Digital Commons Network^™

Towards Context-Aware Traffic Classification Via Time-Wavelet Fusion Network, Ziming Zhao, Zhuoxue Song, Xiaofei Xie, Zhaoxuan Li, Jiongchi Yu, Fan Terry Zhang, Tingting Li

Research Collection School Of Computing and Information Systems

Encrypted traffic classification occupies a significant role in cybersecurity and network management. The existing encrypted traffic classification technology mostly relies on intra-flow semantics for extracting features. However, considering that some attack behaviors inherently have similar patterns to legitimate behaviors, and powerful adversaries could simulate benign users to conceal their attack intentions, intra-flow features may be similar between different categories. In this paper, we propose TrafficScope, a time-wavelet fusion network based on Transformer to enhance the performance of encrypted traffic classification. Specifically, in addition to using intra-flow semantics, TrafficScope also extracts contextual information to construct more comprehensive representations. Moreover, to cope …

Cami: A Counselor Agent Supporting Motivational Interviewing Through State Inference And Topic Exploration, Yizhe Yang, Palakorn Achananuparp, Heyan Huang, Jing Jiang, Phey Ling Kit, Nicholas Gabriel Lim, Cameron Shi Ern Tan, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Conversational counselor agents have become essential tools for addressing the rising demand for scalable and accessible mental health support. This paper introduces CAMI, a novel automated counselor agent grounded in Motivational Interviewing (MI) – a client-centered counseling approach designed to address ambivalence and facilitate behavior change. CAMI employs a novel STAR framework, consisting of client’s state inference, motivation topic exploration, and response generation modules, leveraging large language models (LLMs). These components work together to evoke change talk, aligning with MI principles and improving counseling outcomes for diverse clients. We evaluate CAMI’s performance through both automated and expert evaluations, utilizing simulated …

Assessing The Robustness Of Test Selection Methods For Deep Neural Networks, Qiang Hu, Yuejun Guo, Xiaofei Xie, Maxime Cordy, Wei Ma, Mike Papadakis, Lei Ma, Yves Le Traon

Research Collection School Of Computing and Information Systems

Regularly testing deep learning-powered systems on newly collected data is critical to ensure their reliability, robustness, and efficacy in real-world applications. This process is demanding due to the significant time and human effort required for labeling new data. While test selection methods alleviate manual labor by labeling and evaluating only a subset of data while meeting testing criteria, we observe that such methods with reported promising results are simply evaluated, e.g., testing on original test data. The question arises: are they always reliable? In this article, we explore when and to what extent test selection methods fail. First, we identify …

Knowledge Boundary Of Large Language Models: A Survey, Moxin Li, Yong Zhao, Wenxuan Zhang, Shuaiyi Li, Wenya Xie, See-Kiong Ng, Tat-Seng Chua, Yang Deng

Research Collection School Of Computing and Information Systems

Although large language models (LLMs) store vast amount of knowledge in their parameters, they still have limitations in the memorization and utilization of certain knowledge, leading to undesired behaviors such as generating untruthful and inaccurate responses. This highlights the critical need to understand the knowledge boundary of LLMs, a concept that remains inadequately defined in existing research. In this survey, we propose a comprehensive definition of the LLM knowledge boundary and introduce a formalized taxonomy categorizing knowledge into four distinct types. Using this foundation, we systematically review the field through three key lenses: the motivation for studying LLM knowledge boundaries, …

Beware Of Your Po! Measuring And Mitigating Ai Safety Risks In Role-Play Fine-Tuning Of Llms, Weixiang Zhao, Yulin Hu, Yang Deng, Jiahe Guo, Xingyu Sui, Xinyang Han, An Zhang, Yanyan Zhao, Bing Qin, Tat-Seng Chua, Ting Liu

Research Collection School Of Computing and Information Systems

Although large language models (LLMs) store vast amount of knowledge in their parameters, they still have limitations in the memorization and utilization of certain knowledge, leading to undesired behaviors such as generating untruthful and inaccurate responses. This highlights the critical need to understand the knowledge boundary of LLMs, a concept that remains inadequately defined in existing research. In this survey, we propose a comprehensive definition of the LLM knowledge boundary and introduce a formalized taxonomy categorizing knowledge into four distinct types. Using this foundation, we systematically review the field through three key lenses: the motivation for studying LLM knowledge boundaries, …

Browsing Like Human: A Multimodal Web Agent With Experiential Fast-And-Slow Thinking, Haohao Luo, Jiayi Kuang, Wei Liu, Ying Shen, Jian Luan, Yang Deng

Research Collection School Of Computing and Information Systems

Automating web navigation which aims to build a web agent that follows user instructions to complete tasks like booking flights by interacting with websites, has received increasing attention due to its practical value. Although existing web agents are mostly equipped with visual perception, planning, and memory abilities, their reasoning process are still deviate from human cognition. In this work, we study the human thought pattern to empower agent with more human-like abilities in web navigation. To tackle this problem, we propose a novel multimodal web agent framework called WebExperT, which is designed to emulate the human planning process of “thinking …

Mpo: Multilingual Safety Alignment Via Reward Gap Optimization, Weixiang Zhao, Yulin Hu, Yang Deng, Tongtong Wu, Wenxuan Zhang, Jiahe Guo, An Zhang, Yanyan Zhao, Bing Qin, Tat-Seng Chua, Ting Liu

Research Collection School Of Computing and Information Systems

Large language models (LLMs) have become increasingly central to AI applications worldwide, necessitating robust multilingual safety alignment to ensure secure deployment across diverse linguistic contexts. Existing preference learning methods for safety alignment, such as RLHF and DPO, are primarily monolingual and struggle with noisy multilingual data. To address these limitations, we introduce Multilingual reward gaP Optimization (MPO), a novel approach that leverages the well-aligned safety capabilities of the dominant language (e.g., English) to improve safety alignment across multiple languages. MPO directly minimizes the reward gap difference between the dominant language and target languages, effectively transferring safety capabilities while preserving the …

Exploring Rehabilitation Therapists' Knowledge And Perspectives On The Use Of Artificial Intelligence And Machine Learning For Persons Poststroke, Hannah Clark, Mia Delvecchio, Min Hun Lee, Elena D. Brown, Kaia Mikula, Robert Halyama, Kasey Stepansky

Research Collection School Of Computing and Information Systems

Research Objectives: The use of technology such as robotics, gaming systems, self-monitoring apps, or other sensor-based devices in standard practice is infrequent. Due to the rapid development of artificial intelligence (AI) and machine learning (ML) applications, it is important to look at how therapists perceive AI/ML, and design applications with potential barriers in mind. to support future integration into practice. The purpose of this research project is to gain rehabilitation therapists’ perspectives on AI/ML in post-stroke assessment and intervention.Design: This ongoing study uses a mixed methods design with surveys and focus groups. Participants engaged in a 30-minute webinar to learn …

Dreamanime: Learning Style-Identity Textual Disentanglement For Anime And Beyond, Chenshu Xu, Yangyang Xu, Huaidong Zhang, Xuemiao Xu, Shengfeng He

Research Collection School Of Computing and Information Systems

Text-to-image generation models have significantly broadened the horizons of creative expression through the power of natural language. However, navigating these models to generate unique concepts, alter their appearance, or reimagine them in unfamiliar roles presents an intricate challenge. For instance, how can we exploit language-guided models to transpose an anime character into a different art style, or envision a beloved character in a radically different setting or role? This paper unveils a novel approach named DreamAnime, designed to provide this level of creative freedom. Using a minimal set of 2-3 images of a user-specified concept such as an anime character …

Research On The Relationship Between Manufacturing Process Digitalization And Product Quality Performance: A Case Study Of Discrete Manufacturing, Baozhong Zhang

Dissertations and Theses Collection (Open Access)

The study aims to explore the impact of digital transformation on product quality in discrete manufacturing enterprises. As the global economy and technology rapidly advance, the manufacturing industry faces unprecedented challenges and opportunities. Digital transformation has emerged as a key strategy for tackling these challenges and has become a significant trend in the manufacturing industry. The discrete manufacturing industry, which demands high product quality, faces even greater challenges in digital transformation. However, if discrete manufacturing enterprises successfully navigate this transformation, they can significantly improve quality, gain a competitive edge, and unlock even greater opportunities for their business.

The study combines …

Computational Fact-Checking With Limited Resources, Fengzhu Zeng

Dissertations and Theses Collection (Open Access)

The rapid dissemination of information through online platforms has sparked widespread concern about the propagation of misinformation. Manual fact-checking by pro- fessional fact-checkers is time-consuming and lacks scalability to address the vast volume of daily information. Consequently, computational fact-checking, driven by automated techniques in natural language processing (NLP), has garnered interest as
a potential solution. However, computational fact-checking faces critical challenges limited resources, particularly due to the issues of data scarcity and computing resource constraints. One key challenge is data scarcity, which arises from the constant generation of new information and emerging events on social media. This scarcity manifests in …

Being Seen And Being With Others: Shame And Interpersonal Relationships, Brandon Yip

Research Collection School of Social Sciences

I seek to vindicate heteronomous shame: shame that one experiences in response to a judgment from another that one does not accept. I suggest that such experiences are instances of interpersonal shame. This is shame that involves a sensitivity to interpersonal ideals, whose instantiation depends partly on the attitudes of others. I defend the importance of such shame by showing how vulnerability to others is a constitutive part of rich interpersonal relationships. The account both casts light on and vindicates the heteronomous shame that is pervasive among marginalised and oppressed groups. Such shame is not irrational but involves an accurate …

Socioeconomic Status Shapes Dyadic Interactions: Examining Behavioral And Physiologic Responses, Jacinth J. X. Tan, Tessa V. West, Wendy B. Mendes

Research Collection School of Social Sciences

With more opportunities for diverse interactions, little is known about how social interactions involving people of different socioeconomic status (SES) may unfold. We investigated social attunement patterns in dyadic interactions involving SES. Unacquainted individuals recruited from the community interacted with similar-or-different-SES partners in the lab (Ndyads = 130). Attunement was assessed throughout the interaction by examining physiological linkage—how much a person’s physiological change is predicted by another’s physiological change, over time. Overall, low-SES participants showed stronger physiological linkage—indicating greater attunement—to partners across SES. Participants also appeared more comfortable when interacting with low-SES partners. There were no SES differences in dominance …

Subjective Socioeconomic Status Moderates Self-Esteem Reactivity To Daily Stressor Exposure: Evidence From A Daily Diary Approach, Yi Jing Chua, Nadyanna M. Majeed, Verity Yu Qing Lua, Chi-Ying Cheng, Andree Hartanto

Research Collection School of Social Sciences

Research on self-esteem reactivity has demonstrated that self-esteem fluctuates in response to daily stressor exposure, and the strength of this relationship varies between individuals. Drawing upon the positive link between objective socioeconomic status (SES) and self-esteem, how subjective SES influences self-esteem reactivity to daily stressor exposure was explored. Using a 7-day daily diary study, the current study (N-participants = 243, N-days = 1651) adopted a multilevel analysis to demonstrate that subjective SES attenuated the within-person association between daily stressor exposure and daily self-esteem, even after controlling for demographics and objective indicators of SES. The interactions were also consistent across social …

A Lifespan Perspective On Positive Affect Fluctuations On Purpose In Life: Findings From A 9-Year Longitudinal Study, Jonathan L. Chia, Verity Y. Q. Lua, Andree Hartanto

Research Collection School of Social Sciences

Existing research has examined how static or average levels of positive affect (PA) influence purpose in life (PIL), but theoretical work suggests PA fluctuations may also play a role, potentially undermining PIL, especially in older adulthood. To this end, the present study examined the longitudinal association of PA fluctuations on PIL and the moderating role of age among 1,294 midlife and older adults in the United States, over a 9-year period (between 2004 and 2014). Results revealed a conditional effect of PA fluctuations on PIL – particularly among older individuals, and greater PA fluctuations were associated with a poorer sense …

Understanding The Physical Health Associations Of Intra-Individual Variability In Life Satisfaction Among Older Adults, Frosch Y. X. Quek, Kenneth Tan, David Chan

Research Collection School of Social Sciences

It is well established that inter-individual differences in life satisfaction positively predict health, but it is less clear how intra-individual variability in life satisfaction across time could influence health, particularly across individuals with different satisfaction levels. To address this gap, we analysed a large panel dataset from a national sample of 8,674 older adults, aged 50–70 (M = 59, SD = 5.42) in Singapore who completed surveys over 53 consecutive months. Results from multi-level modelling showed an interaction between variability in life satisfaction and life satisfaction mean on physical health. Specifically, there was no association between variability and health among …

3r-Stadte Furs Leben Gestalten [Designing 3r Cities For Life], Lily Kong

Research Collection School of Social Sciences

What does it mean for a city to be resilient in today’s world? In July this year, over 100 city leaders, scholars, and industry partners gathered at City Dialogues in Vienna, co-convened by Singapore Management University and Urban Innovation Vienna, to reflect on the critical question of urban resilience. Held alongside the Mayors Forum of the World Cities Summit 2025, the dialogue provided a timely opportunity to share how cities can navigate complexity—not only in response to disruption, but also in pursuit of sustainable and inclusive futures. Inspired by SMU City Dialogues, I explore here how cities can bounce back, …

Bridging Generations: Intergenerational Transfers And Time Use In A Changing World, Christine Ho

Research Collection School Of Economics

This Special Issue brings together nine papers that examine how families allocate time and money across generations. Spanning aging societies in East Asia to informal settlements in the Pacific, the contributions employ diverse methodological approaches, from natural experiments and policy variation to administrative data linkage and cross-generational panel surveys. The findings converge on a central insight: intergenerational transfers of time and money are not merely cultural practices, but systematic responses to changing economic environments and institutional frameworks. Family decisions are critical to the provision of long-term care, investment in children’s human capital, and the transmission of preferences, opportunities, and well-being …

A Three-Stage Matheuristic For The Blood Stochastic Inventory Routing Problem, Vincent F. Yu, Nabila Salsabila, Aldy Gunawan, Aldy Gunawan, Nurhadi Siswanto

Research Collection School Of Computing and Information Systems

This research introduces a blood distribution system under vendor-managed inventory that considers uncertain supply and demand. We present it as the Blood Stochastic Inventory Routing Problem, formulating it as a two-stage stochastic programming model. To solve this problem, this study proposes a three-stage matheuristic that combines a perturbation heuristic, Adaptive Large Neighborhood Search, and an exact approach. From historical data of Surabaya Blood Center in Indonesia, six sets of new instances are generated under different settings. Computational results show that our proposed three-stage matheuristic outperforms CPLEX and a two-stage matheuristic by gaining optimal or better solutions within a significantly shorter …

How To Enable Effective Cooperation Between Humans And Nlp Models: A Survey Of Principles, Formalizations, And Beyond, Chen Huang, Yang Deng, Wenqiang Lei, Jiancheng Lv, Tat-Seng Chua, Jimmy Huang

Research Collection School Of Computing and Information Systems

With the advancement of large language models (LLMs), intelligent models have evolved from mere tools to autonomous agents with their own goals and strategies for cooperating with humans. This evolution has birthed a novel paradigm in NLP, i.e., human-model cooperation, that has yielded remarkable progress in numerous NLP tasks in recent years. In this paper, we take the first step to present a thorough review of human-model cooperation, exploring its principles, formalizations, and open challenges. In particular, we introduce a new taxonomy that provides a unified perspective to summarize existing approaches. Also, we discuss potential frontier areas and their corresponding …

Fact-Audit: An Adaptive Multi-Agent Framework For Dynamic Fact-Checking Evaluation Of Large Language Models, Hongzhan Lin, Yang Deng, Yuxuan Gu, Wenxuan Zhang, Jing Ma, See-Kiong Ng, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Large Language Models (LLMs) have significantly advanced the fact-checking studies. However, existing automated fact-checking evaluation methods rely on static datasets and classification metrics, which fail to automatically evaluate the justification production and uncover the nuanced limitations of LLMs in fact-checking. In this work, we introduce FACT-AUDIT, an agent-driven framework that adaptively and dynamically assesses LLMs’ fact-checking capabilities. Leveraging importance sampling principles and multi-agent collaboration, FACT-AUDIT generates adaptive and scalable datasets, performs iterative model-centric evaluations, and updates assessments based on model-specific responses. By incorporating justification production alongside verdict prediction, this framework provides a comprehensive and evolving audit of LLMs’ factual reasoning …

Graph Positional Autoencoders As Self-Supervised Learners, Yang Liu, Deyu Bo, Wenxuan Cao, Yuan Fang, Yawen Li, Chuan Shi

Research Collection School Of Computing and Information Systems

Graph self-supervised learning seeks to learn effective graph representations without relying on labeled data. Among various approaches, graph autoencoders (GAEs) have gained significant attention for their efficiency and scalability. Typically, GAEs take incomplete graphs as input and predict missing elements, such as masked node features or edges. Although effective, our experimental investigation reveals that traditional feature or edge masking paradigms primarily capture low-frequency signals in the graph and fail to learn expressive structural information. To address these issues, we propose Graph Positional Autoencoders (GraphPAE), which employ a dual-path architecture to reconstruct both node features and positions. Specifically, the feature path …

Trust In Healthcare Ai Can’T Just Be Designed – It Must Be Felt By Clinicians And Patients, Adriana Banozic-Tang, Heng Wang

Research Collection Yong Pung How School Of Law

Trust in healthcare AI currently over-relies on system design, not lived medical realities.Continuous feedback loops are necessary to embed trust in healthcare AI that is responsive to clinician and patient needs.Initiatives in South-East Asia show how trust in technology can be extended from policy to practice.

Ai In The Judiciary: The Singapore Case, Nydia Remolina Leon

Research Collection Yong Pung How School Of Law

This paper examines the integration of Artificial Intelligence (AI) within the judicial system of Singapore. Singapore's judiciary has embraced AI not as a tool for adjudication, but as an augmentative instrument for legal research, procedural efficiency, and access to justice. It provides a detailed account of AI use cases in the courts, including case summarization, evidence review, assistance for selfrepresented litigants, and tools like the Divorce Assets Informative Division Estimator. The discussion then turns to the legal profession, exploring how law firms in Singapore are adopting AI technologies. The paper also addresses how AI implementation in the judicial system is …

On The Origin Of Green Finance Policies, Theodor Florian Cojoianu, D. French, Andrea G. F. Hoepner, Sheenan L., Anh Vu

Research Collection College of Integrative Studies

Despite the rising number of green finance policies, the socioeconomic determinants shaping them remain largely unexamined. Drawing from the literature analysing the relationship between regulation, market development and institutional economics, we contend that green finance policy adoption is driven by both market-based and institutional factors. Using a survival analysis approach to understand the levers influencing green finance policy adoption across 188 countries from 2000 to 2019, we find that exposure to the fossil fuel industry predominantly drives the initial issuance of green finance policies. The positive effect of fossil fuel commercial financing on the adoption of green finance policies exists …

Full Circle: Historiography, Missiology, And Theology In Lin Yutang’S From Pagan To Christian, Teng-Kuan Ng

Research Collection College of Integrative Studies

Lin Yutang (1895–1976) is renowned for bridging the Chinese and Western worlds through his prolific writings, but the vital role of religion in his intercultural endeavors remains underappreciated. This article situates his seminal work of religious reflection, From Pagan to Christian (1959), within the context of World Christianity, defined as both movement and method. Lin’s departure from the Christianity of his youth into Chinese religions—and back again to the church in his later years—presents timely insights for the study of religious change and pluralism in global modernity. Analyzing the text’s decolonizing, dialogical, and polyphonic dimensions, this article brings Lin’s spiritual …

Revealing Building Operating Carbon Dynamics For Multiple Cities, Winston Yap, Abraham Noah Wu, Clayton Miller, Filip Biljecki

Research Collection College of Integrative Studies

Achieving carbon neutrality is a critical yet elusive goal for many cities, hindered by limited understanding of the relationship between building emissions and their surroundings. To address this challenge, we present a generalizable open science framework that integrates building energy-consumption data, multi-modal geospatial inputs and graph deep learning to quantify building operating emissions and their links to urban form and socio-economic factors. Applying this approach to five cities with diverse climates and planning contexts—Melbourne, New York City (Manhattan), Seattle, Singapore and Washington DC—we demonstrate that our models explain 78.4% of the variation in building operating carbon emissions across cities, achieving …

Health And Weather In Unfavourable Environments: Exploring The Historical Dynamics Of Colonial Medical Meteorology In Nineteenth-Century Tropical Asia, Fiona Williamson

Research Collection College of Integrative Studies

Medical meteorology had a long precedent in medical thought across Eastern and Western traditions. This article considers the tradition of medical meteorology that was favoured by Western doctors in the nineteenth century, which was often applied within colonial contexts to the understanding of new climates and how they might impact on human health. Looking at British-held tropical and sub-tropical colonies of the Straits Settlements and Hong Kong respectively, medical meteorology was stimulated by the new pathological and atmospheric conditions that European explorers and settlers now inhabited in the name of the British Empire. They brought with them concepts of disease …

A Comprehensive Analysis Of Evolving Permission Usage In Android Apps: Trends, Threats, And Ecosystem Insights, Ali Alkinoon, Trung Cuong Dang, Ahod Alghuried, Abdulaziz Alghamdi, Soohyeon Choi, Manar Mohaisen, An Wang, Saeed Salem, David Mohaisen

Research Collection School Of Computing and Information Systems

The proper use of Android app permissions is crucial to the success and security of these apps. Users must agree to permission requests when installing or running their apps. Despite official Android platform documentation on proper permission usage, there are still many cases of permission abuse. This study provides a comprehensive analysis of the Android permission landscape, highlighting trends and patterns in permission requests across various applications from the Google Play Store. By distinguishing between benign and malicious applications, we uncover developers’ evolving strategies, with malicious apps increasingly requesting fewer permissions to evade detection, while benign apps request more to …

Other Orienteering Problem Variants, Pieter Vansteenwegen, Aldy Gunawan

Research Collection School Of Computing and Information Systems

In this chapter, different variants of routing problems with profits will be discussed. Based on what is available in literature, mostly variants of the orienteering problem will be discussed. A first variant considers capacity constraints, since these appear frequently in many practical applications. Next, multi-objective orienteering problems, explicitly considering different types of profits separately are discussed. Time-dependent and stochastic travel times are also relevant for most practical applications. These are considered together with time-dependent and stochastic profits. More and more routing problems are considered together with inventory management. For routing problems with profits, this leads to the inventory orienteering problem, …