Digital Commons Network^™

Predict Social Economic Outcomes By Transferred Knowledge With Satellite Imagery, Yang Tang, Shih-Fen Cheng, Yunqiang Zhu, Yichen Yang, Zhiqiang Zou

Research Collection School Of Computing and Information Systems

Traditional deep learning methods and econometric models have played a crucial role in the field of data mining, particularly in the prediction of socioeconomic outcomes. However, socio-economic information is unable to be directly extracted from remote sensing data. So, in this paper, we propose a method to leverage transfer learning to predict socioeconomic indicators (outcomes) through satellite imagery. Specifically, we use road network types as a proxy for socioeconomic factors, which is more effective and stable than using nightlight. We have extracted eleven distinct road topological features to generate reasonable road network types. Given the unique characteristics of road networks, …

Usefulness And Diminishing Returns: Evaluating Social Information In Recommender Systems, Qing Meng, Huiyu Min, Ming Shan Hee, Roy Ka-Wei Lee, Bing Tian Dai, Shuai Xu

Research Collection School Of Computing and Information Systems

Social recommendation, which leverages users’ social information to predict users’ preferences, is a popular branch of recommender systems. Many existing studies have attempted to advance the performance of collaborative filtering methods by leveraging the user-user matrix to enhance user embedding learning with user’s social connections. While the existing social recommender systems have demonstrated good performance in various recommendation tasks, the extent of social information usefulness in recommender systems remains unclear. This paper addresses the research gap by designing experiments to answer three research questions: (i) How useful is social information in varying user-item data sparsity? (ii) How much social information …

Intentionframe: A Semi-Structured, Multi-Aspect Framework For Fine-Grained Conversational Intention Understanding, Zailong Tian, Zhuoheng Han, Lizi Liao, Lizi Liao

Research Collection School Of Computing and Information Systems

Understanding user intentions in multi-turn dialogues is critical for conversational AI, yet existing approaches—relying on rigid slot-value structures or unstructured free-text—fail to fully capture conversational complexity. In this paper, we propose IntentionFrame, a semi-structured framework inspired by psychological and cognitive intention theories, which organizes conversational intents into four interrelated aspects: situation, emotion, action, and knowledge. This design not only retains interpretability but also provides LLMs with a rich context to accurately parse and respond to nuanced user inputs. To efficiently scale IntentionFrame annotations, we introduce a Weakly-supervised Reinforced Generation (WeRG) method that leverages a small set of high-quality human annotations …

Unified Molecule Pre-Training With Flexible 2d And 3d Modalities: Single And Paired Modality Integration, Tengwei Song, Min Wu, Yuan Fang

Research Collection School Of Computing and Information Systems

Molecular representation learning plays a crucial role in advancing applications such as drug discovery and material design. Existing work leverages 2D and 3D modalities of molecular information for pre-training, aiming to capture comprehensive structural and geometric insights. However, these methods require paired 2D and 3D molecular data to train the model effectively and prevent it from collapsing into a single modality, posing limitations in scenarios where a certain modality is unavailable or computationally expensive to generate. To overcome this limitation, we propose FlexMol, a flexible molecule pre-training framework that learns unified molecular representations while supporting single-modality input. Specifically, inspired by …

Metacan: Improving Generalizability Of Few‑Shot Anomaly Detection With Meta‑Learning, Zhisheng Lv, Jianfeng Zhang, Songlei Jian, Chenlin Huang, Hongguang Zhang, Guansong Pang, Zhong Liu

Research Collection School Of Computing and Information Systems

Few-shot Anomaly Detection (AD) for images aims to detect anomalies with few-shot normal samples from the target dataset. It is a crucial task when only few samples can be obtained, and it is challenging since it needs to be generalized to different domains. Existing methods try to enhance the generalizability of AD by incorporating large vision-language models (LVLMs).However, how to transform category semantic information in LVLMs into anomaly information to improve the generalizability of AD remains a challenge facing existing methods.To address the challenge, we propose a few-shot AD method called MetaCAN, a novel category-to-anomaly network trained with AD meta-learning …

International Workshop On Multimodal Generative Search And Recommendation (Mmgensr@Cikm 2025), Yi Bin, Haoxuan Li, Haokai Ma, Yang Zhang, Wenjie Wang, Yunshan Ma, Yang Yang, Tat‑Seng Chua

Research Collection School Of Computing and Information Systems

Recent breakthroughs in generative Artificial Intelligence (AI) have ignited a revolutionary wave across information retrieval and recommender systems. This workshop serves as a premier interdisciplinary platform to explore how generative models, particularly Large Language Models (LLMs) and Large Multimodal Models (LMMs), are transforming multimodal search and recommendation paradigms [3, 6, 9, 10, 12-14]. We aim to convene researchers and practitioners to discuss innovative architectures, methodologies, and evaluation strategies spanning generative document retrieval [5, 8] generative image retrieval [ 7, 16], grounded answer generation [17], generative recommendation [2, 4, 11], and related tasks involving multiple modalities [1,15]. The workshop will facilitate …

Gmm Estimation With Brownian Kernels Applied To Income Inequality Measurement, Jin Seo Cho, Peter C. B. Phillips

Research Collection School Of Economics

In GMM estimation, it is well known that if the moment dimension grows with the sample size, the asymptotics of GMM differ from the standard finite dimensional case. The present work examines the asymptotic properties of infinite dimensional GMM estimation when the weight matrix is formed by inverting Brownian motion or Brownian bridge covariance kernels. These kernels arise in econometric work such as minimum Cramér–von Mises distance estimation when testing distributional specification. The properties of GMM estimation are studied under different environments where the moment conditions converge to a smooth Gaussian or non-differentiable Gaussian process. Conditions are also developed for …

Judicial Review Of Prosecutorial Discretion: Missed Opportunities, Benjamin Joshua Ong

Research Collection Yong Pung How School Of Law

Director of Public Prosecutions v Durham (also called Bouye), decd and others [2024] UKPC 21; [2024] 1 W.L.R. 3900 involved an application for judicial review of a decision to prosecute. The Privy Council rightly refused that application on the ground that the evidence did not disclose a ground for judicial review, and the criminal trial would be the more appropriate forum to investigate any further evidence. Unfortunately, the Privy Council missed several opportunities to address various lingering problems with the law on judicial review of prosecutorial decisions.

Case Series Overview: Analysis Of Innovation Applications And Value Driven By Aigc Technology—An Early Investment Perspective In The Chinese Market, Siyuan Ma, Mengyu Wang, Tianyi Zhang

Sim Kee Boon Institute for Financial Economics

This case series explores the innovative applications and value analysis driven by AIGC (AI-generated content) technology from the perspective of early-stage investments in the Chinese market. We analyse the influence of core factors such as technology progression, market demand, policy environment, industry cycles and data on AIGC-driven value creation; case studies are provided to illustrate how AIGC has varying applications across different industries depending on market conditions. This series contains four cases: first, we first explore the investment opportunities of AIGC by combining the core technological value and industrial application status of generative AI, using China’s energy industry as a …

4 Of 4: Impact Of Policy And Technological Factors On Ai Innovation And Investment: The 2b Model Service Industry, Siyuan Ma, Mengyu Wang, Tianyi Zhang

Sim Kee Boon Institute for Financial Economics

This case explores AI investment opportunities in 2B model services, particularly in sectors that intrinsically benefit from the reduction in human error. We will analyse applications in the legal industry as an example of overarching 2B model service trends.

3 Of 4: Analysis Of Innovation Applications And Value Driven By Aigc Technology: An Early Investment Perspective In The Chinese Market, Siyuan Ma, Mengyu Wang, Tianyi Zhang

Sim Kee Boon Institute for Financial Economics

This case series explores the innovative applications and value analysis driven by AIGC (AI-generated content) technology from the perspective of early-stage investments in the Chinese market. We analyse the influence of core factors such as technology progression, market demand, policy environment, industry cycles and data on AIGC-driven value creation; case studies are provided to illustrate how AIGC has varying applications across different industries depending on market conditions. This series contains four cases: first, we first explore the investment opportunities of AIGC by combining the core technological value and industrial application status of generative AI, using China’s energy industry as a …

2 Of 4: Impact Of Human Resource Factors On Ai Investment: Ai In The Human Resource Market, Siyuan Ma, Mengyu Wang, Tianyi Zhang

Sim Kee Boon Institute for Financial Economics

This case will explore the implications that AIGC trends have on the development of the Chinese Human Resource (HR) market. While previous generation internet products were based on common needs and provided standardized products, the development of large AI models has opened doors to personalized custom products and services. Take AI applications in online education as an example: AI education models are developing to tailor to individual needs, since almost everything is not only digitalised but also based on dynamic database analysis for each user, including traffic distribution, sales conversion and service evaluation.

1 Of 4: Aigc Technology And Applications: Policy And Industry Development, Siyuan Ma, Mengyu Wang, Tianyi Zhang

Sim Kee Boon Institute for Financial Economics

This case explores the investment opportunities of AIGC by combining the core technological value and industrial application status of generative AI. We then analyse the impacts of these large-scale sectoral changes in a study of AI in China’s energy industry. We are currently in the early stage of the generative AI industry, thus it is analysed more from the perspective of early value investment, including trend investment opportunities brought by macro cycles, inflection point investment opportunities brought by industry transformation and application, and value creation brought by disruptive innovation. The early investment in the Chinese market is also at a …

Prrla Members Digital Preservation Landscape, Pin Pin Yeo, Suqing Liu, Pimnapa Amaritworachai

Research Collection Library

The research aimed to assess the current state of digital preservation practices among PRRLA (Pacific Rim Research Libraries Alliance) member libraries. A literature review on digital preservation in academic libraries was conducted. Information was gathered through surveys and interviews. focusing on policies, staffing, skills, funding, collection maintenance and services related to digital preservation. Additionally, the study explored the role of AI, and future trends in digital preservation. Challenges and best practices for sustainable digital preservation were highlighted.

Technical Appendix: Analysis Of Innovation Applications And Value Driven By Aigc Technology—An Early Investment Perspective In The Chinese Market, Siyuan Ma, Mengyu Wang, Tianyi Zhang

Sim Kee Boon Institute for Financial Economics

Following the introduction of generative AI/AIGC concepts and applications, it is necessary to clarify two related technical concepts: machine vision (CV) and convolutional neural networks (CNN). Computer Vision (CV) is a discipline that studies how to convert inputs such as images, sounds, and videos into a language that computers can understand. Taking 2D images as an example, all images can be broken down into very small pixels, each of which can be converted into a number (based on grayscale) or a combination of numbers. The number represented by each pixel is the feature of that pixel, and combining these numbers …

Marching To The Beat: The Role Of Complementor Alignment In The Architectural Evolution Of Ecosystems, Pengxiang Zhang, Liang Chen, Yang Yang

Research Collection Lee Kong Chian School Of Business

The evolution of innovation ecosystems hinges on the effective coordination between ecosystem leaders and complementors. While ecosystem-sponsored architectural innovations create new technological opportunities for complementors, they may unintentionally disrupt the performance of complementor products that were originally developed based on legacy architectural designs. This study provides empirical evidence of these disruptive effects and explores how complementors’ alignment with the ecosystem leader mitigates such challenges. Focusing on Apple’s release of Core ML—a proprietary artificial intelligence module—in its mobile ecosystem, we employ a difference-in-differences design to investigate variations in complementor performance after adopting this ecosystem-sponsored architectural innovation. Our findings reveal that complementors’ …

The Obsession With Staying On Track Is Holding Singapore Students Back, Kenneth T. Goh

Research Collection Lee Kong Chian School Of Business

In a commentary, SMU Associate Professor of Strategy & Entrepreneurship (Education) and Academic Director of SMU’s Business Families Institute Kenneth Goh, reflected on a former student who built a successful e-commerce business while studying, using his story to challenge Singapore’s “linear progression fallacy”. He argued that the education system reinforces this narrow view and stressed the need to value adaptability, experimentation, and creativity over rigid achievement. He called for reforms, concluding that Singapore should nurture a generation that values exploration and flexibility over simply staying “on track.”

The Impact Of A Vocational Training ‘Plus’ Programme On Employment And Income, Abu S. Shonchoy, Tomoki Fujii, Selim. Raihan

Research Collection School Of Economics

Following a Randomised Controlled Trial in Northern Bangladesh, this study explores the barriers to rural youth migration to urban employment hubs. By implementing a vocational training “plus” programme facilitating apparel sector employment, the study revealed significant and persistent effects of the programme on income and employment, primarily due to the addition of a stipend and on-the-job training components. Treated participants experienced significant income and remittance increases, alongside reduced income poverty, attributed to the lower job search costs and job–fit risks. Notably, the on-the-job paid apprenticeship offered a benefit–cost ratio of 8.85, demonstrating its cost-effectiveness for programme scalability.

The Motherhood Penalty On Health: Evidence From China, Ang Sun, Fang Xia, Xuan Zhang

Research Collection School Of Economics

Understanding women’s physical and mental well-being following childbirth is critical for informing policies on labor market equity, family support, and fertility. Using event study methods and panel data from China, we document a persistent motherhood penalty in both physical and mental health, whereas the health impacts on fathers are minimal. While mothers experience a temporary reduction in paid work hours, they face a sustained increase in unpaid domestic labor — housework and childcare — resulting in a net increase in total work time. This additional workload likely contributes to deterioration in health. Mothers are also more likely to engage in …

Personality And Personnel Selection: Going Beyond Self-Reports And Linear Relationships, Filip Lievens, Jinyan Fan, Jingyi Li

Research Collection Lee Kong Chian School Of Business

The study of personality in selection and assessment represents one of the most longstanding and voluminous literature in industrial and organizational psychology. In this paper, we review two important recent research streams. First, we review studies on alternatives to self-report personality inventories, namely the use of Situational Judgment Tests (SJTs), assessment center (AC) exercises, and a multi-rater framework. Second, we review studies that go beyond linear relationships between personality and job performance. Generally, our review reveals that these alternative approaches show promises in better understanding personality and how personality relates to performance.

Review Of Victor Fan, “Cinema Illuminating Reality: Media Philosophy Through Buddhism”, Teng-Kuan Ng

Research Collection College of Integrative Studies

This is a book review of Victor Fan, Cinema Illuminating Reality: Media Philosophy through Buddhism (Minneapolis: University of Minnesota Press, 2022)

A Comprehensive Review Of Financial Knowledge Graphs, Jeyaraman Brindha Priyadarshini, Bing Tian Dai, Yuan Fang

Research Collection School Of Computing and Information Systems

Knowledge Graphs (KGs) are increasingly used in finance to manage complex, interconnected data and support advanced analytics. This survey provides an overview of how KGs are applied across various financial areas, such as fraud detection, credit risk assessment, anti-money laundering, and regulatory compliance. We examine key techniques for building and using KGs in finance, including graph construction, embedding methods, and machine learning models. The survey also discusses challenges specific to finance, like handling private data, ensuring interpretability, and managing real-time data. Additionally, we explore the emerging combination of KGs with large language models and generative AI, which offers new possibilities …

Information Provision And Search Frictions: Evidence From The Taxi Industry In Singapore, Sumit Agarwal, Shih-Fen Cheng, Jussi Keppo, Long Wang, Yang Yang

Research Collection School Of Computing and Information Systems

Search frictions and misallocation are common in decentralized transportation markets. Using novel trip-level data of taxis in Singapore, this paper examines the impactof real-time demand information at airport terminals on search frictions. The information reduces taxi supply misallocation, increasing deadheading speed by 16.3% and decreasing deadheading time by 10.77%, benefiting both passengers and drivers. It raises daily earnings by $3.70 USD and adds 6.2 minutes of operational time per airport-trip taxi. Spatial spillovers are primarily observed among drivers in adjacentdistricts. Taxis from the Budget Terminal and drivers with fewer prior airport pickups benefit more from this information.

Conditional Attribute-Based Pre: Definition And Construction From Lwe, Lisha Yao, Jian Weng, Pengfei Wu, Guofeng Tang, Guomin Yang, Haiyang Xue, Robert H. Deng

Research Collection School Of Computing and Information Systems

Attribute-based proxy re-encryption (AB-PRE) is a crucial variant of proxy re-encryption. It allows a proxy with a re-encryption key to transform a delegator’s ciphertext associated with an access policy into another ciphertext associated with a new access policy, enabling delegatees with matching attributes to decrypt the transformed ciphertext. However, a key limitation of AB-PRE is that the delegator cannot control which ciphertexts are transformed. As a result, the proxy, once given the re-encryption key, indiscriminately transforms all ciphertexts, effectively switching their underlying policies—an issue known as the all-or-nothing problem. It limits the system’s flexibility and practicality in real-world use cases.In …

Stable Score Distillation, Haiming Zhu, Yangyang Xu, Chenshu Xu, Tingrui Shen, Wenxi Liu, Yong Du, Jun Yu, Shengfeng He

Research Collection School Of Computing and Information Systems

Text-guided image and 3D editing have advanced with diffusion-based models, yet methods like Delta Denoising Score often struggle with stability, spatial control, and editing strength. These limitations stem from reliance on complex auxiliary structures, which introduce conflicting optimization signals and restrict precise, localized edits. We introduce Stable Score Distillation (SSD), a streamlined framework that enhances stability and alignment in the editing process by anchoring a single classifier to the source prompt. Specifically, SSD utilizes Classifier-Free Guidance (CFG) equation to achieve cross-prompt alignment, and introduces a constant term null-text branch to stabilize the optimization process. This approach preserves the original content's …

Tactile Data Comics: Combining Step-By-Step Presentation Of Tactile Graphics With Verbal Narration For The Blind And Visually Impaired, Yang Jiao, Ruoting Sun, Rong Luo, Xiwen Yao, Xinran She, Kotaro Hara, Yuewen Zhang, Xinyi Fu

Research Collection School Of Computing and Information Systems

Tactile graphics on a refreshable display have proven effective in enabling visually impaired people to comprehend pictorial content. To further evaluate the effectiveness of refreshable tactile displays in blind education, we designed tactile data comics, a method that combines step-by-step presentation of tactile graphics with verbal narration. We conducted a user study with sixteen visually impaired students to compare tactile data comics against verbal-only and static tactile graphics. Our findings show that tactile data comics significantly improve participants’ comprehension and engagement during the learning experience. These empirical results suggest that the integration of refreshable tactile displays and tactile data comics …

Psychological Characteristics Of Board Secretaries And Information Disclosure Quality - An Empirical Analysis Based On The Questionnaire Survey And Interviews With Board Secretaries Of A-Share Listed Companies, Shuijun Dai

Dissertations and Theses Collection (Open Access)

The capital market functions fundamentally on the principles of information, and effective information disclosure acts as the cornerstone of its operation. At present, China's capital market is fully advancing the registration-based reform that is primarily focused on information disclosure. In this context, the secretary of the board of directors ("board secretary")—who serves as the legal officer tasked with overseeing information disclosure for A-share listed companies—plays a vital role in information release and transmission.

In the context of the comprehensive implementation of the registration system and establishment of an investor-oriented capital market, this study surveys over 400 board secretaries from A-share …

Availability Of Esg Rating Information And Voluntary Esg Disclosure: Evidence From Coverage Expansion Of Esg Rating Agency, Xuefan Peng

Dissertations and Theses Collection (Open Access)

I examine the effect of availability of ESG rating information on firms’ voluntary ESG disclosure practices. Thomson Reuters Asset4 expanded ESG rating coverage from Russell 1000 index to Russell 2000 index in 2017. Exploiting this exogenous shock of availability of ESG rating information in a difference-in-difference research design, I find that compared with Russell 1000 firms (i.e., control firms), Russell 2000 firms (i.e., treatment firms) are less likely to increase voluntary ESG disclosures. The effect is more pronounced for firms with higher disclosure costs, captured by higher level of firm complexity and lower level of digitalization, and less pronounced for …

Investigating Organisational Ethical Transgressions: A Middle Management Perspective, Belinda Kit Wah Boey

Dissertations and Theses Collection (Open Access)

This study questions how large-scale ethical transgressions persist within organisations by focusing on the pivotal yet underexamined role of middle managers. Positioned between senior leadership and frontline employees, middle managers often determine the trajectory of reported misconduct. By analysing their responses to ethical concerns raised by subordinates, the study seeks to illuminate the processes that sustain or interrupt organisational inaction.

Using grounded theory methodology, in-depth interviews were conducted with middle managers across diverse sectors. The analysis yields a typology of five distinct handling strategies: creative compliance, face-saving resolution, informal influence, formal escalation, and strategic withdrawal. …

Report On Assessing The Digital Preservation Landscape And Capacity Of Prrla Libraries, Pin Pin Yeo, Suqing Liu, Pimnapa Amaritworachai

Research Collection Library

This project evaluated the current state of digital preservation practices among PRRLA (Pacific Rim Research Libraries Alliance) member libraries. This report outlined the best practices and guidelines of the member libraries. The study involved a literature review to examine existing research and practices in digital preservation. A survey was designed to collect detailed information from PRRLA members, complemented by online interviews with selected institutions to gain deeper insights. The report has the key findings, successful strategies with some suggestions for sustainable development of digital preservation.