proksch
Artificial Intelligence has shown paradigmatic success in defeating world champions in strategy games. However, the same programming tactics are not a reasonable approach to creative and ostensibly emotional artistic endeavors such as music composition. Here we review key examples of current creative music generating…
Le Cong, David Smerkous, Xiaotong Wang, Di Yin + 29 more
Modern science advances fastest when thought meets action. LabOS represents the first AI co-scientist that unites computational reasoning with physical experimentation through multimodal perception, self-evolving agents, and XR-enabled, embodied human-AI collaboration. To empower agentic AI with embodied intelligence…
Hsuan-Han Chiu, Ashley Varghese, Kunming Shao, Yen-Chun Lu + 5 more
Single-cell RNA sequencing (scRNA-seq) has transformed biomedical research by enabling transcriptomic analysis at single-cell resolution. Yet, existing computational approaches remain primarily data-driven and lack the ability to integrate research context, limiting their interpretability and impact on hypothesis…
Jungwoo Ryoo, Kurt Winkelmann, Stephanie E. August, Audrey Tsaima
The role of artificial intelligence in US education is expanding. As education moves toward providing customized learning paths, the use of artificial intelligence (AI) and machine learning (ML) algorithms in learning systems increases. This can be viewed as growing metaphorical exoskeletons for instructors, enabling…
Authors not listed
Agentic artificial intelligence (AI) is poised to redefine how science is conducted, automating not just data analysis but the entire research lifecycle, from hypothesis generation to validation. Yet most current AI agents remain domain-bound, tailored to specific applications such as materials synthesis or quantum…
Authors not listed
The value of generative artificial intelligence (AI) for teaching and learning is currently hotly debated. Concerns regarding the accuracy of information produced by generative AI as well as student over-reliance on this tool coexist with excitement about tailored opportunities that AI may provide for educational…
Christelle Langley, Bogdan-Ionuţ Cîrstea, Fabio Cuzzolin, Barbara Jacquelyn Sahakian
'Barbara Jacquelyn Sahakian'] Humans can think flexibly and creatively, whereas current artificial intelligence (AI) systems may fail to recognize instances where they would need to change the solution approach, when the current approach is unsuccessful. For a long time, AI systems used to be incapable of matching…
Iiris Sundin, Alexey Voronov, Haoping Xiao, Kostas Papadopoulos + 5 more
A de novo molecular design workflow can be used together with technologies such as reinforcement learning to navigate the chemical space. A bottleneck in the workflow that remains to be solved is how to integrate human feedback in the exploration of the chemical space to optimize molecules. A human drug designer still…
Muhammad Zain Butt, Rana Sheraz Ahmad, Eman Fatima, Muhammad Tahir ul Qamar
The application of Large Language Models (LLMs) for generating data visualizations through natural language interaction represents a promising advance in AI-assisted scientific analysis. However, existing LLM-based tools largely emphasize graph generation, while research workflows require not only visualization but…
Authors not listed
As the utilization of artificial intelligence (AI) and generative AI (GenAI) is expanding in the educational field, presenting significant implications for STEM disciplines, it is bringing opportunities to enhance how chemistry and chemical engineering are taught and learned. This perspective critically explores the…
Kevin Kawchak
Large Multimodal Models (LMMs) possess the ability to analyze chemical spectra of an organic compound using state of the art conversational AI. These outputs can then be chained together and introduced as a text input for other LLMs or LMMs to predict the compound name. Here, a challenging 15 carbon molecule problem…
Yuanqi Du, Chenru Duan, Andres Bran, Anna Sotnikova + 5 more
Large language models (LLMs) have demonstrated outstanding capabilities in general problem-solving and been shown to improve productivity in certain domains. Thanks to their flexibility, recent work has leveraged them for diverse scientific applications, ranging from predictive modeling, scientific Q&A, and even as…
Gerard R. Lazo, Devadharshini Ayyappan, Parva K. Sharma, Vijay K. Tiwari
Provided here is a study of large language models (LLMs) and retrieval augmented generation (RAG) frameworks in air-gapped environments for genome research on small grain crops. We developed two main applications: (1) a RAG-based system for contextual analysis of scientific literature, collecting over 5,000 PDFs on…
Authors not listed
Artificial intelligence (AI) is reshaping scientific research by accelerating discovery and enabling the analysis of complex data that traditional methods struggle to handle. This review examines over 310,000 journal articles and patents from the CAS Content Collection (2015–2025), with a focus on, biomedical research…