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2021 Student Research Workshop, SRW 2021 at the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, ACL-IJCNLP 2021

作者： Wang, Weiyue Yang, Zijian Gao, Yingbo Ney, Hermann Human Language Technology and Pattern Recognition Group Computer Science Department RWTH Aachen University Germany

ISBN: (纸本)9781954085558

The neural hidden Markov model has been proposed as an alternative to attention mechanism in machine translation with recurrent neural networks. However, since the introduction of the transformer models, its performance has been surpassed. This work proposes to introduce the concept of the hidden Markov model to the transformer architecture, which outperforms the transformer baseline. Interestingly, we find that the zero-order model already provides promising performance, giving it an edge compared to a model with first-order dependency, which performs similarly but is significantly slower in training and decoding. © 2021 Association for Computational Linguistics.

关键词： Hidden Markov models

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Task-Agnostic Learning to Accomplish New Tasks

arXiv

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arXiv 2022年

作者： Zhang, Xianqi Wang, Xingtao Liu, Xu Wang, Wenrui Fan, Xiaopeng Zhao, Debin Research Center of Intelligent Interface and Human Computer Interaction the Department of Computer Science and Technology Harbin Institute of Technology Harbin150001 China

Reinforcement Learning (RL) and Imitation Learning (IL) have made great progress in robotic control in recent years. However, these methods show obvious deterioration for new tasks that need to be completed through new combinations of actions. RL methods heavily rely on reward functions that cannot generalize well for new tasks, while IL methods are limited by expert demonstrations which do not cover new tasks. In contrast, humans can easily complete these tasks with the fragmented knowledge learned from task-agnostic experience. Inspired by this observation, this paper proposes a task-agnostic learning method (TAL for short) that can learn fragmented knowledge from task-agnostic data to accomplish new tasks. TAL consists of four stages. First, the task-agnostic exploration is performed to collect data from interactions with the environment. The collected data is organized via a knowledge graph. Compared with the previous sequential structure, the knowledge graph representation is more compact and fits better for environment exploration. Second, an action feature extractor is proposed and trained using the collected knowledge graph data for task-agnostic fragmented knowledge learning. Third, a candidate action generator is designed, which applies the action feature extractor on a new task to generate multiple candidate action sets. Finally, an action proposal is designed to produce the probabilities for actions in a new task according to the environmental information. The probabilities are then used to select actions to be executed from multiple candidate action sets to form the plan. Experiments on a virtual indoor scene show that the proposed method outperforms the state-of-the-art offline RL method: CQL by 35.28% and the IL method: BC by 22.22%. Copyright © 2022, The Authors. All rights reserved.

关键词： Reinforcement learning

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From Reader to Experiencer: Design and Evaluation of an Interactive Vr Story for Promoting the Situation Awareness of Public Health Threats

SSRN

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SSRN 2023年

作者： Zhu, Qian Yuan, Linping Xu, Zian Yang, Leni Xia, Meng Wang, Zhuo Liang, Hai-Ning Ma, Xiaojuan The Hong Kong University of Science and Technology Department of Computer Science and Engineering Hong Kong Carnegie Mellon University Human-Computer Interaction Institute PittsburghPA United States Xi’an Jiaotong Liverpool University Department of Computing Suzhou China

Informing people of health threats is crucial as they may lack situation awareness (SA) of risky situations when they do not have personal experiences or lessons learned from dangerous encounters. In this work, we explored the potential of using an interactive VR (Virtual Reality) story to raise people's SA of health risks. We first worked with seven participants to iteratively design the immersive story and summarized five design considerations. Then, we implemented the VR story with five design features referring to the design considerations. Using a between-subjects study (N=62), we evaluated the effects of the VR story on raising SA and investigated the role of each design feature. Our results show that the VR story can promote SA by enhancing people's connection to risky situations. Design features such as immersive visualizations, multiple perspectives, and embodied interactions contribute to this connection. Drawing on qualitative and quantitative findings, we discuss the implications of designing VR stories for promoting public health. © 2023, The Authors. All rights reserved.

关键词： Virtual reality

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Camera-Based HRV Prediction for Remote Learning Environments 10

Camera-Based HRV Prediction for Remote Learning Environments

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10th IEEE Smart World Congress, SWC 2024

作者： Wang, Kegang Wei, Yantao Tang, Jiankai Wang, Yuntao Li, Zhe Tong, Mingwen Gao, Jie Ma, Yujian Zhao, Zhongjin Central China Normal University Wuhan430079 China National Key Laboratory of Human Factors Engineering Beijing100094 China Tsinghua University Department of Computer Science and Technology Beijing100084 China Ant Group Beijing100000 China East China Normal University Shanghai200241 China

ISBN: (纸本)9798331520861

In recent years, the widespread use of online facial videos has brought increasing attention to remote photoplethys-mography (rPPG) in affective computing. Recovering blood volume pulse (BVP) signals from facial videos is a complex task, involving multiple stages of preprocessing, image analysis, and postprocessing to accurately reconstruct waveforms. Not only is the heart rate metric utilized for affective computing, but the heart rate variability (HRV) metric is even more significant. The challenge in obtaining HRV indices through rPPG lies in the necessity for algorithms to precisely predict the BVP peak positions. In this paper, we collected the Remote Learning Affect and Physiology (RLAP) dataset, which includes over 32 hours of highly synchronized video and labels from 58 subjects. This is a public dataset whose BVP labels have been meticulously designed to better suit the training of HRV models. Using the RLAP dataset, we trained a new model called Seq-rPPG, it is a model based on one-dimensional convolution, and experimental results reveal that this structure is more suitable for handling HRV tasks, which outperformed all other baselines in HRV performance and also demonstrated significant advantages in computational efficiency. The RLAP dataset is open source: https://***/KegangWangCCNU/RLAP-dataset © 2024 IEEE.

关键词： Heart

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Exploring Trade-Offs for Online Mental Health Matching: Agent-Based Modeling Study

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JMIR Formative Research 2024年 8卷 e58241页

作者： Liu, Yuhan Fang, Anna Moriarty, Glen Firman, Cristopher Kraut, Robert E. Zhu, Haiyi Department of Computer Science Princeton University Princeton NJ United States Human-Computer Interaction Institute Carnegie Mellon University Pittsburgh PA United States 7 Cups Wilmington DE United States

Background: Online mental health communities (OMHCs) are an effective and accessible channel to give and receive social support for individuals with mental and emotional issues. However, a key challenge on these platforms is finding suitable partners to interact with given that mechanisms to match users are currently underdeveloped or highly naive. Objective: In this study, we collaborated with one of the world’s largest OMHCs;our contribution is to show the application of agent-based modeling for the design of online community matching algorithms. We developed an agent-based simulation framework and showcased how it can uncover trade-offs in different matching algorithms between people seeking support and volunteer counselors. Methods: We used a comprehensive data set spanning January 2020 to April 2022 to create a simulation framework based on agent-based modeling that replicates the current matching mechanisms of our research site. After validating the accuracy of this simulated replication, we used this simulation framework as a “sandbox” to test different matching algorithms based on the deferred acceptance algorithm. We compared trade-offs among these different matching algorithms based on various metrics of interest, such as chat ratings and matching success rates. Results: Our study suggests that various tensions emerge through different algorithmic choices for these communities. For example, our simulation uncovered that increased waiting time for support seekers was an inherent consequence on these sites when intelligent matching was used to find more suitable matches. Our simulation also verified some intuitive effects, such as that the greatest number of support seeker–counselor matches occurred using a “first come, first served” protocol, whereas relatively fewer matches occurred using a “last come, first served” protocol. We also discuss practical findings regarding matching for vulnerable versus overall populations. Results by demographic group reveal

关键词： agent-based modeling algorithmic matching mental health online communities social computing

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BEWARE-22: Bringing together researchers to address the logical, ethical, and epistemological challenges of AI 1

BEWARE-22: Bringing together researchers to address the logi...

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1st Workshop on Bias, Ethical AI, Explainability and the Role of Logic and Logic Programming, BEWARE 2022

作者： Boella, Guido D’Asaro, Fabio Aurelio Dyoub, Abeer Primiero, Giuseppe Department of Computer Science University of Turin Turin Italy Ethos Group Department of Human Sciences University of Verona Verona Italy DISIM University of L’Aquila L’Aquila Italy LUCI Group Department of Philosophy University of Milan Milan Italy

The BEWARE-22 workshop, held on December 2, 2022 in Udine, Italy, focused on emerging ethical aspects of artificial intelligence, with a particular emphasis on bias, risk, explainability, and the role of logic and logic programming. The invited speaker, Francesca Alessandra Lisi, gave a talk on "Ethics & Gender for a Responsible Research and Innovation in AI," exploring the intersection of ethics and gender in the context of responsible research and innovation in artificial intelligence. The workshop program consisted of three sessions: "Logic for AI", "Technical Approaches to XAI", and "Conceptual Views," which this short preface aims to describe. In total, 13 papers were accepted for the workshop, with 5 accepted as long papers and 8 as short papers. The proceedings include 12 papers out of the 13 from the workshop, plus an invited abstract, and will hopefully serve as a valuable resource for researchers and practitioners working on the ethical aspects of AI, inspiring further discussions and collaborations in this critical area of research. © 2022 Copyright for this paper by its authors.

关键词： Logic programming

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In-the-loop or on-the-loop? interactional arrangements to support team coordination with a planning agent

In-the-loop or on-the-loop? Interactional arrangements to su...

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作者： Fischer, Joel E. Greenhalgh, Chris Jiang, Wenchao Ramchurn, Sarvapali D. Wu, Feng Rodden, Tom The Mixed Reality Laboratory School of Computer Science University of Nottingham Nottingham United Kingdom Agents Interaction and Complexity Group Department of Electronics and Computer Science University of Southampton Southampton United Kingdom School of Computer Science and Technology University of Science and Technology of China Hefei China

In this paper, we present the study of interactional arrangements that support the collaboration of headquarters (HQ), field responders, and a computational planning agent in a time-critical task setting created by a mixed-reality game. interactional arrangements define the extent to which control is distributed between the collaborative parties. We provide 2 field trials, one to study an "on-the-loop" arrangement in which HQ monitors and intervenes in agent instructions to field players on demand and the other, to study a version that places HQ more tightly "in-the-loop." The studies provide an understanding of the sociotechnical collaboration between players and the agent in these interactional arrangements by conducting interaction analysis of video recordings and game log data. The first field trial focuses on the collaboration of field responders with the planning agent. Findings highlight how players negotiate the agent guidance within the social interaction of the collocated teams. The second field trial focuses on the collaboration between the automated planning agent and the HQ. We find that the human coordinator and the agent can successfully work together in most cases, with human coordinators inspecting and "correcting" the agent-proposed plans. Through this field trial-driven development process, we generalise interaction design implications of automated planning agents around the themes of supporting common ground and mixed-initiative planning. © 2017 The Authors. Concurrency and Computation: Practice and Experience Published by John Wiley & Sons, Ltd.

关键词： Mixed reality

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Cruising Queer HCI on the DL: A Literature Review of LGBTQ+ People in HCI 24

Cruising Queer HCI on the DL: A Literature Review of LGBTQ+ ...

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Proceedings of the CHI Conference on human Factors in Computing Systems

作者： Jordan Taylor Ellen Simpson Anh-Ton Tran Jed R. Brubaker Sarah E Fox Haiyi Zhu Human-Computer Interaction Institute Carnegie Mellon University United States Department of Information Science University of Colorado United States Georgia Institute of Technology United States Department of Information Science University of Colorado Boulder United States

ISBN: (纸本)9798400703300

LGBTQ+ people have received increased attention in HCI research, paralleling a greater emphasis on social justice in recent years. However, there has not been a systematic review of how LGBTQ+ people are researched or discussed in HCI. In this work, we review all research mentioning LGBTQ+ people across the HCI venues of CHI, CSCW, DIS, and TOCHI. Since 2014, we find a linear growth in the number of papers substantially about LGBTQ+ people and an exponential increase in the number of mentions. Research about LGBTQ+ people tends to center experiences of being politicized, outside the norm, stigmatized, or highly vulnerable. LGBTQ+ people are typically mentioned as a marginalized group or an area of future research. We identify gaps and opportunities for (1) research about and (2) the discussion of LGBTQ+ in HCI and provide a dataset to facilitate future Queer HCI research.

关键词： LGBTQ+ people Literature Review Marginalized Communities Queer HCI Queer People

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Investigating the Role of Metaphors in human-AI Conversation and Engagement

Investigating the Role of Metaphors in Human-AI Conversation...

引用

IEEE International Conference on Data Mining Workshops (ICDM Workshops)

作者： Pragati Maheshwary Qiawen Liu Rui Mao Human-Computer Interaction Institute Carnegie Mellon University United States Department of Psychology University of Wisconsin-Madison United States College of Computing and Data Science Nanyang Technological University Singapore

ISBN: (数字)9798331530631

ISBN: (纸本)9798331530648

Metaphorical expressions are widely used in daily communication between humans to improve the understanding of both complex and abstract concepts. However, it is unclear whether the usage of metaphorical language is helpful for enhancing the conversational engagement between humans and AI. In this work, we leverage a state-of-the-art computational metaphor processing tool to gain insights from human and ChatGPT conversations. Our quantitative analysis finds that although metaphors may enhance the quality of human-AI interactions, they do not directly lead to higher levels of conversational engagement, which is measured by the duration of the conversation. However, regression analysis shows a notable relationship between user and ChatGPT metaphor usage, suggesting that ChatGPT is adept at reflecting the linguistic style of users, especially in terms of metaphorical language. Additional topic modeling and concept mapping analyses further explored the patterns of metaphorical language across various engagement levels and topics in user and ChatGPT messages.

关键词： Analytical models Conferences Oral communication Linguistics Chatbots Regression analysis Data mining Artificial intelligence

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Immersive Neural Graphics Primitives

arXiv

引用

arXiv 2022年

作者： Li, Ke Rolff, Tim Schmidt, Susanne Bacher, Reinhard Frintrop, Simone Leemans, Wim Steinicke, Frank Human-Computer Interaction Group Department of Informatics Universität Hamburg Germany Computer Vision Group Department of Informatics Universität Hamburg Germany Deutsches Elektronen-Synchrotron DESY Germany

Neural radiance field (NeRF), in particular its extension by instant neural graphics primitives, is a novel rendering method for view synthesis that uses real-world images to build photo-realistic immersive virtual scenes. Despite its potential, research on the combination of NeRF and virtual reality (VR) remains sparse. Currently, there is no integration into typical VR systems available, and the performance and suitability of NeRF implementations for VR have not been evaluated, for instance, for different scene complexities or screen resolutions. In this paper, we present and evaluate a NeRF-based framework that is capable of rendering scenes in immersive VR allowing users to freely move their heads to explore complex real-world scenes. We evaluate our framework by benchmarking three different NeRF scenes concerning their rendering performance at different scene complexities and resolutions. Utilizing super-resolution, our approach can yield a frame rate of 30 frames per second with a resolution of 1280×720 pixels per eye. We discuss potential applications of our framework and provide an open source implementation online.1 Copyright © 2022, The Authors. All rights reserved.

关键词： Virtual reality

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