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Articles 211 - 240 of 10053
Full-Text Articles in Entire DC Network
The Case For Ai Authorship In Copyright Law, Cheng Lim Saw, Duncan Lim
The Case For Ai Authorship In Copyright Law, Cheng Lim Saw, Duncan Lim
Research Collection Yong Pung How School Of Law
Today, with generative AI, literary and artistic works can be created almost effortlessly. There is at present intense debate as to whether works generated by AI – broadly categorised as “AI-assisted” and “AI-generated” works – ought to attract copyright protection. AI-assisted works are those that involve some degree of human intervention. Where AI-generated works are concerned, however, such works are created autonomously by the AI itself with minimal (de minimis) input from an identifiable human being. Presently, it is generally accepted that AI-generated works do not attract copyright protection for want of a human author. This article examines whether it …
There Is No One-Size-Fits-All Approach To Sovereign Finance, Guan Seng Khoo, Annie Koh
There Is No One-Size-Fits-All Approach To Sovereign Finance, Guan Seng Khoo, Annie Koh
Research Collection Lee Kong Chian School Of Business
In a commentary, SMU Professor Emeritus of Finance (Practice) Annie Koh and Khoo Guan Seng, Asia-Pacific advisory council member of the SWF Academy and EU-Asean Centre, opined that in a volatile world, the strength of a sovereign wealth fund lies in its ability to fulfil its specific, sovereign purpose. Prof Koh and Mr Khoo said that sovereign wealth funds are bespoke instruments of national policy, and in the world of sovereign capital, one size does not, and cannot, fit all. They noted that each fund is a reflection of a country’s unique ambitions, its resource endowments and its specific fears …
Defending Code Language Models Against Backdoor Attacks With Deceptive Cross-Entropy Loss, Guang Yang, Yu Zhou, Xiangyu Zhang, Xiang Chen, Terry Yue Zhuo, David Lo, Taolue Chen
Defending Code Language Models Against Backdoor Attacks With Deceptive Cross-Entropy Loss, Guang Yang, Yu Zhou, Xiangyu Zhang, Xiang Chen, Terry Yue Zhuo, David Lo, Taolue Chen
Research Collection School Of Computing and Information Systems
Code Language Models (CLMs), particularly those leveraging deep learning, have achieved significant success in code intelligence domain. However, the issue of security, particularly backdoor attacks, is often overlooked in this process. The previous research has focused on designing backdoor attacks for CLMs, but effective defenses have not been adequately addressed. In particular, existing defense methods from natural language processing, when directly applied to CLMs, are not effective enough and lack generality, working well in some models and scenarios but failing in others, thus fall short in consistently mitigating backdoor attacks. To bridge this gap, we first confirm the phenomenon of …
Beyond Resilience: The Case For Regenerative, Restorative Cities, Lily Kong
Beyond Resilience: The Case For Regenerative, Restorative Cities, Lily Kong
Research Collection School of Social Sciences
In a commentary, SMU President Professor Lily Kong mentioned that at the City Dialogues event, co-convened by SMU and Urban Innovation Vienna, participants agreed that cities must equip their residents to withstand shocks and thrive in an evolving urban environment. Prof Kong said resilient cities anticipate, adapt and respond effectively to disruptions, which involves attention not only to physical infrastructure, but also to social cohesion and institutional foresight. She said that embedding sustainability into urban design is fundamental to ensuring cities flourish in a world of climate uncertainty and resource constraints. She added that the value of urban resilience lies …
Secondary School Students' Engagement In Learning Activities: Validation Of A Short Scale, Feliciano Henriques Veiga, Zi Yang Wong, Johnmarshall Reeve, Shane Jimerson, Antonio Leite, Joan Perales, Sonia Valente, Isabel Martinez
Secondary School Students' Engagement In Learning Activities: Validation Of A Short Scale, Feliciano Henriques Veiga, Zi Yang Wong, Johnmarshall Reeve, Shane Jimerson, Antonio Leite, Joan Perales, Sonia Valente, Isabel Martinez
Research Collection School of Social Sciences
Student engagement is a multidimensional construct strongly associated with learning outcomes and academic success. However, its measurement remains challenging, as existing instruments often conflate engagement in learning activities with engagement in the school community. In addition, brief measures are scarce despite their increasing value, and most available instruments do not incorporate agentic engagement. Assessing student engagement in learning activities is, therefore, crucial for monitoring academic progress, identifying students at risk of dropping out, and predicting academic success. This study aimed to validate the 12-item Secondary School Student Engagement in Learning Activities: Short Scale, adapted from a higher education measure, which …
Uncertain Search With Knowledge Transfer, Woonghee Tim Huh, Michael Jong Kim, Meichun Lin
Uncertain Search With Knowledge Transfer, Woonghee Tim Huh, Michael Jong Kim, Meichun Lin
Research Collection Lee Kong Chian School Of Business
We consider a sequential search over a group of similar alternatives. The individual value of an alternative contains two components, an observable utility and an idiosyncratic value. Observable utilities share an unknown population distribution, which captures the similarity across the alternatives and allows for knowledge transfer within the group. Once a decision maker encounters an alternative, its utility is revealed immediately, whereas the idiosyncratic value is unobservable and needs to be learned by sampling. The goal is to select an alternative with the highest individual value while accounting for the sampling and search costs. A novel feature of this problem …
Are Cities Losing Innovation Advantages? Online Versus Face-To-Face Interactions, Ruben Gaetani, Naqun Huang, Jing Li, Yanmin Yang
Are Cities Losing Innovation Advantages? Online Versus Face-To-Face Interactions, Ruben Gaetani, Naqun Huang, Jing Li, Yanmin Yang
Research Collection School Of Economics
How did COVID-19 affect the innovation advantages of dense locations? Using data on the universe of U.S. patent applications, we find that the density premium in the production of novel inventions declined by 18.5%-22.9% in 2020-2021 relative to its pre-pandemic level. Smartphone data on local mobility suggest that the drop in the frequency of local interactions can explain a significant portion of this effect. While COVID-19 resulted in a temporary setback in the innovation advantages of dense locations, the role of urban density in facilitating the exchange and recombination of ideas is unlikely to be persistently replaced by online communication.
G-Trac: Graph-Textual Representations Alignment For Cold-Start Recommendations, Li Yang Chang, Yuan Fang, Ming Feng Tsai, Chuan Ju Wang
G-Trac: Graph-Textual Representations Alignment For Cold-Start Recommendations, Li Yang Chang, Yuan Fang, Ming Feng Tsai, Chuan Ju Wang
Research Collection School Of Computing and Information Systems
The cold-start problem remains a significant challenge in recommendation systems, particularly for new users or unseen items with little to no historical data. Existing methods, including graph neural networks, often struggle in such scenarios. Inspired by the success of transformer models in natural language processing, we propose G-TRAC (Graph-Textual Representations Alignment for Cold-start Recommendations), a novel approach that integrates transformer-based textual modeling with graph neural networks. By effectively leveraging both textual and structural information, G-TRAC addresses cold-start challenges more effectively. Extensive experiments demonstrate its ability to enhance recommendation quality and generalize well across diverse scenarios.
A Dynamic Inspection And Replacement Policy For Systems Subject To Degradation And Periodic Shocks, Jiawen Hu, Qiuzhuang Sun
A Dynamic Inspection And Replacement Policy For Systems Subject To Degradation And Periodic Shocks, Jiawen Hu, Qiuzhuang Sun
Research Collection College of Integrative Studies
Inspection is widely adopted to improve the maintenance efficiency. Most works predetermine a periodic inspection scheme and focus on optimizing the replacement threshold. However, it is reasonable to inspect less frequently when the degradation level of the system is low and to perform inspections more frequently as the degradation level increases. This work investigates a dynamic inspection and replacement policy for systems subject to regular degradation and periodic shocks. The regular degradation of the system is modeled as a Wiener process. Meanwhile, a periodic arrived shock will incur a random amount increment to the degradation, which is assumed to satisfy …
The Affective Economy Of Toxic Atmospheres: Sensory Governance, Ecological Intelligences And The Performative Politics Of Urban Mosquito Management, Orlando Woods, Creighton Connolly
The Affective Economy Of Toxic Atmospheres: Sensory Governance, Ecological Intelligences And The Performative Politics Of Urban Mosquito Management, Orlando Woods, Creighton Connolly
Research Collection College of Integrative Studies
This paper considers how atmospheres can play a powerful role in troubling the management of nature in the multispecies city. It brings the cyclical nature of atmospheric effects, the affective values and il/logics that determine human responses to non-human threats, and the misguided and potentially deleterious health outcomes that ensue into one analytical frame. Drawing on the empirical case of urban mosquito management in Singapore, it considers how the creation of toxic atmospheres through fogging – blowing insecticides into the air in a bid to kill mosquitoes – is ineffective and sets in motion a cascading series of socio-environmental consequences. …
Geopolitical Ecologies Of Cloud Capitalism: Territorial Restructuring And The Making Of National Computing Power In The Us And China, Justin Kollar, Sol Andrew Stokols
Geopolitical Ecologies Of Cloud Capitalism: Territorial Restructuring And The Making Of National Computing Power In The Us And China, Justin Kollar, Sol Andrew Stokols
Research Collection College of Integrative Studies
As computing power becomes central to geopolitical rivalry, cloud infrastructure is increasingly framed as critical to national security, economic resilience and technological sovereignty. Current debates often focus on global competition – especially between the U.S. and China – highlighting strategic investments, export controls and infrastructure diplomacy abroad. Yet far less attention has been paid to the domestic territorial transformations that make such geopolitical projection possible. This paper argues that national strategies for AI and cloud dominance depend on the reorganization of land, energy and regulatory systems to sustain large-scale computation. Using a geopolitical ecology framework, we examine how the U.S. …
Vercation: Precise Vulnerable Open-Source Software Version Identification Based On Static Analysis And Llm, Yiran Cheng, Ting Zhang, Lwin Khin Shar, Shouguo Yang, Chaopeng Dong, David Lo, Shichao Lv, Zhiqiang Shi, Limin Sun
Vercation: Precise Vulnerable Open-Source Software Version Identification Based On Static Analysis And Llm, Yiran Cheng, Ting Zhang, Lwin Khin Shar, Shouguo Yang, Chaopeng Dong, David Lo, Shichao Lv, Zhiqiang Shi, Limin Sun
Research Collection School Of Computing and Information Systems
Open-source software (OSS) has experienced a surge in popularity, attributed to its collaborative development model and cost-effective nature. However, the adoption of specific software versions in development projects may introduce security risks when these versions bring along vulnerabilities. Current methods of identifying vulnerable versions typically analyze and extract the code features involved in vulnerability patches using static analysis with pre-defined rules. They then use code clone detection to identify the vulnerable versions. These methods are hindered by imprecision due to (1) the exclusion of vulnerability- irrelevant code in the analysis and (2) the inadequacy of code clone detection. This paper …
Efficient Function Orchestration For Large Language Models, Xiaoxia Liu, Peng Di, Cong Li, Jun Sun, Jingyi Wang
Efficient Function Orchestration For Large Language Models, Xiaoxia Liu, Peng Di, Cong Li, Jun Sun, Jingyi Wang
Research Collection School Of Computing and Information Systems
Function calling is a fundamental capability of today's large language models, but sequential function calling posed efficiency problems. Recent studies have proposed to request function calls with parallelism support in order to alleviate this issue. However, they either delegate the concurrent function calls to users for execution which are conversely executed sequentially, or overlook the relations among various function calls, rending limited efficiency. This paper introduces LLMOrch, an advanced framework for automated, parallel function calling in large language models. The key principle behind LLMOrch is to identify an available processor to execute a function call while preventing any single processor …
Exploring Jvm Garbage Collector Testing With Event-Coverage, Kai Zheng, Yingquan Zhao, Junjie Chen, Hanmo You, Haoyu Wang, Haoyu Wang, Tianchang Gao
Exploring Jvm Garbage Collector Testing With Event-Coverage, Kai Zheng, Yingquan Zhao, Junjie Chen, Hanmo You, Haoyu Wang, Haoyu Wang, Tianchang Gao
Research Collection School Of Computing and Information Systems
Garbage Collection (GC) in the Java Virtual Machine (JVM) serves as an automatic memory management mechanism, efficiently reclaiming unused memory space in different production scenarios. To optimize JVM performance, developers typically fine-tune the garbage collector by identifying an optimal set of GC configurations for specific scenarios. Despite the sophisticated design of garbage collectors, they still have the potential for bugs in different settings, and these bugs can result in more severe consequences. Hence, comprehensive testing of these garbage collectors is imperative before their release. Code coverage criteria are typically employed to assess the comprehensiveness of a test suite. However, traditional …
Less Is More: Docstring Compression In Code Generation, Guang Yang, Yu Zhou, Wei Cheng, Xiangyu Zhang, Xiang Chen, Terry Yue Zhuo, Xin Zhou, Ke Liu, David Lo, Taolue Chen
Less Is More: Docstring Compression In Code Generation, Guang Yang, Yu Zhou, Wei Cheng, Xiangyu Zhang, Xiang Chen, Terry Yue Zhuo, Xin Zhou, Ke Liu, David Lo, Taolue Chen
Research Collection School Of Computing and Information Systems
The widespread use of Large Language Models (LLMs) in software engineering has intensified the need for improved model and resource efficiency. In particular, for neural code generation, LLMs are used to translate function/method signature and DocString to executable code. DocStrings, which capture user requirements for the code and are typically used as the prompt for LLMs, often contain redundant information. Recent advancements in prompt compression have shown promising results in Natural Language Processing (NLP), but their applicability to code generation remains uncertain. Our empirical study shows that the state-ofthe-art prompt compression methods achieve only about 10% reduction, as further reductions …
Constrained Pricing In Logit-Based Revenue Management, Qian Shao, Tien Mai, Shih-Fen Cheng
Constrained Pricing In Logit-Based Revenue Management, Qian Shao, Tien Mai, Shih-Fen Cheng
Research Collection School Of Computing and Information Systems
We consider a dynamic pricing problem in network revenue management in which customer behavior is predicted by a choice model, that is, the multinomial logit model. The problem, even in the static setting (i.e., customer demand remains unchanged over time), is highly nonconcave in prices. Existing studies mostly rely on the observation that the objective function is concave in terms of purchasing probabilities, implying that the static pricing problem with linear constraints on purchasing probabilities can be efficiently solved. However, this approach is limited in handling constraints on prices, noting that such constraints could be highly relevant in some real …
Fcghunter: Towards Evaluating Robustness Of Graph-Based Android Malware Detection, Shiwen Song, Xiaofei Xie, Ruitao Feng, Qi Guo, Sen Chen
Fcghunter: Towards Evaluating Robustness Of Graph-Based Android Malware Detection, Shiwen Song, Xiaofei Xie, Ruitao Feng, Qi Guo, Sen Chen
Research Collection School Of Computing and Information Systems
Graph-based detection methods leveraging Function Call Graph (FCG) have shown promise for Android malware detection (AMD) due to their semantic insights. However, the deployment of malware detectors in dynamic and hostile environments raises significant concerns about their robustness. While recent approaches evaluate the robustness of FCG-based detectors using adversarial attacks, their effectiveness is constrained by the vast perturbation space, particularly across diverse models and features. To address these challenges, we introduce FCGHunter, a novel robustness testing framework for FCG-based AMD systems. Specifically, FCGHunter employs innovative techniques to enhance exploration and exploitation within this huge search space. Initially, it identifies critical …
Zero-Shot Video Translation Via Token Warping, Haiming Zhu, Yangyang Xu, Jun Yu, Shengfeng He
Zero-Shot Video Translation Via Token Warping, Haiming Zhu, Yangyang Xu, Jun Yu, Shengfeng He
Research Collection School Of Computing and Information Systems
With the revolution of generative AI, video-related tasks have been widely studied. However, current state-of-the-art video models still lag behind image models in visual quality and user control over generated content. In this paper, we introduce TokenWarping, a novel framework for temporally coherent video translation. Existing diffusion-based video editing approaches rely solely on key and value patches in self-attention to ensure temporal consistency, often sacrificing the preservation of local and structural regions. Critically, these methods overlook the significance of the query patches in achieving accurate feature aggregation and temporal coherence. In contrast, TokenWarping leverages complementary token priors by constructing temporal …
Light Cone Cancellation For Variational Quantum Eigensolver In Solving Noisy Max-Cut, Xinwei Lee, Xinjian Yan, Ningyi Xie, Yoshiyuki Saito, Leo Kurosawa, Nobuyoshi Asai, Dongsheng Cai, Hoong Chuin Lau
Light Cone Cancellation For Variational Quantum Eigensolver In Solving Noisy Max-Cut, Xinwei Lee, Xinjian Yan, Ningyi Xie, Yoshiyuki Saito, Leo Kurosawa, Nobuyoshi Asai, Dongsheng Cai, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Variational Quantum Eigensolver (VQE) is a quantum-classical hybrid algorithm used to estimate the ground energy of a given Hamiltonian. It consists of a parameterized quantum circuit, which the parameters are optimized using a classical optimizer. With the increasing need in solving large-scale problems in real-world applications, solving those large problems with fewer qubits and fewer gates becomes essential, so that we reduce the simulation difficulty and mitigate the effect of noise in real quantum hardware. In this study, we applied the Light Cone Cancellation (LCC) method to reduce the number of qubits and gates required in a two-local ansatz. LCC …
Grounding Is All You Need? Dual Temporal Grounding For Video Dialog, You Qin, Wei Ji, Xinze Lan, Hao Fei, Xun Yang, Dan Guo, Roger Zimmermann, Lizi Liao
Grounding Is All You Need? Dual Temporal Grounding For Video Dialog, You Qin, Wei Ji, Xinze Lan, Hao Fei, Xun Yang, Dan Guo, Roger Zimmermann, Lizi Liao
Research Collection School Of Computing and Information Systems
In the realm of video dialog response generation, capturing both the essence of video content and the temporal nuances of conversation history is crucial. While some approaches rely on large-scale pretrained visual-language models, often neglecting temporal dynamics, others emphasize spatial-temporal relationships within videos but demand intricate object trajectory pre-extractions and overlook dialog temporal dynamics. This paper introduces the Dual Temporal Grounding-enhanced Video Dialog model (DTGVD), designed to bridge the gap between these two approaches. DTGVD uniquely integrates the strengths of both by emphasizing dual temporal relationships. It achieves this by predicting dialog turn-specific temporal regions, selectively filtering video content, and …
Learnable Game-Theoretic Policy Optimization For Data-Centric Self-Explanation Rationalization, Yunxiao Zhao, Zhiqiang Wang, Xingtong Yu, Xiaoli Li, Jiye Liang, Ru Li
Learnable Game-Theoretic Policy Optimization For Data-Centric Self-Explanation Rationalization, Yunxiao Zhao, Zhiqiang Wang, Xingtong Yu, Xiaoli Li, Jiye Liang, Ru Li
Research Collection School Of Computing and Information Systems
Rationalization, a data-centric framework, aims to build self-explanatory models to explain the prediction outcome by generating a subset of human-intelligible pieces of the input data. It involves a cooperative game model where a generator generates the most human-intelligible parts of the input (i.e., rationales), followed by a predictor that makes predictions based on these generated rationales. Conventional rationalization methods typically impose constraints via regularization terms to calibrate or penalize undesired generation. However, these methods are suffering from a problem called mode collapse, in which the predictor produces correct predictions yet the generator consistently outputs rationales with collapsed patterns. Moreover, existing …
Perceptions Of Game-Based Assessments: The Role Of Test Takers' Occupational Background, Marie L. Ohlms, Klaus G. Melchers, Filip Lievens
Perceptions Of Game-Based Assessments: The Role Of Test Takers' Occupational Background, Marie L. Ohlms, Klaus G. Melchers, Filip Lievens
Research Collection Lee Kong Chian School Of Business
Game-based assessments (GBAs) have become increasingly popular in personnel selection. However, research on perceptions of GBAs has yielded mixed results, highlighting the need to explore variables that may shape perceptions of GBAs. Therefore, we examined whether test takers' occupational background and other person-related characteristics (i.e., gender, age, video game usage, openness to experience) are associated with their perceptions of GBAs. N = 179 individuals from technical and social occupational backgrounds rated their perceptions of GBAs and non-gamified tests. We found that GBAs were generally rated more positively than non-gamified tests in terms of organizational attractiveness, behavioral intentions toward the organization, …
Design Principles For Customer-Engaging Digital Service Systems: An Action Research Study, Keng Leng Siau, Xiaofeng Chen, Xin Tan
Design Principles For Customer-Engaging Digital Service Systems: An Action Research Study, Keng Leng Siau, Xiaofeng Chen, Xin Tan
Research Collection School Of Computing and Information Systems
Digital services represent a business approach employed by organizations to operate in the digital environment. However, systematic development guidelines for developing quality digital service systems are lacking in the literature. The authors identified four general challenges for developing and implementing customer-engaging digital service systems (CEDSS). By employing the method of canonical action research in a digital service system project, they derived 10 design principles for developing high-quality CEDSS. They empirically evaluated the design principles in the development project and through follow-up focus group sessions. The design principles provide applicable and actionable guidelines for the development of CEDSS.
Choice-Based Crowdshipping For Next-Day Delivery Services: A Dynamic Task Display Problem, Alp Arslan, Firat Kilci, Shih-Fen Cheng, Archan Misra
Choice-Based Crowdshipping For Next-Day Delivery Services: A Dynamic Task Display Problem, Alp Arslan, Firat Kilci, Shih-Fen Cheng, Archan Misra
Research Collection School Of Computing and Information Systems
This paper studies integrating the crowd workforce into next-day home delivery services. In this setting, both crowd drivers and contract drivers collaborate in making deliveries. Crowd drivers have limited capacity and can choose not to deliver if the presented tasks do not align with their preferences. The central question addressed is: How can the platform minimize the total task fulfilment cost, which includes payouts to crowd drivers and additional payouts to contract drivers for delivering the unselected tasks by customizing task displays to crowd drivers? To tackle this problem, we formulate it as a finite-horizon Stochastic Decision Problem, capturing crowd …
Towards Secure Program Partitioning For Smart Contracts With Llm’S In-Context Learning, Ye Liu, Yuqing Niu, Chengyan Ma, Ruidong Han, Wei Ma, Yi Li, Debin Gao, David Lo
Towards Secure Program Partitioning For Smart Contracts With Llm’S In-Context Learning, Ye Liu, Yuqing Niu, Chengyan Ma, Ruidong Han, Wei Ma, Yi Li, Debin Gao, David Lo
Research Collection School Of Computing and Information Systems
Smart contracts are highly susceptible to manipulation attacks due to the leakage of sensitive information. Addressing manipulation vulnerabilities is particularly challenging because they stem from inherent data confidentiality issues rather than straightforward implementation bugs. To tackle this by preventing sensitive information leakage, we present PARTITIONGPT, the first LLM-driven approach that combines static analysis with the in-context learning capabilities of large language models (LLMs) to partition smart contracts into critical (privileged) and normal codebases, guided by a few annotated sensitive data variables. We evaluated PARTITIONGPT on 18 annotated smart contracts containing 99 sensitive functions. The results demonstrate that PARTITIONGPT successfully generates …
Qualitative Study For Llm-Assisted Design Study Process: Strategies, Challenges, And Roles, Shaolun Ruan, Rui Sheng, Xiaolin Wen, Jiachen Wang, Tianyi Zhang, Yong Wang, Tim Dwyer, Jiannan Li
Qualitative Study For Llm-Assisted Design Study Process: Strategies, Challenges, And Roles, Shaolun Ruan, Rui Sheng, Xiaolin Wen, Jiachen Wang, Tianyi Zhang, Yong Wang, Tim Dwyer, Jiannan Li
Research Collection School Of Computing and Information Systems
Design studies aim to develop visualization solutions for real-world problems across various application domains. Recently, the emergence of large language models (LLMs) has introduced new opportunities to enhance the design study process, providing capabilities such as creative problem-solving, data handling, and insightful analysis. However, despite their growing popularity, there remains a lack of systematic understanding of how LLMs can effectively assist researchers in visualization-specific design studies. In this paper, we conducted a rnulti-stage qualitative study to fill this gap, which involved 30 design study researchers from diverse backgrounds and expertise levels. Through in-depth interviews and carefully-designed questionnaires, we investigated strategies …
Artem: Enhancing Large Language Model Agents With Spatial-Temporal Episodic Memory, Cassandra Hui Ming Tan, Budhitama Subagdja, Ah-Hwee Tan
Artem: Enhancing Large Language Model Agents With Spatial-Temporal Episodic Memory, Cassandra Hui Ming Tan, Budhitama Subagdja, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Current large language models (LLMs) exhibit significant deficiencies in episodic memory tasks including encoding, storing, and retrieving specific information from temporally dependent events over a long period of time. Recent approaches to handle memory tasks in LLMs, such as in-context learning, retrieval-augmented generation (RAG), and fine-tuning, may resolve the long-term retention issues, but are still inadequate to handle tasks requiring chronological awareness of the stored information. We introduce Agentic Retrieval with Temporal-Episodic Memory (ARTEM), a hybrid LLM-based agent architecture integrating LLMs with a self-organizing neural network named Spatial-Temporal Episodic Memory (STEM), designed to handle episodic memory tasks. Our approach employs …
A Case Study Of Gender And Online Team Communication In Software Engineering Education, Rita Garcia, Christoph Treude
A Case Study Of Gender And Online Team Communication In Software Engineering Education, Rita Garcia, Christoph Treude
Research Collection School Of Computing and Information Systems
Collaboration is crucial in Software Engineering (SE), yet factors like gender bias can shape team dynamics and behaviours. This descriptive case study examines an eight-week project involving 39 SE students across eight teams contributing to GitHub projects. Focusing on gender, we used a mixed-methods approach to analyse Slack communications, identifying gender differences in how students respond to initiated communications and comparing how students’ communications influenced other aspects of students’ performance, including learning gains. We found higher help-seeking and leadership behaviours in the all-woman team involved in this case study, while men responded more slowly. Although communication did not directly affect …
Internationalization Struggles And Student Mobility: Ethnic Exclusion And Racism In Philippine Higher Education, Yasmin Y. Ortiga
Internationalization Struggles And Student Mobility: Ethnic Exclusion And Racism In Philippine Higher Education, Yasmin Y. Ortiga
Research Collection School of Social Sciences
There is an extensive literature on student mobility that seeks to understand the nature of, rationales for and consequences of internationalisation in higher education. This scholarship primarily focusses on students studying in the ‘west’. This paper shows how ‘atypical’ student destinations also illuminate the contradictions of internationalisation, revealing the challenges faced by higher education settings beyond academic centres in the west. Drawing on the case of the Philippines, I discuss how private universities actively recruited international students to maximise profits from student tuition. Yet, these efforts led to a backlash among Filipino educators and students, prompting administrators to institute policies …
Sports And Corporate Innovation, Bing Qin
Sports And Corporate Innovation, Bing Qin
Dissertations and Theses Collection (Open Access)
Driven by the digital economy and intensifying global competition, corporate innovation has become a core driver of sustainable growth. Topmanagement members are key strategic decision-makers, and their individual characteristics critically influence the formulation and implementation of innovation strategies. While existing studies have examined the impact of topmanagement’s cognitive and psychological traits on innovation performance, significant gaps remain in understanding how their routine behavioral preferences—particularly running, a globally prevalent exercise—affect innovation performance through psychological mechanisms. The systematic relationship between running preferences, top management’s psychological traits, and organizational innovation outcomes remains underexplored.
Against this backdrop, the study investigates the mechanismthroughwhich top management’s …