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Articles 3151 - 3180 of 11188
Full-Text Articles in Artificial Intelligence and Robotics
Learning Nighttime Semantic Segmentation The Hard Way, Wenxi Liu, Jiaxin Cai, Qi Li, Chenyang Liao, Jingjing Cao, Shengfeng He, Yuanlong Yu
Learning Nighttime Semantic Segmentation The Hard Way, Wenxi Liu, Jiaxin Cai, Qi Li, Chenyang Liao, Jingjing Cao, Shengfeng He, Yuanlong Yu
Research Collection School Of Computing and Information Systems
Nighttime semantic segmentation is an important but challenging research problem for autonomous driving. The major challenges lie in the small objects or regions from the under-/over-exposed areas or suffer from motion blur caused by the camera deployed on moving vehicles. To resolve this, we propose a novel hard- class-aware module that bridges the main network for full-class segmentation and the hard-class network for segmenting aforementioned hard-class objects. In specific, it exploits the shared focus of hard-class objects from the dual-stream network, enabling the contextual information flow to guide the model to concentrate on the pixels that are hard to classify. …
Text-Attributed Graph Representation Learning : Methods, Applications, And Challenges, Ce Zhang, Menglin Yang, Rex Ying, Hady Wirawan Lauw
Text-Attributed Graph Representation Learning : Methods, Applications, And Challenges, Ce Zhang, Menglin Yang, Rex Ying, Hady Wirawan Lauw
Research Collection School Of Computing and Information Systems
Text documents are usually connected in a graph structure, resulting in an important class of data named text-attributed graph, e.g., paper citation graph and Web page hyperlink graph. On the one hand, Graph Neural Networks (GNNs) consider text in each document as general vertex attribute and do not specifically deal with text data. On the other hand, Pre-trained Language Models (PLMs) and Topic Models (TMs) learn effective document embeddings. However, most models focus on text content in each single document only, ignoring link adjacency across documents. The above two challenges motivate the development of text-attributed graph representation learning, combining GNNs …
Cornac-Ab : An Open-Source Recommendation Framework With Native A/B Testing Integration, Rong Sheng Ong, Quoc Tuan Truong, Hady Wirawan Lauw
Cornac-Ab : An Open-Source Recommendation Framework With Native A/B Testing Integration, Rong Sheng Ong, Quoc Tuan Truong, Hady Wirawan Lauw
Research Collection School Of Computing and Information Systems
Recommender systems significantly impact user experience across diverse domains, yet existing frameworks often prioritize offline evaluation metrics, neglecting the crucial integration of A/B testing for forward-looking assessments. In response, this paper introduces a new framework seamlessly incorporating A/B testing into the Cornac recommendation library. Leveraging a diverse collection of model implementations in Cornac, our framework enables effortless A/B testing experiment setup from offline trained models. We introduce a carefully designed dashboard and a robust backend for efficient logging and analysis of user feedback. This not only streamlines the A/B testing process but also enhances the evaluation of recommendation models in …
Term Importance For Transformer-Based Qa Retrieval : A Case Study Of Stackexchange, Bryan Zhi Yang Tan, Hady W. Lauw
Term Importance For Transformer-Based Qa Retrieval : A Case Study Of Stackexchange, Bryan Zhi Yang Tan, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Question-answering (QA) retrieval is the task of retrieving the most relevant answer to a given question from a collection of answers. Various approaches to QA retrieval have been developed recently. One successful and popular model is Contextualized Late Interaction over BERT (ColBERT), a transformer-based approach that adopts a query-document scoring mechanism that retains the granularity of transformer matching, whilst improving on efficiency. However, one key limitation is that it requires further fine-tuning for new query or collection types. In this work, we explore and propose several non-parametric retrieval augmentation methods based on explicit signals of term importance that improve over …
Online Control Of Adaptive Large Neighborhood Search Using Deep Reinforcement Learning, Reijnen Reijnen, Yingqian Zhang, Hoong Chuin Lau, Zaharah Bukhsh
Online Control Of Adaptive Large Neighborhood Search Using Deep Reinforcement Learning, Reijnen Reijnen, Yingqian Zhang, Hoong Chuin Lau, Zaharah Bukhsh
Research Collection School Of Computing and Information Systems
The Adaptive Large Neighborhood Search (ALNS) algorithm has shown considerable success in solving combinatorial optimization problems (COPs). Nonetheless, the performance of ALNS relies on the proper configuration of its selection and acceptance parameters, which is known to be a complex and resource-intensive task. To address this, we introduce a Deep Reinforcement Learning (DRL) based approach called DR-ALNS that selects operators, adjusts parameters, and controls the acceptance criterion throughout the search. The proposed method aims to learn, based on the state of the search, to configure ALNS for the next iteration to yield more effective solutions for the given optimization problem. …
Difference Of Convex Functions Programming For Policy Optimization In Reinforcement Learning, Akshat Kumar
Difference Of Convex Functions Programming For Policy Optimization In Reinforcement Learning, Akshat Kumar
Research Collection School Of Computing and Information Systems
We formulate the problem of optimizing an agent's policy within the Markov decision process (MDP) model as a difference-of-convex functions (DC) program. The DC perspective enables optimizing the policy iteratively where each iteration constructs an easier-to-optimize lower bound on the value function using the well known concave-convex procedure. We show that several popular policy gradient based deep RL algorithms (both for discrete and continuous state, action spaces, and stochastic/deterministic policies) such as actor-critic, deterministic policy gradient (DPG), and soft actor critic (SAC) can be derived from the DC perspective. Additionally, the DC formulation enables more sample efficient learning approaches by …
Rule-Guided Counterfactual Explainable Recommendation, Yinwei Wei, Xiaoyang Qu, Xiang Wang, Yunshan Ma, Liqiang Nie, Tat‑Seng Chua
Rule-Guided Counterfactual Explainable Recommendation, Yinwei Wei, Xiaoyang Qu, Xiang Wang, Yunshan Ma, Liqiang Nie, Tat‑Seng Chua
Research Collection School Of Computing and Information Systems
To empower the trust of current recommender systems, the counterfactual explanation (CE) method is adopted to generate the counterfactual instance for each input and take their changes causing the different outcomes as the explanation. Although promising results have been achieved by existing CE-based methods, we propose to generate the attribute-oriented counterfactual explanation. Different from them, we aim to generate the counterfactual instance by performing the intervention on the attributes, and then build an attribute-oriented counterfactual explainable recommender system. Considering the correlation and categorical values of attributes, how to efficiently generate the reliable counterfactual instances on the attributes challenges us. To …
Learning To Generate Explainable Stock Predictions Using Self‑Reflective Large Language Models, Kelvin J.L. Koa, Yunshan Ma, Ritchie Ng, Tat‑Seng Chua
Learning To Generate Explainable Stock Predictions Using Self‑Reflective Large Language Models, Kelvin J.L. Koa, Yunshan Ma, Ritchie Ng, Tat‑Seng Chua
Research Collection School Of Computing and Information Systems
Explaining stock predictions is generally a difficult task for traditional non-generative deep learning models, where explanations are limited to visualizing the attention weights on important texts. Today, Large Language Models (LLMs) present a solution to this problem, given their known capabilities to generate human-readable explanations for their decision-making process. However, the task of stock prediction remains challenging for LLMs, as it requires the ability to weigh the varying impacts of chaotic social texts on stock prices. The problem gets progressively harder with the introduction of the explanation component, which requires LLMs to explain verbally why certain factors are more important …
Fashionregen: Llm‑Empowered Fashion Report Generation, Yujuan Ding, Yunshan Ma, Wenqi Fan, Yige Yao, Tat‑Seng Chua, Qing Li
Fashionregen: Llm‑Empowered Fashion Report Generation, Yujuan Ding, Yunshan Ma, Wenqi Fan, Yige Yao, Tat‑Seng Chua, Qing Li
Research Collection School Of Computing and Information Systems
Fashion analysis refers to the process of examining and evaluating trends, styles, and elements within the fashion industry to understand and interpret its current state, generating fashion reports. It is traditionally performed by fashion professionals based on their expertise and experience, which requires high labour cost and may also produce biased results for relying heavily on a small group of people. In this paper, to tackle the Fashion Report Generation (FashionReGen) task, we propose an intelligent Fashion Analyzing and Reporting system based the advanced Large Language Models (LLMs), debbed as GPT-FAR. Specifically, it tries to deliver FashionReGen based on effective …
Escaping Saddle Points In Heterogeneous Federated Learning Via Distributed Sgd With Communication Compression, Sijin Chen, Zhize Li, Yuejie Chi
Escaping Saddle Points In Heterogeneous Federated Learning Via Distributed Sgd With Communication Compression, Sijin Chen, Zhize Li, Yuejie Chi
Research Collection School Of Computing and Information Systems
We consider the problem of finding second-order stationary points in the optimization of heterogeneous federated learning (FL). Previous works in FL mostly focus on first-order convergence guarantees, which do not rule out the scenario of unstable saddle points. Meanwhile, it is a key bottleneck of FL to achieve communication efficiency without compensating the learning accuracy, especially when local data are highly heterogeneous across different clients. Given this, we propose a novel algorithm PowerEF-SGD that only communicates compressed information via a novel error-feedback scheme. To our knowledge, PowerEF-SGD is the first distributed and compressed SGD algorithm that provably escapes saddle points …
Navigating Real-World Challenges: A Quadruped Robot Guiding System For Visually Impaired People In Diverse Environments, Shaojun Cai, Ashwin Ram, Zhengtai Gou, Mohd Alqama Wasim Shaikh, Yu-An Chen, Yingjia Wan, Kotaro Hara, Shengdong Zhao, David Hsu
Navigating Real-World Challenges: A Quadruped Robot Guiding System For Visually Impaired People In Diverse Environments, Shaojun Cai, Ashwin Ram, Zhengtai Gou, Mohd Alqama Wasim Shaikh, Yu-An Chen, Yingjia Wan, Kotaro Hara, Shengdong Zhao, David Hsu
Research Collection School Of Computing and Information Systems
Blind and Visually Impaired (BVI) people find challenges in navigating unfamiliar environments, even using assistive tools such as white canes or smart devices. Increasingly affordable quadruped robots offer us opportunities to design autonomous guides that could improve how BVI people find ways around unfamiliar environments and maneuver therein. In this work, we designed RDog, a quadruped robot guiding system that supports BVI individuals’ navigation and obstacle avoidance in indoor and outdoor environments. RDog combines an advanced mapping and navigation system to guide users with force feedback and preemptive voice feedback. Using this robot as an evaluation apparatus, we conducted experiments …
Optimization Pump As Turbine Coupled To A Self-Excited Induction Generator Using Multi-Objective Genetic Algorithm, Emanuel J. Nyirenda
Optimization Pump As Turbine Coupled To A Self-Excited Induction Generator Using Multi-Objective Genetic Algorithm, Emanuel J. Nyirenda
Tanzania Journal of Engineering and Technology (TJET)
As a way of accelerating the deployment of affordable and clean renewable energy generation technologies, applying a pump working as a turbine coupled to a self-excited induction generator is gaining popularity in various areas including energy recovery and micro hydro systems. However, it is currently challenging to predict the performance of the PAT-SEIG system and there is no agreed-upon rule on the selection of the appropriate system to be installed at a particular site. This paper has presented multi-objective optimization to select the best operating point of the PAT-SEIG system. The results show that the peak efficiencies for the PAT …
Assessment Of Risk Factors Related To Body Pain Complaints In Tanzania Construction Industry, Fatma K. Mohamed
Assessment Of Risk Factors Related To Body Pain Complaints In Tanzania Construction Industry, Fatma K. Mohamed
Tanzania Journal of Engineering and Technology (TJET)
The construction industry is associated with risks that can result in musculoskeletal diseases. Although young male workers who are presumed to be healthy dominate the industry in Tanzania, body pain complaints have been widely reported. The aim of this study is to assess the prevalence and causes of body pains in workers. A cross-sectional study involving 396 workers was conducted. A chi square test was used for testing association of independent categorical variables and binary logistic regression analysis was used to determine predictors for body pain complaints. The results show that all study participants complained of at least one form …
Evaluating Introductory Computer Science Labs In The Presence Of Ai Tools, Nicholas Snow, Devin Chaimberlain, Abigail Pitcairn, Benjamin Sweeney
Evaluating Introductory Computer Science Labs In The Presence Of Ai Tools, Nicholas Snow, Devin Chaimberlain, Abigail Pitcairn, Benjamin Sweeney
Thinking Matters Symposium
This study explores the resistance of introductory computer science lab assignments to “shortcutting” by generative AI tools, such as ChatGPT. By analyzing the work of three distinct student personas on these assignments, we identified key characteristics of language and structure that influence an assignment's vulnerability to AI abuse. Based on these insights, we propose strategies for educators to adapt labs to both counteract AI shortcutting and encourage productive uses of AI.
Machine Learning-Based Gps Jamming And Spoofing Detection, Alberto Squatrito
Machine Learning-Based Gps Jamming And Spoofing Detection, Alberto Squatrito
Doctoral Dissertations and Master's Theses
The increasing reliance on Global Positioning System (GPS) technology across various sectors has exposed vulnerabilities to malicious attacks, particularly GPS jamming and spoofing. This thesis presents an analysis into detection and mitigation strategies for enhancing the resilience of GPS receivers against jamming and spoofing attacks. The research entails the development of a simulated GPS signal and a receiver model to accurately decode and extract information from simulated GPS signals. The study implements the generation of jammed and spoofed signals to emulate potential threats faced by GPS receivers in practical settings. The core innovation lies in the integration of machine learning …
Artificial Intelligence And Film: A Journey In Public Perception From 1960 To The Present Day, Kayla Anderson, Andrew Roggeman, Joseph Fuller
Artificial Intelligence And Film: A Journey In Public Perception From 1960 To The Present Day, Kayla Anderson, Andrew Roggeman, Joseph Fuller
Celebrating Scholarship and Creativity Day (2018-)
An analysis of accomplishments in film from the 1960s-2020s that feature Artificial Intelligence to give a full picture of how public perception has changed towards these technologies over time, supplemented by historical and technological context.
Hello, World., Elliot Cetinski, Evan Chartock, Olivia Cross, Kiran Drew, Kaya Eller, Ben Little, Joey Nolan, Spencer Toth, Sophie Wahl-Taylor, Sadie Walker, Destiny Young, Annie Zulick
Hello, World., Elliot Cetinski, Evan Chartock, Olivia Cross, Kiran Drew, Kaya Eller, Ben Little, Joey Nolan, Spencer Toth, Sophie Wahl-Taylor, Sadie Walker, Destiny Young, Annie Zulick
Theater and Dance Presentations
This project works to theatrically represent the current state of Artificial Intelligence (AI), as well as its benefits and drawbacks, in the style of the Living Newspaper. Originating from a Great Depression-era job program, the Living Newspaper sought to take headlines and present them onstage for a poignant and contemporary social critique. This work does the same, melding different angles of the AI debate into a single production that emphasizes the rapidly progressing state of modern AI technology and the need for humans to consider the impacts such technologies will have. Furthermore, it asks the audience to question their position …
Editorials For Special Topic "Artificial Intelligence And Future Society"
Editorials For Special Topic "Artificial Intelligence And Future Society"
Bulletin of Chinese Academy of Sciences (Chinese Version)
No abstract provided.
Social Order In Age Of Artificial Intelligence, Yongnian Zheng
Social Order In Age Of Artificial Intelligence, Yongnian Zheng
Bulletin of Chinese Academy of Sciences (Chinese Version)
While the rapid development of artificial intelligence is empowering society, it is also posing serious threats to the continuation of the traditional social order. The "de-intellectualization" function of AI has given rise to the phenomenon of "artificial ignorance", referring to the self-inflicted intellectual harm caused by the uncontrolled and excessive misuse of AI-related tools, thus causing a profound impact on the social order. The technical structural characteristics and governance structural characteristics of AI contributed to the emergence of the phenomenon of "artificial ignorance". The technical structural characteristics of AI can be summarized as highly concentrated capabilities, highly centralized control, highly …
Impact Analysis Of Artificial Intelligence Technology On Employment And Income In China, Yan Lu, Lincui Gui
Impact Analysis Of Artificial Intelligence Technology On Employment And Income In China, Yan Lu, Lincui Gui
Bulletin of Chinese Academy of Sciences (Chinese Version)
With the continuous development of artificial intelligence technology, employment and income in China will undergo some new changes. It is necessary to explore the impact of artificial intelligence technology on employment and income distribution. The study finds that in terms of employment, the impact of artificial intelligence includes redefining the number and nature of jobs, affecting work patterns and work skills, and possibly triggering structural imbalances between supply and demand in the labor market, leading to employment inequality, increasing employment risks. In term of income distribution, artificial intelligence technology has a heterogeneous impact on the initial distribution of different fields, …
Open Governance And Innovation Directions Regulation: Research On Institutional Mechanisms For Promoting Development Of Artificial General Intelligence, Yuhao Jiang, Xinyi Zhang, Mingjie Dai
Open Governance And Innovation Directions Regulation: Research On Institutional Mechanisms For Promoting Development Of Artificial General Intelligence, Yuhao Jiang, Xinyi Zhang, Mingjie Dai
Bulletin of Chinese Academy of Sciences (Chinese Version)
In the field of artificial intelligence development, there is still a certain gap between China and the United States. The uncertain future of artificial general intelligence (AGI) decides that China should not only implement the "catch-up" strategy. Artificial intelligence is not a ‘linear innovation' development path, but there is overlap between basic research, applied research, and industrial transformation. This feature of innovation shows that diversified exploration can be realized based on tracking of international frontiers, breakthrough of basic research, and satisfaction of diverse application needs. China needs to adhere to the promotion of open governance, and regulate innovation directions of …
Research On Data Security And International Governance Cooperation Framework In Era Of Artificial Intelligence, Yuanyuan Wei
Research On Data Security And International Governance Cooperation Framework In Era Of Artificial Intelligence, Yuanyuan Wei
Bulletin of Chinese Academy of Sciences (Chinese Version)
This study explores the international cooperation framework for data security governance and its implementation pathways from a global governance perspective. First, the study defines the concepts of data security and governance, emphasizing that the core objective of data governance is to ensure the secure flow and effective utilization of data. Second, it analyzes the current fragmentation of the global data governance system, revealing its development trends and challenges under the influence of geopolitics, particularly the tensions and collaborations in key areas such as cross-border data flows. Based on this analysis, the study proposes the concept of the "Embedded Digital Community …
Study On Constraints And Policy Responses For Production And Circulation Of Ai Training Data In China, Tao Lin
Bulletin of Chinese Academy of Sciences (Chinese Version)
The quantity and quality of training data are critical to the performance of artificial intelligence (AI) models. However, in China, the production of training data is hindered by issues such as insufficient quantity, low quality, and fragmented distribution, compounded by limitations stemming from commercial ecosystems, regulatory frameworks, and restricted development and utilization of public data. To address these challenges, this study proposes several policy recommendations, including incentivizing research institutions to generate open-source datasets, fostering AI application scenarios, adopting a "loose-in, focus-out" regulatory approach, introducing intellectual property exemption provisions, refining personal information protection guidelines, and expediting the establishment of a unified …
Venture Capital And Its Role In Facilitating Better Development In China's Artificial Intelligence Industry, Randong Yuan
Venture Capital And Its Role In Facilitating Better Development In China's Artificial Intelligence Industry, Randong Yuan
Bulletin of Chinese Academy of Sciences (Chinese Version)
The venture capital (VC) industry plays a crucial role in advancing the development of the artificial intelligence (AI) sector. As a key bridge between technological innovation and industrialization, VC not only provides financial support to AI startups but also empowers them in strategic planning, technological research and development, and market expansion. However, China's VC industry currently faces several challenges in supporting AI development, including an imbalance in the roles of state-owned and private capital, a short-term investment mindset, and the cyclical phenomenon of "herding" and abrupt market exits. These issues hinder the growth trajectories of Chinese AI enterprises and constrain …
New System For Mobilizing Resources Nationwide To Promote Leapfrog Development Of Innovation Ecosystem Of Artificial Intelligence Enterprises: Mechanisms, Problems And Strategies, Yang Mei, Hao Niu, Han Jiang
New System For Mobilizing Resources Nationwide To Promote Leapfrog Development Of Innovation Ecosystem Of Artificial Intelligence Enterprises: Mechanisms, Problems And Strategies, Yang Mei, Hao Niu, Han Jiang
Bulletin of Chinese Academy of Sciences (Chinese Version)
Facing the unpredictable new features of top-down AI technological innovation and the new requirements on functions, this study proposes to re-examine the technological innovation of AI at the enterprise level from the perspective of the "a new system for mobilizing the resources nationwide" and with the enterprise innovation ecosystem as the carrier. On the basis of explaining the elements and operation logic of the new system at the enterprise level, compared to the "implicit national system" of the US, this study preliminarily compares the new system of AI in China and that in the US. It is proposed that the …
How China Leads Global Governance Of Artificial Intelligence: A Sustainable Development Approach Beyond Technological Competition, Xuanming Pan, Zhenzhen Chen, Shaoshan Liu
How China Leads Global Governance Of Artificial Intelligence: A Sustainable Development Approach Beyond Technological Competition, Xuanming Pan, Zhenzhen Chen, Shaoshan Liu
Bulletin of Chinese Academy of Sciences (Chinese Version)
In the context of great power competition and escalating geopolitical conflicts, the academic community generally holds a pessimistic view of AI international cooperation, believing that the space is shrinking. This perception mainly stems from conflicts in the cross-border supervision of AI data and algorithms among technologically advanced countries, while overlooking the strong willingness and potential for cooperation in energy conservation and emission reduction through AI technologies shown by Global South countries. Looking into the future of global governance, China, starting from leading the transformation of AI technologies, shall take lead in supporting these countries to transform the sustainable development consensus …
U.S.-Europe Artificial Intelligence Regulatory Cooperation, Divergence, And China's "Window Of Opportunity" For Strategic Breakthrough, Yang Mei, Jing Zeng, Yong Zhan
U.S.-Europe Artificial Intelligence Regulatory Cooperation, Divergence, And China's "Window Of Opportunity" For Strategic Breakthrough, Yang Mei, Jing Zeng, Yong Zhan
Bulletin of Chinese Academy of Sciences (Chinese Version)
The United States, Europe, and China have adopted completely different technological development paths in the era of artificial intelligence innovation, forming a model division of "development-driven governance", "stringent governance framework", and "coordinated governance model" The United States and Europe have respectively set strategic goals as "maintaining technological hegemony" and "competing for the soft power of international rules", forming an interactive model in which institutional supervision and industry independence parallel, and cooperation needs and policy divergence coexist. China has contributed a unique technological governance logic of "people-oriented" and "moral-oriented". Faced with the current technological "window of opportunity", China should adopt two …
Ai-Powered Learning: Blending Ai With Active Learning In The Information Literacy Classroom, Kevin J. Reagan, Wilhelmina Randtke
Ai-Powered Learning: Blending Ai With Active Learning In The Information Literacy Classroom, Kevin J. Reagan, Wilhelmina Randtke
Georgia International Conference on Information Literacy
In 2016, the ACRL Framework for Information Literacy in Higher Education launched in response to more voluminous, less-vetted online information, including misinformation and content farms. Subsequently, the ACRL Framework has been widely adopted, and numerous high-quality lesson plans and resources for teaching the frames already exist, including published lesson plans and textbooks. Now, generative AI tools, such as ChatGPT and other chat bots present new challenges for information literacy educators. For instance, in addition to teaching students how to identify issues such as fake news, the information literacy professional has to address topics such as ethical AI use, AI hallucination …
Andrews University Pre-Professional Students Preparedness For A Future With Artificial Intelligence, Zachary Alignay
Andrews University Pre-Professional Students Preparedness For A Future With Artificial Intelligence, Zachary Alignay
Honors Theses
Artificial Intelligence technology has advanced considerably over the past four years. With such rapid technological development, the question has to be asked if students are adequately educated on the implications and abilities of artificial intelligence. Are Andrews University pre-professional students prepared for future careers with artificial intelligence? To approach this question, a survey of students across multiple perspectives was conducted to sample if there was a consensus, or lack thereof, on the perception of ethics regarding artificial intelligence, to ask students how using artificial intelligence has changed their education, what purposes it can be used or cannot be used, personal …
Subject Analysis Ex Machina: Developing A Subject Heading Recommendation Service For Jmu Libraries, Steven W. Holloway
Subject Analysis Ex Machina: Developing A Subject Heading Recommendation Service For Jmu Libraries, Steven W. Holloway
Libraries
Results of a 2022 evaluation of ANNIF, open-source software designed to generate controlled vocabulary subject headings, using James Madison University Libraries resources.