检索结果-内蒙古大学图书馆

2025 CHI Conference on Human Factors in computing Systems, CHI 2025

作者： Lim, Jared Ordoña Barkhuff, Grace Awuah, Jane Clyde, Sophie Sogani, Riya Gardner-Mccune, Christina Touretzky, David Uchidiuno, Judith Odili School of Interactive Computing Georgia Institute of Technology Atlanta GA United States Department of Computer and Information Science and Engineering University of Florida Gainesville FL United States Computer Science Department Carnegie Mellon University Pittsburgh PA United States

ISBN: (纸本)9798400713941

There are many initiatives that teach Artificial Intelligence (AI) literacy to K-12 students. Most downsize college-level instructional materials to grade-level appropriate formats, overlooking students' unique perspectives in the design of curricula. To investigate the use of educational games as a vehicle for uncovering youth's understanding of AI instruction, we co-designed games with 39 Black, Hispanic, and Asian high school girls and non-binary youth to create engaging learning materials for their peers. We conducted qualitative analyses on the designed game artifacts, student discourse, and their feedback on the efficacy of learning activities. This study highlights the benefits of co-design and learning games to uncover students' understanding and ability to apply AI concepts in game-based learning, their emergent perspectives of AI, and the prior knowledge that informs their game design choices. Our research uncovers students' AI misconceptions and informs the design of educational games and grade-level appropriate AI instruction. © 2025 Copyright held by the owner/author(s).

关键词： AI Education AI Literacy Co-design game-based learning Youth

来源：评论

学校读者我要写书评

暂无评论

ARXIVEDITS: Understanding the Human Revision Process in Scientific Writing

ARXIVEDITS: Understanding the Human Revision Process in Scie...

引用

2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022

作者： Jiang, Chao Xu, Wei Stevens, Samuel School of Interactive Computing Georgia Institute of Technology United States Department of Computer Science and Engineering Ohio State University United States

Scientific publications are the primary means to communicate research discoveries, where the writing quality is of crucial importance. However, prior work studying the human editing process in this domain mainly focused on the abstract or introduction sections, resulting in an incomplete picture. In this work, we provide a complete computational framework for studying text revision in scientific writing. We first introduce ARXIVEDITS, a new annotated corpus of 751 full papers from arXiv with gold sentence alignment across their multiple versions of revision, as well as fine-grained span-level edits and their underlying intentions for 1, 000 sentence pairs. It supports our data-driven analysis to unveil the common strategies practiced by researchers for revising their papers. To scale up the analysis, we also develop automatic methods to extract revision at document-, sentence-, and word-levels. A neural CRF sentence alignment model trained on our corpus achieves 93.8 F1, enabling the reliable matching of sentences between different versions. We formulate the edit extraction task as a span alignment problem, and our proposed method extracts more fine-grained and explainable edits, compared to the commonly used diff algorithm. An intention classifier trained on our dataset achieves 78.9 F1 on the fine-grained intent classification task. Our data and system are released at ***/arxivedits. © 2022 Association for Computational Linguistics.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

An Audit on the Perspectives and Challenges of Hallucinations in NLP

An Audit on the Perspectives and Challenges of Hallucination...

引用

2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Venkit, Pranav Narayanan Chakravorti, Tatiana Gupta, Vipul Biggs, Heidi Srinath, Mukund Goswami, Koustava Rajtmajer, Sarah Wilson, Shomir College of Information Sciences and Technology Pennsylvania State University United States Adobe Research United States School of Interactive Computing Georgia Institute of Technology United States Department of Computer Science & Engineering Pennsylvania State University United States

ISBN: (纸本)9798891761643

We audit how hallucination in large language models (LLMs) is characterized in peer-reviewed literature, using a critical examination of 103 publications across NLP research. Through the examination of the literature, we identify a lack of agreement with the term 'hallucination' in the field of NLP. Additionally, to compliment our audit, we conduct a survey with 171 practitioners from the field of NLP and AI to capture varying perspectives on hallucination. Our analysis calls for the necessity of explicit definitions and frameworks outlining hallucination within NLP, highlighting potential challenges, and our survey inputs provide a thematic understanding of the influence and ramifications of hallucination in society. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

来源：评论

学校读者我要写书评

暂无评论

Investigation on Relative Pose Regression for Multi-Camera Setups with Neural Radiance Fields 8

Investigation on Relative Pose Regression for Multi-Camera S...

引用

8th International ISPRS Workshop LowCost 3D - Sensors, Algorithms, Applications

作者： Kullmann, Timo Hübner, Patrick Wirth, Tristan Kuijper, Arjan Iwaszczuk, Dorota Technical University of Darmstadt Dept. of Civil and Environmental Engineering Sciences Remote Sensing and Image Analysis Darmstadt Germany Technical University of Darmstadt Dept. of Computer Science Mathematical and Applied Visual Computing Darmstadt Germany Fraunhofer IGD Darmstadt Germany Technical University of Darmstadt Dept. of Computer Science Interactive Graphics Systems Darmstadt Germany

Neural Radiance Fields (NeRFs) are a novel approach that is being intensively investigated in 3D scene reconstruction and similar fields to overcome challenges of conventional methods. In this paper, we address the problem of estimating missing camera poses in a six degrees of freedom setting, pushing the capabilities of NeRFs to address scenarios where only the primary camera's pose is known. Specifically, we focus on dual-camera setups with this constraint. Our core contribution is a novel pose correction model that operates alongside an unmodified NeRF model, for which we have chosen Nerfacto in the Nerfstudio framework. The pose correction model learns the necessary relative translation and rotation adjustments for the secondary camera solely through the NeRF loss. This allows us to integrate our correction model directly into the Nerfacto training pipeline without altering the core functionality. Through extensive experiments on different camera configurations in a synthetic scene, we rigorously evaluate our model's performance across diverse scenarios, pushing it to its limits. Our findings reveal that our model can effectively learn pose correction parameters within a constrained range, with increased sensitivity to larger translations and particular challenges in rotation corrections. This research highlights the potential of NeRFs for machine learning-driven 3D reconstruction on dual- and multi-camera platforms, expanding the applicability of NeRFs to more complex, real-world setups despite the inherent challenges. Copyright: © 2024 Timo Kullmann et al.

关键词： 3D reconstruction

来源：评论

学校读者我要写书评

暂无评论

Datafication Dilemmas: Data Governance in the Public Interest 24

Datafication Dilemmas: Data Governance in the Public Interes...

引用

27th ACM Conference on computer-Supported Cooperative Work and Social computing, CSCW Companion 2024

作者： Huber, Linda Singh, Anubha Dombrowski, Lynn Guha, Shion Hardy, Jean Holten Møller, Naja School of Information University of Michigan Ann ArborMI United States School of Interactive Computing Georgia Institute of Technology AtlantaGA United States Faculty of Information University of Toronto Department of Computer Science TorontoON Canada Department of Media & Information Michigan State University East LansingMI United States Department of Computer Science University of Copenhagen Copenhagen Denmark

ISBN: (纸本)9798400711145

Within CSCW, there is a robust body of literature examining the infrastructures, institutions, and labor processes enabling pervasive processes of datafication. Key public sectors and industries are being increasingly datafied, often in the service of implementing AI tools to improve the efficiency, efficacy, and equity of public goods and services. This panel specifically examines the role of CSCW scholars in advancing public-interest technologies by engaging with datafication through the register of data governance. Each panelist brings perspectives from diverse domains of datafication - including healthcare, education, and agriculture - and state, corporate, and community forms of data governance. We invite panelists and attendees to explore a series of provocations focused on reconceptualizing our role and responsibility as researchers in intervening in processes of datafication and data governance. © 2024 Owner/Author.

关键词： Data assimilation

来源：评论

学校读者我要写书评

暂无评论

ProxiCycle: Passively Mapping Cyclist Safety Using Smart Handlebars for Near-Miss Detection 25

ProxiCycle: Passively Mapping Cyclist Safety Using Smart Han...

引用

2025 CHI Conference on Human Factors in computing Systems, CHI 2025

作者： Breda, Joseph Chen, Keyu Plötz, Thomas Patel, Shwetak Paul G. Allen School of Computer Science & Engineering University of Washington Seattle WA United States Gridware San Fancisco United States School of Interactive Computing Georgia Institute of Technology Atlanta GA United States

ISBN: (纸本)9798400713941

Active transportation is a valuable tool to prevent some of the most common causes of mortality worldwide, but is severely underutilized. The primary factors preventing cyclist adoption are safety concerns, specifically, the fear of collision from automobiles. One solution to address this concern is to direct cyclists to known safe routes to minimize risk and stress, thus making cycling more approachable. However, few localized safety priors are available, hindering safety based routing. Specifically, road user behavior is unknown. To address this issue, we develop a novel handlebar attachment to passively monitor the proximity of passing cars as a an indicator of cycling safety along historically traveled routes. We deploy this sensor with 15 experienced cyclists in a 2 month longitudinal study to source a citywide map of car passing distance. We then compare this signal to both historic collisions and perceived safety reported by experienced and inexperienced cyclists. © 2025 Copyright held by the owner/author(s).

关键词： Bicycle Mobile Sensing Public Health Safety Smartphone Transportation Urban Sensing

来源：评论

学校读者我要写书评

暂无评论

Heterogeneous Collaborative Pursuit via Coverage Control Driven by Fokker-Planck Equations

引用

IEEE Transactions on Robotics 2025年

作者： Lin, Ruoyu Kim, Soobum Egerstedt, Magnus University of California Department of Electrical Engineering and Computer Science IrvineCA92697 United States Georgia Institute of Technology School of Interactive Computing AtlantaGA30332 United States

Inspired by common features found in collaborative behaviors in nature, we investigate a general collaborative pursuit framework enabling heterogeneous multi-robot systems to adapt to dynamic environments and diverse tasks. A class of augmented Fokker-Planck equations is formulated to characterize dynamic environmental conditions, and the resulting time-varying density functions drive a novel coverage-based controller, with provable stability properties, for the participating robots to perform tasks in real time. The developed framework is decentralized and incorporates heterogeneity among different robots in task suitability, relative performance in a specific task, and safe operating regions. To demonstrate its adaptivity and effectiveness, the framework is implemented across four experimental applications ranging from multi-robot coordination to collaboration, namely forest firefighting, pursuit-evasion, monitoring of various environmental phenomena, and phoretic interactions. © 2004-2012 IEEE.

关键词： Multipurpose robots

来源：评论

学校读者我要写书评

暂无评论

Enhancing Textbooks with Visuals from the Web for Improved Learning

arXiv

引用

arXiv 2023年

作者： Singh, Janvijay Zouhar, Vilém Sachan, Mrinmaya School of Interactive Computing Georgia Institute of Technology United States ETH Zürich Department of Computer Science Switzerland

Textbooks are one of the main mediums for delivering high-quality education to students. In particular, explanatory and illustrative visuals play a key role in retention, comprehension and general transfer of knowledge. However, many textbooks lack these interesting visuals to support student learning. In this paper, we investigate the effectiveness of vision-language models to automatically enhance textbooks with images from the web. We collect a dataset of e-textbooks in the math, science, social science and business domains. We then set up a text-image matching task that involves retrieving and appropriately assigning web images to textbooks, which we frame as a matching optimization problem. Through a crowd-sourced evaluation, we verify that (1) while the original textbook images are rated higher, automatically assigned ones are not far behind, and (2) the precise formulation of the optimization problem matters. We release the dataset of textbooks with an associated image bank to inspire further research in this intersectional area of computer vision and NLP for education. © 2023, CC BY.

关键词： Image enhancement

来源：评论

学校读者我要写书评

暂无评论

Work of the Unemployed

Work of the Unemployed

引用

2021 ACM Designing interactive Systems Conference: Nowhere and Everywhere, DIS 2021

作者： Holten Holten Møller, Naja Rask Nielsen, Trine Le Dantec, Christopher Department of Computer Science University of Copenhagen Denmark School of Interactive Computing Georgia Institute of Technology United States

ISBN: (纸本)9781450384766

Public services increasingly presume a new and more active role for individuals to play in datafied society. While design efforts increasingly attempt to include stakeholders, such attempts are often limited to professional perspectives. Little is known about how individuals who are subject to these solutions experience the increasing use of data about them. One example of public services is job placement. Taking design fiction as our approach, we invited individuals enrolled in job placement (n=20) to reflect on the gwork of the unemployed', a fictive scenario where individuals make themselves eligible for support through sharing data. The fiction addresses power dynamics. The study shows how approaches, such as design fiction, are effective at including marginalized communities through changing the conditions for design. Showcasing the fictional outlook, and how the gdesign experience' can be disempowering if not qualified through a deeper critique, the paper contributes to agendas on design justice. © 2021 ACM.

关键词： computer programming

来源：评论

学校读者我要写书评

暂无评论

DLPO : Towards a Robust, Efficient, and Generalizable Prompt Optimization Framework from a Deep-Learning Perspective

arXiv

引用

arXiv 2025年

作者： Peng, Dengyun Zhou, Yuhang Chen, Qiguang Liu, Jinhao Chen, Jingjing Qin, Libo Research Center for Social Computing and Interactive Robotics Harbin Institute of Technology China School of Computer Science and Engineering Central South University China Fudan University China

Large Language Models (LLMs) have achieved remarkable success across diverse tasks, largely driven by well-designed prompts. However, crafting and selecting such prompts often requires considerable human effort, significantly limiting its scalability. To mitigate this, recent studies have explored automated prompt optimization as a promising solution. Despite these efforts, existing methods still face critical challenges in robustness, efficiency, and generalization. To systematically address these challenges, we first conduct an empirical analysis to identify the limitations of current reflection-based prompt optimization paradigm. Building on these insights, we propose 7 innovative approaches inspired by traditional deep learning paradigms for prompt optimization (DLPO), seamlessly integrating these concepts into text-based gradient optimization. Through these advancements, we progressively tackle the aforementioned challenges and validate our methods through extensive experimentation. We hope our study not only provides valuable guidance for future research but also offers a comprehensive understanding of the challenges and potential solutions in prompt optimization. Our code is available at https://***/sfasfaffa/DLPO. Copyright © 2025, The Authors. All rights reserved.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：