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Mixed Reality (MR) presents novel opportunities to investigate how individuals perceive themselves and others during shared, augmented experiences within a common physical environment. Previous research has demonstrated that users can…

Human-Computer Interaction · Computer Science 2025-09-15 Yuan He , Brendan Rooney , Rachel McDonnell

Family learning takes place in everyday routines where children and caregivers read, practice, and develop new skills together. Although AI is increasingly present in learning environments, most systems remain child-centered and overlook…

Human-Computer Interaction · Computer Science 2025-10-29 Yao Li , Jingyi Xie , Ya-Fang Lin , He Zhang , Ge Wang , Gaojian Huang , Rui Yu , Si Chen

Humans face countless scenarios that require reasoning and judgment in daily life. However, existing large language model training methods primarily allow models to learn from existing textual content or solve predetermined problems,…

Artificial Intelligence · Computer Science 2026-01-27 Yin Cai , Zhouhong Gu , Juntao Zhang , Ping Chen

In this position paper, we discuss the potential for leveraging LLMs as interactive research tools to facilitate collaboration between human coders and AI to effectively annotate online risk data at scale. Collaborative human-AI labeling is…

Human-Computer Interaction · Computer Science 2024-04-12 Jinkyung Park , Pamela Wisniewski , Vivek Singh

Mixed methods research integrates quantitative and qualitative data but faces challenges in aligning their distinct structures, particularly in examining measurement characteristics and individual response patterns. Advances in large…

Computation and Language · Computer Science 2025-05-29 Jihong Zhang , Xinya Liang , Anqi Deng , Nicole Bonge , Lin Tan , Ling Zhang , Nicole Zarrett

Recent progress in large language model (LLM) technology has significantly enhanced the interaction experience between humans and voice assistants (VAs). This project aims to explore a user's continuous interaction with LLM-based VA…

Human-Computer Interaction · Computer Science 2024-09-04 Szeyi Chan , Shihan Fu , Jiachen Li , Bingsheng Yao , Smit Desai , Mirjana Prpa , Dakuo Wang

Hidden Markov Models with an underlying Mixture of Gaussian structure have proven effective in learning Human-Robot Interactions from demonstrations for various interactive tasks via Gaussian Mixture Regression. However, a mismatch occurs…

Recently, collaborative robots have begun to train humans to achieve complex tasks, and the mutual information exchange between them can lead to successful robot-human collaborations. In this paper we demonstrate the application and…

Robotics · Computer Science 2019-09-24 Sayanti Roy , Emily Kieson , Charles Abramson , Christopher Crick

Mobile video calls are widely used to share information about real-world objects and environments with remote collaborators. While these calls provide valuable visual context in real time, the experience of interacting with people and…

This paper presents a hopeful perspective on the potentially dramatic impacts of Large Language Models on how we children learn and how they will expect to interact with technology. We review the effects of LLMs on education so far, and…

Human-Computer Interaction · Computer Science 2025-04-21 Russell Beale

We investigated the challenges of mitigating response delays in free-form conversations with virtual agents powered by Large Language Models (LLMs) within Virtual Reality (VR). For this, we used conversational fillers, such as gestures and…

The development of AI agents based on large, open-domain language models (LLMs) has paved the way for the development of general-purpose AI assistants that can support human in tasks such as writing, coding, graphic design, and scientific…

Artificial Intelligence · Computer Science 2025-06-03 Mustafa Mert Çelikok , Saptarashmi Bandyopadhyay , Robert Loftin

Existing multi-agent learning approaches have developed interactive training environments to explicitly promote collaboration among multiple Large Language Models (LLMs), thereby constructing stronger multi-agent systems (MAS). However,…

Artificial Intelligence · Computer Science 2026-04-14 Hehai Lin , Shilei Cao , Sudong Wang , Haotian Wu , Minzhi Li , Linyi Yang , Juepeng Zheng , Chengwei Qin

With the recent development of natural language generation models - termed as large language models (LLMs) - a potential use case has opened up to improve the way that humans interact with robot assistants. These LLMs should be able to…

Multiagent Systems · Computer Science 2024-11-27 Mitchell Rosser , Marc. G Carmichael

The role of large language models (LLMs) in education is increasing, yet little attention has been paid to whether LLM-generated text resembles child language. This study evaluates how LLMs replicate child-like language by comparing…

Computation and Language · Computer Science 2025-08-20 Hanna Woloszyn , Benjamin Gagl

The ability to combine linguistic guidance from others with direct experience is central to human development, enabling safe and rapid learning in new environments. How do people integrate these two sources of knowledge, and how might AI…

Artificial Intelligence · Computer Science 2026-02-19 Cédric Colas , Tracey Mills , Ben Prystawski , Michael Henry Tessler , Noah Goodman , Jacob Andreas , Joshua Tenenbaum

Virtual and augmented reality communication platforms are seen as promising modalities for next-generation remote face-to-face interactions. Our study attempts to explore non-verbal communication features in relation to their conversation…

Human-Computer Interaction · Computer Science 2019-04-10 Mohammad Keshavarzi , Michael Wu , Michael N. Chin , Robert N. Chin , Allen Y. Yang

Artificial Intelligence (AI) chatbots powered by a large language model (LLM) are entering young children's learning and play, yet little is known about how young children construe these agents or how such construals relate to engagement.…

Human-Computer Interaction · Computer Science 2025-12-04 Pilyoung Kim , Jenna H. Chin , Yun Xie , Nolan Brady , Tom Yeh , Sujin Yang

Exploiting relationships between visual regions and question words have achieved great success in learning multi-modality features for Visual Question Answering (VQA). However, we argue that existing methods mostly model relations between…

Computer Vision and Pattern Recognition · Computer Science 2019-08-14 Peng Gao , Haoxuan You , Zhanpeng Zhang , Xiaogang Wang , Hongsheng Li

Artificial intelligence (AI) has become tightly integrated into modern technology, yet existing exploratory visualizations for explainable AI (XAI) are primarily designed for users with technical expertise. This leaves everyday users, who…

Human-Computer Interaction · Computer Science 2024-10-08 Yuzhe You , Jian Zhao