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Trading With The Enemy: A Coopetitive Perspective Of Resource Exchange At Arm’S Length, Zhefei Li, David Gomulya, Heli Wang Jan 2026

Trading With The Enemy: A Coopetitive Perspective Of Resource Exchange At Arm’S Length, Zhefei Li, David Gomulya, Heli Wang

Research Collection Lee Kong Chian School Of Business

Research Summary: Research on inter-firm cooperation often focuses on long-term strategic alliances while overlooking the distinct form of arm's-length resource exchanges. Our study addresses this gap using the National Basketball Association (NBA) data for precise resource exchange measurements. Contrary to strategic alliances, where competitive pressure fosters cooperation, we find that competitive pressure reduces cooperation in arm's-length exchanges. However, relational capital helps to facilitate resource exchanges. We also found that while resource bundling exacerbates the negative effect of competitive pressure, it amplifies the positive effect of relational capital. Interestingly, relational rivalry intensifies the impact of competitive pressure but does not diminish …

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Multihoming And Single-Homing Complementors' Responses To Intensified Between-Platform Competition: Evidence From The Youtube–Twitch Rivalry, Niloofar Abolfathi Jan 2026

Multihoming And Single-Homing Complementors' Responses To Intensified Between-Platform Competition: Evidence From The Youtube–Twitch Rivalry, Niloofar Abolfathi

Research Collection Lee Kong Chian School Of Business

Research Summary: This paper examines how heterogeneous YouTube content creators-specifically, single-homing and multihoming channels-respond to a sudden increase in the exposure of the rival platform, Twitch. Contrary to expectations, I find that multihoming channels reduce their content creation efforts and underperform relative to single-homers. To make sense of these surprising results, I develop a formal model that characterizes the strategic behavior of different types of complementors operating across two platforms with varying levels of user exposure. The model offers a plausible explanation for the observed empirical patterns, suggesting that intensified competition between platforms, as a consequence of their changing exposure, …

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Large Owner Expropriation Threat And Stock Option Pay's Effect On Firm Risk-­Taking Behaviors In Weak Institutions, Cuili Qian, Lipeng (Gary) Ge, Xuesong Geng, Jiatao Li, Maria Hasenhuttl Jan 2026

Large Owner Expropriation Threat And Stock Option Pay's Effect On Firm Risk-­Taking Behaviors In Weak Institutions, Cuili Qian, Lipeng (Gary) Ge, Xuesong Geng, Jiatao Li, Maria Hasenhuttl

Research Collection Lee Kong Chian School Of Business

Research Question/Issue: This study investigates the impact of managerial stock option pay on firm risk-­ taking behaviors in aweak institutional context, a critical question that has been overlooked by the literature. Specifically, we build on the comparative corporate governance perspective that emphasizes the implications of large shareholders' expropriation threat in weak institutions to develop predictions about their impact on the stock option's incentive alignment effect. We further explore the boundary conditions of such a relationship.Research Findings/Insights: Based on a sample of Chinese listed firms between 2006 and 2016, we find that a high level of large shareholders' expropriation threat weakens …

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Algorithm Envelopment In Platform Markets, Liang Chen, Zhou Zhou, Lester Chan Jan 2026

Algorithm Envelopment In Platform Markets, Liang Chen, Zhou Zhou, Lester Chan

Research Collection Lee Kong Chian School Of Business

The theory of platform envelopment rests on network effects as the key mechanism for value creation, which nonetheless receives mixed support for its efficacy in determining competitive outcomes. We argue that the value of network effects depends on matching quality, which is a function of platform-specific algorithm technology and market-level data-driven learning. In formalizing these conceptualizations, we analyze a model that demonstrates how an entrant with a superior algorithm technology may outcompete an incumbent possessing a user base advantage, a strategy we call “algorithm envelopment.” By considering specific characteristics of data-driven learning, our analysis leads to propositions regarding the entry …

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Shrinkflation And Consumer Demand, Aljoscha Janssen, Johannes Kasinger Jan 2026

Shrinkflation And Consumer Demand, Aljoscha Janssen, Johannes Kasinger

Research Collection School Of Economics

This study investigates shrinkflation—the practice of reducing product size while maintaining or slightly changing prices—in the U.S. retail grocery market. We analyze a decade of retail scanner data to assess the prevalence and patterns of product size changes across various product categories. Our findings show that approximately 1.92% of products have been downsized. When comparing total sales, product downsizing is more than five times as prevalent as upsizing. Product downsizing typically occurs without a corresponding decrease in price and is widespread across product categories. Consequently, consumers end up paying more per unit volume. We further find that consumers are more …

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Childlessness And Health In Middle Age And Older Adulthood: Evidence From Singapore, Christine Ho, Dahye Kim, Rohan Ray, Bussarawan Teerawichitchainan Jan 2026

Childlessness And Health In Middle Age And Older Adulthood: Evidence From Singapore, Christine Ho, Dahye Kim, Rohan Ray, Bussarawan Teerawichitchainan

Research Collection School Of Economics

Health and well-being in mature adulthood are important concerns given the prevalence of individuals aging without children. We exploit two new instruments for childlessness— infertility and the number of childless siblings—and condition our analyses on a rich set of covariates including childhood health and financial status, to investigate the causal relationship between childlessness and health in middle age and older adulthood. Using a nationwide dataset of 1,500 Singaporeans aged 50 and above, we show that OLS underestimates the negativeeffects of childlessness on health. We find that childlessness leads to higher likelihood of poorer self-reported health and mental distress. The results …

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Analysis Theories On Artificial Intelligence, Chatgpt, Data Science, And Metaverse: The Case Of Digital Medicine, Yin Yang, Xingyun Liu, Jorge Luis Cuyubamba Dominguez, Yuan Fang, Wen Xie, Bairong Shen, Keng Siau Jan 2026

Analysis Theories On Artificial Intelligence, Chatgpt, Data Science, And Metaverse: The Case Of Digital Medicine, Yin Yang, Xingyun Liu, Jorge Luis Cuyubamba Dominguez, Yuan Fang, Wen Xie, Bairong Shen, Keng Siau

Research Collection School Of Computing and Information Systems

Healthcare organizations are increasingly adopting digital technologies, with Artificial Intelligence (AI), Data Science, and the metaverse driving significant advancements in smart healthcare. Al facilitates personalized medicine and efficient drug development, while Data Science enables predictive analytics and big data management, enhancing patient outcomes and healthcare quality. The metaverse introduces immersive training and telemedicine platforms, revolutionizing patient engagement and healthcare research. This study conducts' a scoping review of 6,171 articles, analyzing the transformational impact of AI, ChatGPT, Data Science, and the metaverse on healthcare. It highlights the benefits and risks of these technologies, identifies research gaps in their application within the …

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Trajlens: Visual Analysis For Constructing Cell Developmental Trajectories In Cross-Sample Exploration, Qipeng Wang, Shaolun Ruan, Rui Sheng, Yong Wang, Min Zhu, Huamin Qu Jan 2026

Trajlens: Visual Analysis For Constructing Cell Developmental Trajectories In Cross-Sample Exploration, Qipeng Wang, Shaolun Ruan, Rui Sheng, Yong Wang, Min Zhu, Huamin Qu

Research Collection School Of Computing and Information Systems

Constructing cell developmental trajectories is a critical task in single-cell RNA sequencing (scRNA-seq) analysis, enabling the inference of potential cellular progression paths. However, current automated methods are limited to establishing cell developmental trajectories within individual samples, necessitating biologists to manually link cells across samples to construct complete cross-sample evolutionary trajectories that consider cellular spatial dynamics. This process demands substantial human effort due to the complex spatial correspondence between each pair of samples. To address this challenge, we first proposed a GNN-based model to predict cross-sample cell developmental trajectories. We then developed TrajLens, a visual analytics system that supports biologists in …

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Revisiting The Canonicalization For Fast And Accurate Crystal Tensor Property Prediction, Haowei Hua Hua, Jingwen Yang, Wanyu Lin, Pan Zhou Jan 2026

Revisiting The Canonicalization For Fast And Accurate Crystal Tensor Property Prediction, Haowei Hua Hua, Jingwen Yang, Wanyu Lin, Pan Zhou

Research Collection School Of Computing and Information Systems

Predicting the tensor properties of crystalline materials is a fundamental task in materials science. Unlike single-value property prediction, which is inherently invariant, tensor property prediction requires maintaining O(3) group tensor equivariance. Such equivariance constraint often requires specialized architecture designs to achieve effective predictions, inevitably introducing tremendous computational costs. Canonicalization, a classical technique for geometry, has recently been explored for efficient learning with symmetry. In this work, we revisit the problem of crystal tensor property prediction through the lens of canonicalization. Specifically, we demonstrate how polar decomposition, a simple yet efficient algebraic method, can serve as a form of canonicalization and …

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Uncovering Mild Drift In Asset Prices With Intraday High-Frequency Data, Shuping Shi, Peter C. B. Phillips Jan 2026

Uncovering Mild Drift In Asset Prices With Intraday High-Frequency Data, Shuping Shi, Peter C. B. Phillips

Research Collection School Of Economics

Asset prices are commonly represented as a drift-diffusion process, wherein the drift component denotes the anticipated return of the asset within some time frame, while the diffusion component accommodates random shocks. The drift component has substantial practical significance but accurate estimation is typically challenging and has met with limited success in the existing literature except over large time spans. This paper explores a comprehensive range of drift-diffusion models that include constant, linear, trending, and bursting drift. Conditions are identified under which realized squared drift  is a reliable tool for gauging integrated squared drift when the time span Tn is large …

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Assessing Ethereum’S Diversification Role With Bitcoin And Major Equity Index – A Bayesian Mixture Copula Approach, Jackie Li, Jacie Jia Liu Jan 2026

Assessing Ethereum’S Diversification Role With Bitcoin And Major Equity Index – A Bayesian Mixture Copula Approach, Jackie Li, Jacie Jia Liu

Research Collection School Of Economics

With the introduction of spot Ethereum ETFs, Ethereum plays an increasingly important role in the cryptocurrency market. In this paper, we propose a Bayesian modelling framework incorporating a mixture copula for co-modelling Ethereum returns with Bitcoin or FTSE 100 returns. The mixture copula is designed as a combination of the Clayton copula and its three rotations, Frank, and Gaussian copulas. It provides substantial flexibility for handling a variety of dependency structures. The Bayesian approach offers the advantage of jointly estimating both the margins and copulas and simulating future returns in a coherent procedure. Using 10 different risk or risk-return measures, …

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Dystop: Dynamic Staleness Control And Topology Construction For Asynchronous Decentralized Federated Learning, Yizhou Shi, Qianpiao Ma, Yan Xu, Junlong Zhou, Ming Hu, Yunming Liao Jan 2026

Dystop: Dynamic Staleness Control And Topology Construction For Asynchronous Decentralized Federated Learning, Yizhou Shi, Qianpiao Ma, Yan Xu, Junlong Zhou, Ming Hu, Yunming Liao

Research Collection School Of Computing and Information Systems

Federated Learning (FL) has emerged as a potential distributed learning paradigm that enables model training on edge devices (i.e., workers) while preserving data privacy. However, its reliance on a centralized server leads to limited scalability. Decentralized federated learning (DFL) eliminates the dependency on a centralized server by enabling peer-to-peer model exchange. Existing DFL mechanisms mainly employ synchronous communication, which may result in training inefficiencies under heterogeneous and dynamic edge environments. Although a few recent asynchronous DFL (ADFL) mechanisms have been proposed to address these issues, they typically yield stale model aggregation and frequent model transmission, leading to degraded training performance …

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Purified Zero-Shot Sketch-Based Image Retrieval, Yang Zhou, Jingru Yang, Jin Wang, Kaixiang Huang, Guodong Lu, Shengfeng He Jan 2026

Purified Zero-Shot Sketch-Based Image Retrieval, Yang Zhou, Jingru Yang, Jin Wang, Kaixiang Huang, Guodong Lu, Shengfeng He

Research Collection School Of Computing and Information Systems

Sketches, as a new solution in multimedia systems that can replace natural language, are characterized by sparse visual cues such as simple strokes that differ significantly from natural images containing complex elements such as background, foreground, and texture. This misalignment poses substantial challenges for zero-shot sketch-based image retrieval (ZS-SBIR). Prior approaches match sketches to full images and tend to overlook redundant elements in natural images, leading to model distraction and semantic ambiguity. To address this issue, we introduce a distraction-agnostic framework, purified cross-domain matching (PuXIM), which operates on a straightforward principle: masking and matching. We devise a visual-cross-linguistic (VxL) sampler …

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International Law, The Courts, And The Political Branches Of Singapore: Painting A Complete Picture, Benjamin Joshua Ong Jan 2026

International Law, The Courts, And The Political Branches Of Singapore: Painting A Complete Picture, Benjamin Joshua Ong

Research Collection Yong Pung How School Of Law

In line with Singapore's vision of the separation of powers, the courts' duty is primarily to give effect to domestic law; the political branches take the lead in engaging with international law. A study of Singapore's interface with international law would therefore be incomplete were it to consider only the courts' role and not the political branches' model of international law as primarily a guarantor of Singapore's sovereignty and standing as a participant on the international stage. The political branches have been circumspect in engaging with international law in other areas, such as human rights, preferring a specifically Singaporean vision …

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‘Salami Slicing’ And Issue Estoppel: Foreign Decisions On The Governing Law, Adeline Chong Jan 2026

‘Salami Slicing’ And Issue Estoppel: Foreign Decisions On The Governing Law, Adeline Chong

Research Collection Yong Pung How School Of Law

Whether an issue estoppel arises over foreign decisions on the governing law of the claim has not been directly considered by an English court, but decisions in other jurisdictions show that this question is increasingly being raised in litigation. Is there identity of issue if the two courts apply different choice of law rules? The answer turns on whether a broad or narrow framing of the issue is adopted. It is suggested that, absent an issue which is subject to forum international public policy, forum overriding mandatory rules or which is one that the forum court retains the prerogative to …

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The Shareholder’S Standing To Challenge The Exercise Of Directorial Power: Tianrui (International) Holding Company V China Shanshui Cement Group Ltd, Pearlie M. C. Koh Jan 2026

The Shareholder’S Standing To Challenge The Exercise Of Directorial Power: Tianrui (International) Holding Company V China Shanshui Cement Group Ltd, Pearlie M. C. Koh

Research Collection Yong Pung How School Of Law

An enduring problem with the proper purposes duty is the apparent right of the shareholder to enforce the same despite the duty being owed to the company. The cases on the proper purpose duty have thus far simply assumed the right of the shareholder to do so without dealing with the question of standing. In Tianrui (International) Holding Company Ltd v China Shanshui Cement Group Ltd, the Privy Council dealt with this issue directly and affirmed the shareholder's right to bring the action on the basis of the statutory contract constituted by the memorandum and articles of association of the …

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Smart Cities Beyond Methodological Cityism: Foregrounding Developmentalism, Scalar Flexing And The Rebranding Of The 'Urban', Prerona Das, Orlando Woods, Lily Kong Jan 2026

Smart Cities Beyond Methodological Cityism: Foregrounding Developmentalism, Scalar Flexing And The Rebranding Of The 'Urban', Prerona Das, Orlando Woods, Lily Kong

Research Collection College of Integrative Studies

In this paper we show that in Southeast Asia, smart city development has become a type of digital urban transformation that is not targeted towards any particular territorial formation or settlement. Instead, development-oriented states in the region leverage the smart city rhetoric as a nationwide branding strategy to leapfrog development stages. Such smart city policies are infused with a scalar logic – which we call ‘scalar flexing’ – that captures the enmeshing of local and national scales, causing local scale smart city initiatives to be stretched across wide-ranging, national-scale urban transformation agendas. We examine the nationwide 100 smart cities policies …

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How Do You Fix Knowledge In Place? Digital Nomads And Infrastructural Stickiness, Emma Grimley, Prerona Das, Orlando Woods, Lily Kong Jan 2026

How Do You Fix Knowledge In Place? Digital Nomads And Infrastructural Stickiness, Emma Grimley, Prerona Das, Orlando Woods, Lily Kong

Research Collection College of Integrative Studies

Remote work has become increasingly accessible due to the growing acceptance of remote work arrangements following the COVID-19 pandemic. Some state actors, especially in countries which face a shortage of digital talent and have reputations as leisure-tourism destinations, have begun considering the opportunities for digital transformation or workforce upskilling that highly skilled remote workers may offer. This paper develops the case of remote workers in Thailand to argue that infrastructural stickiness is a critical determinant for effective knowledge transfer to occur. By infrastructural stickiness we refer to the regulatory and socio-material infrastructures that both attract and retain international remote workers …

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Modelling Nature? The Digital Twinning And Untwinning Of Urban Farms, Prerona Das, Orlando Woods, Lily Kong Jan 2026

Modelling Nature? The Digital Twinning And Untwinning Of Urban Farms, Prerona Das, Orlando Woods, Lily Kong

Research Collection College of Integrative Studies

Data-driven solutions and innovations have been extended to various industries, including agriculture, to increase efficiency. With the emergence of smart farming and agriculture 4.0, advanced technologies such as IoT, big data, machine learning, and cloud computing are increasingly integrated into farming. Among these, technologies such as digital models, digital twins and the metaverse are now used to control various farming activities remotely based on real-time data. However agricultural ecosystems, involving uncertain nature-based factors and complex human-nature interactions cannot always be accurately represented or predicted by digital models. Digital models aim to reduce natural environments into controllable game-like situations and undermine …

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Walking Through Green And Grey: Exploring Sequential Exposure And Multisensory Environmental Effects On Psychological Restoration, Sifan Cheng, Binyu Lei, Kunihiko Fujiwara, Clayton Miller, Filip Biljecki, Jeroen Van Ameijde Jan 2026

Walking Through Green And Grey: Exploring Sequential Exposure And Multisensory Environmental Effects On Psychological Restoration, Sifan Cheng, Binyu Lei, Kunihiko Fujiwara, Clayton Miller, Filip Biljecki, Jeroen Van Ameijde

Research Collection College of Integrative Studies

Urban environments are increasingly recognised for their potential to support psychological restoration, yet most studies assess green and grey spaces in isolation and rely on static, lab-based measures. This study introduces a multi-layered analytical framework that integrates experimental walking, momentary perception tracking, and machine learning to investigate how multisensory urban features shape restoration. Conducted on a university campus, the experiment exposed 20 participants to sequential grey–green–grey walking routes. Restoration was measured through pre/post psychometric surveys, heart rate variability (HRV), and minute-level micro-surveys during walking. Results reveal three key insights: (1) green exposure induces a short-term “inoculation effect”, with restorative benefits …

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Multidimensional Analysis Of Human Outdoor Comfort: Integrating Just-In-Time Adaptive Interventions (Jitais) In Urban Digital Twins, Binyu Lei, Pengyuan Liu, Kunihiko Fujiwara, Mario Frei, Clayton Miller, Xuan Yun Chua, Filip Biljecki Jan 2026

Multidimensional Analysis Of Human Outdoor Comfort: Integrating Just-In-Time Adaptive Interventions (Jitais) In Urban Digital Twins, Binyu Lei, Pengyuan Liu, Kunihiko Fujiwara, Mario Frei, Clayton Miller, Xuan Yun Chua, Filip Biljecki

Research Collection College of Integrative Studies

How can bidirectional information exchange be enhanced in urban digital twins, and support human-centric data and processes? Their key characteristic is the nearly real-time exchange of information, allowing adjustments to physical environments based on simulations and analytics within virtual models. Yet, achieving such interaction remains challenging, particularly regarding device deployment and infrastructure development. Embracing the concept of humans as sensors, this work develops a two-way framework based on the emerging concept of just-in-time adaptive interventions (JITAIs), exploring how urban digital twins can play a role in understanding and enhancing human comfort outdoors. Human comfort outdoors is inherently spatio-temporal and personalised, …

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An Ex-Post Analysis Framework For Assessing The Effectiveness And Driving Factors Of Green Building Certification Adoption: A Case Study Of Singapore, Hao Gu, Xiaoyu Jin, Fu Xiao, Maomao Hu, Clayton Miller Jan 2026

An Ex-Post Analysis Framework For Assessing The Effectiveness And Driving Factors Of Green Building Certification Adoption: A Case Study Of Singapore, Hao Gu, Xiaoyu Jin, Fu Xiao, Maomao Hu, Clayton Miller

Research Collection College of Integrative Studies

Cities worldwide are adopting green building certification policies to meet sustainability and decarbonization targets in the building sector. However, the effectiveness of green certifications remains contested due to the difficulty of decomposing multiple influencing factors on building energy consumption. This study proposes an econometrics-based ex-post analysis framework to assess the effectiveness of green building certification policies in energy savings and identify driving factors by decomposing multiple influential factors. The proposed framework incorporates time-fixed effect models to examine factors driving the adoption of green building certifications, and causality analysis to quantify the effectiveness. Applying the framework to analyze a panel dataset …

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Relevance Between Strict Liability Theory And Banking Crimes In The Transfer Of Customer Funds: Negligence And Intent, Astrid Athina Indradewi, Evi Kongres, Ananda Chrisna D. Panjaitan, Evelyn Hutami Gunawarman Jan 2026

Relevance Between Strict Liability Theory And Banking Crimes In The Transfer Of Customer Funds: Negligence And Intent, Astrid Athina Indradewi, Evi Kongres, Ananda Chrisna D. Panjaitan, Evelyn Hutami Gunawarman

Research Collection Yong Pung How School Of Law

This article discusses the relevance of the Strict Liability theory to banking crimes in the transfer of customer funds involving elements of negligence as well as intent committed by bank managers. Strict liability places responsibility on the perpetrator without the need to prove fault, but rather by establishing a causal relationship between the act and the harm. In the context of civil law, Articles 1365 and 1367 of the Indonesian Civil Code recognize a form of liability resembling this concept through the mechanism of vicarious liability, whereby the bank as employer may be held liable for the unlawful acts of …

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Do Comments And Expertise Still Matter? An Experiment On Programmers’ Adoption Of Ai-Generated Javascript Code, Changwen Li, Christoph Treude, Ofir Turel Jan 2026

Do Comments And Expertise Still Matter? An Experiment On Programmers’ Adoption Of Ai-Generated Javascript Code, Changwen Li, Christoph Treude, Ofir Turel

Research Collection School Of Computing and Information Systems

This paper investigates the factors influencing programmers’ adoption of AI-generated JavaScript code recommendations within the context of lightweight, function-level programming tasks. It extends prior research by (1) utilizing objective (as opposed to the typically self-reported) measurements for programmers’ adoption of AI-generated code and (2) examining whether AI-generated comments added to code recommendations and development expertise drive AI-generated code adoption. We tested these potential drivers in an online experiment with 173 programmers. Participants were asked to answer some questions to demonstrate their level of development expertise. Then, they were asked to solve a LeetCode problem without AI support. After attempting to …

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Automatic Generation Of Introductory Programming Exercises With Large Language Models, Nguyen Binh Duong Ta, Hua Gia Phuc Nguyen, Gottipati Swapna Jan 2026

Automatic Generation Of Introductory Programming Exercises With Large Language Models, Nguyen Binh Duong Ta, Hua Gia Phuc Nguyen, Gottipati Swapna

Research Collection School Of Computing and Information Systems

Despite recent advances in code generation made possible by large language models (LLMs), programming is still an essential skill that computing students need to master now and in the foreseeable future. In learning programming, frequent practices with exercises set at an appropriate difficulty and knowledge level is of crucial importance for students. However, it’s not a trivial task for instructors to create many good quality exercises customized for each student. Programming problems found on Internet sources such as LeetCode are mostly too challenging for novice programmers with no prior coding knowledge. Recent work in AI-enabled education has been leveraging LLMs …

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Generalization Bounds For Semi‑Supervised Matrix Completion With Distributional Side Information, Antoine Ledent, Mun Chong Soo, Minh Hieu Nong Jan 2026

Generalization Bounds For Semi‑Supervised Matrix Completion With Distributional Side Information, Antoine Ledent, Mun Chong Soo, Minh Hieu Nong

Research Collection School Of Computing and Information Systems

We study a matrix completion problem where both the ground truth R matrix and the unknown sampling distribution P over observed entries are low-rank matrices, and share a common subspace. We assume that a large amount M of unlabeled data drawn from the sampling distribution P is available, together with a small amount N of labeled data drawn from the same distribution and noisy estimates of the corresponding ground truth entries. This setting is inspired by recommender systems scenarios where the unlabeled data corresponds to ‘implicit feedback’ (consisting in interactions such as purchase, click, etc. ) and the labeled data …

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Can We Read Ai’S Mind? A Quest For Transparency, Santhosh Kumar Ravindran, Estera Kot, Fiona Fui-Hoon Nah Jan 2026

Can We Read Ai’S Mind? A Quest For Transparency, Santhosh Kumar Ravindran, Estera Kot, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

Although Artificial Intelligence (AI) systems are playing an increasing role in critical domains such as healthcare, finance, and autonomous systems, their decision-making processes remain largely opaque. This paper examines the challenges of AI transparency, addressing the “black box” problem using Explainable AI (XAI) techniques such as SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME). It also examines the ethical, regulatory, and societal implications of AI opacity and proposes a Comprehensive AI Observability (CAO) Framework that integrates deep explainability, provenance tracking, and real-time monitoring to enhance AI accountability. By bridging technical solutions with governance structures, this research emphasizes the …

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Actor-Critic For Continuous Action Chunks: A Reinforcement Learning Framework For Long-Horizon Robotic Manipulation With Sparse Reward, Jiarui Yang, Bin Zhu, Jingjing Chen, Yu-Gang Jiang Jan 2026

Actor-Critic For Continuous Action Chunks: A Reinforcement Learning Framework For Long-Horizon Robotic Manipulation With Sparse Reward, Jiarui Yang, Bin Zhu, Jingjing Chen, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

Existing reinforcement learning (RL) methods struggle with long-horizon robotic manipulation tasks, particularly those involving sparse rewards. While action chunking is a promising paradigm for robotic manipulation, using RL to directly learn continuous action chunks in a stable and data-efficient manner remains a critical challenge. This paper introduces AC3 (Actor-Critic for Continuous Chunks), a novel RL framework that learns to generate high-dimensional, continuous action sequences. To make this learning process stable and dataefficient, AC3 incorporates targeted stabilization mechanisms for both the actor and the critic. First, to ensure reliable policy improvement, the actor is trained with an asymmetric update rule, learning …

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Interpretable Machine Learning For In-Home Mild Cognitive Impairment Detection, Budhitama Subagdja, Shanthoshigaa D, Ah-Hwee Tan, Iris Rawtaer Jan 2026

Interpretable Machine Learning For In-Home Mild Cognitive Impairment Detection, Budhitama Subagdja, Shanthoshigaa D, Ah-Hwee Tan, Iris Rawtaer

Research Collection School Of Computing and Information Systems

This paper introduces a novel system for in-home cognitive health assessment using ambient sensors and a machine learning technology that can robustly detect mild cognitive impairment (MCI) despite limited available data. The learned model can explain the aspects of individuals’ daily lives led to the prediction, while reliably predicting MCI, providing more insights to healthcare workers for further clinical interventions. We developed the robust transparent machine learning model, based on fusion adaptive resonance theory (Fusion ART) neural network to learn individuals’ daily patterns of activity from continuous sensor data in terms of a suite of digital biomarkers reflecting four key …

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Ai Systems For Physicians: A Review From Socio-Technical And Human-Computer Interaction Perspectives, Wu Jiaqi Young, Fiona Fui-Hoon Nah Jan 2026

Ai Systems For Physicians: A Review From Socio-Technical And Human-Computer Interaction Perspectives, Wu Jiaqi Young, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

The adoption of artificial intelligence (AI) in healthcare is accelerating, yet successful implementations of physician-facing AI systems remain limited and uneven. This paper presents a literature review of 40 peer-reviewed studies published between November 2022 and November 2024, spanning clinical, technical, and human-computer interaction (HCI) domains. Anchored in a socio-technical perspective, the review examines our existing understanding of how technical design, user expertise, and organizational factors shape the effectiveness of AI systems in real-world clinical settings. Our analysis identifies two meta-themes: (1) context as a dynamic, multi-level influence that actively reshapes AI system behavior, and (2) trust as an emergent …

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