Digital Commons Network^™

Towards Multimodal Emotional Support Conversation Systems, Yuqi Chu, Lizi Liao, Zhiyuan Zhou, Chong-Wah Ngo, Richang Hong

Research Collection School Of Computing and Information Systems

The integration of conversational artificial intelligence (AI) into mental health care promises a new horizon for therapist-client interactions, aiming to closely emulate the depth and nuance of human conversations. Despite the potential, the current landscape of conversational AI is markedly limited by its reliance on single-modal data, constraining the systems’ ability to empathize and provide effective emotional support. This limitation stems from a paucity of resources that encapsulate the multimodal nature of human communication essential for therapeutic counseling. To address this gap, we introduce the Multimodal Emotional Support Conversation (MESC) dataset, a first-of-its-kind resource enriched with comprehensive annotations across text, …

Finding Safety Violations Of Ai-Enabled Control Systems Through The Lens Of Synthesized Proxy Programs, Jieke Shi, Zhou Yang, Junda He, Bowen Xu, Dongsun Kim, Donggyun Han, David Lo

Research Collection School Of Computing and Information Systems

Given the increasing adoption of modern AI-enabled control systems, ensuring their safety and reliability has become a critical task in software testing. One prevalent approach to testing control systems is falsification, which aims to find an input signal that causes the control system to violate a formal safety specification using optimization algorithms. However, applying falsification to AI-enabled control systems poses two significant challenges: (1) it requires the system to execute numerous candidate test inputs, which can be time-consuming, particularly for systems with AI models that have many parameters, and (2) multiple safety requirements are typically defined as a conjunctive specification, …

Max-Share Misidentification, Liyu Dou, Paul Ho, Thomas Lubik

Research Collection School Of Economics

While max-share identiffcation has become increasingly popular in a wide range of applications, we show that its validity requires necessary and suffffcient conditions that are rarely satisffed in practice—the target variable’s response to the target shock must be (i) orthogonal to its responses to untargeted shocks and (ii) larger than combinations of those responses. Imposing additional restrictions on the target shock weakens but does not fully eliminate these conditions. We show that in practice, the weight max-share places on an identiffed untargeted shock can be obtained by projecting the response to that shock on the max-share response. We also theoretically …

Speculative Bubbles In The Recent Ai Boom: Nasdaq And The Magnificent Seven, Rerotlhe B. Basele, Peter C. B. Phillips, Shuping Shi

Research Collection School Of Economics

The recent artificial intelligence (AI) boom covers a period of rapid innovation and wide adoption of AI intelligence technologies across diverse industries. These developments have fueled an unprecedented frenzy in the Nasdaq, with AI-focused companies experiencing soaring stock prices that raise concerns about speculative bubbles and real-economy consequences. Against this background, this study investigates the formation of speculative bubbles in the Nasdaq stock market with a specific focus on the so-called Magnificent Seven (Mag-7) individual stocks during the AI boom, spanning the period from January 2017 to January 2025. We apply the real-time PSY bubble detection methodology of Phillips et …

Learning Camp, Language Of Instruction, And Education Outcomes: Evidence From A Field Experiment In Malawi, Hyuncheol Bryant. Kim, Kim

Research Collection School Of Economics

We conducted a randomized experiment to study the impacts of a summer learning camp and the language of instruction on education outcomes. The program, covering social studies and mathematics, provided additional high-quality learning time for 4th and 5th graders in Malawi. The program significantly increased test scores in social studies and mathematics (0.24–0.36 standard deviations). We find suggestive evidence that the impact on test scores in social studies was greater for students instructed in Chichewa, the local language, than for those instructed in English. However, we find no such evidence of differential impacts on test scores in mathematics by the …

How To Strengthen The International Competitiveness Of Capital Markets, Aurelio Gurrea-Martinez

Research Collection Yong Pung How School Of Law

Global capital markets are undergoing profound transformation. Over the past decade, there has been a marked decline in Initial Public Offerings (IPOs) in most advanced economies, including those with highly developed capital markets such as the United Kingdom and the United States. Interestingly, during the same period, countries like Indonesia, Malaysia, Thailand, and particularly China have witnessed a significant increase in the number of listed companies, contributing to making Asia home to approximately 55 percent of all listed companies worldwide (OECD, 2025). Much of the decline in IPO activity in many advanced economies can be attributed to the expansion of …

(When) Can Trade Wars Be Good?, Henry S. Gao, Weihuan Zhou

Research Collection Yong Pung How School Of Law

‘Trade wars are good, and easy to win,’ tweeted Donald Trump in 2018. The US–China trade war that followed proved otherwise – especially when confronting a major economic power. Yet, can trade wars ever be good? While the academic consensus holds they harm all participants, we argue that under certain circumstances they can produce positive outcomes. Set against the backdrop of the Liberation Day tariffs announced on April 2, 2025, this paper examines the limits of the Ricardian free trade model underpinning the current multilateral trading system, identifies when trade wars may serve strategic goals, and explores alternative rules to …

A Commitment Rule For Insolvency Forum: A Response To Critics, Anthony J. Casey, Aurelio Gurrea-Martinez, Robert K. Rasmussen

Research Collection Yong Pung How School Of Law

On September 14, 2023, we sent a letter to the Secretariat of the United Nations Commission on International Trade Law (“UNCITRAL”) Working Group V (Insolvency) expressing our concern about the concept of “Center of Main Interest” (“COMI”) adopted in the Model Law on Cross-Border Insolvency (“Model Law”).1 We noted that the concept of COMI presents various weaknesses.

Ponzilens+: Visualizing Bytecode Actions For Smart Ponzi Scheme Identification, Xiaolin Wen, Tai D. Nguyen, Shaolun Ruan, Qiaomu Shen, Jun Sun, Feida Zhu, Yong Wang

Research Collection School Of Computing and Information Systems

With the prevalence of smart contracts, smart Ponzi schemes have become a common fraud on blockchain and have caused significant financial loss to cryptocurrency investors in the past few years. Despite the critical importance of detecting smart Ponzi schemes, a reliable and transparent identification approach adaptive to various smart Ponzi schemes is still missing. To fill the research gap, we first extract semantic-meaningful actions to represent the execution behaviors specified in smart contract bytecodes, which are derived from a literature review and in-depth interviews with domain experts. We then propose PonziLens+, a novel visual analytic approach that provides an intuitive …

Government Vicarious Liability And The Concept Of Deemed Equality With Private Persons, Gary K. Y. Chan

Research Collection Yong Pung How School Of Law

The immunity against Crown liability was abolished in the United Kingdom in 1948 based on the Diceyan notion of rule of law and deemed equality under the law between public officials and private persons. This paper analyses government vicarious liability in respect of the acts and omissions of public officers under the Singapore Government Proceedings Act with reference to the concept of deemed equality. We will discuss the scope of the statute in light of recent common law developments in vicarious liability, statutory exceptions to government vicarious liability that may be justified by the functions of the government in the …

Death Penalty For Drug Offenders In Southeast Asia: Weakening Of Resistance To Change?, Wing Cheong Chan

Research Collection Yong Pung How School Of Law

Although the global movement towards abolition of the death penalty has been supported by an increasing number of countries in the world, the number of persons executed for drug offences actually increased in the last few years. Known executions for drug offences now account for more than 40 per cent of all global executions. Most such executions take place in Asia. Of the 34 countries in the world that still retain the death penalty for drug offenders, all nine of those identified as “high application states” (China, Indonesia, Iran, Kuwait, Malaysia, North Korea, Saudi Arabia, Singapore and Vietnam) are found …

Deep Graph Anomaly Detection: A Survey And New Perspectives, Hezhe Qiao, Hanghang Tong, Nanyang Technological University, Irwin King, Charu Aggarwal, Guansong Pang

Research Collection School Of Computing and Information Systems

Graph anomaly detection (GAD), which aims to identify unusual graph instances (e.g., nodes, edges, subgraphs, or graphs), has attracted increasing attention in recent years due to its significance in a wide range of applications. Deep learning approaches, graph neural networks (GNNs) in particular, have been emerging as a promising paradigm for GAD, owing to its strong capability in capturing complex structure and/or node attributes in graph data. Considering the large number of methods proposed for GNN-based GAD, it is of paramount importance to summarize the methodologies and findings in the existing GAD studies, so that we can pinpoint effective model …

Probabilistic Modeling, Learnability And Uncertainty Estimation For Interaction Prediction In Movie Rating Datasets, Jennifer Poernomo, Nicole Gabrielle Lee Tan, Rodrigo Alves, Antoine Ledent

Research Collection School Of Computing and Information Systems

In this paper, we examine the hypothesis that the interactions recorded in many Recommendation Systems datasets are distributed according to a low-rank distribution, i.e. a mixture of factorizable distributions. Surprisingly, we find that on several popular datasets, a simple non-negative matrix factorization method equals or outperforms more modern methods such as LightGCN, which indicates that the sampling distribution over interactions is indeed low-rank. Furthermore, we mathematically prove that low-rank distributions are learnable with a sparse number of observations (where m/n and r refer to the number of users/items and the non-negative rank respectively) both in terms of the total variation …

Recurrent Autoregressive Linear Model For Next-Basket Recommendation, Tereza Zmeskalova, Antoine Ledent, Martin Spisak, Pavel Kordik, Rodrigo Alves

Research Collection School Of Computing and Information Systems

Next-basket recommendation aims to predict the (sets of) items that a user is most likely to purchase during their next visit, capturing both short-term sequential patterns and long-term user preferences. However, effectively modeling these dynamics remains a challenge for traditional methods, which often struggle with interpretability and computational efficiency, particularly when dealing with intricate temporal dependencies and inter-item relationships. In this paper, we propose ReALM, a Recurrent Autoregressive Linear Model that explicitly captures temporal item-to-item dependencies across multiple time steps. By leveraging a recurrent loss function and a closed-form optimization solution, our approach offers both interpretability and scalability while maintaining …

Privacy-Preserving Ridge Regression Over Encrypted Data Under Multiple Keys, Yanling Li, Junzuo Lai, Meng Sun, Beibei Song, Robert H. Deng

Research Collection School Of Computing and Information Systems

With the increase of private data being collected by data owners, it has been a trend for data owners to store the data on cloud computing platforms. The huge amounts of data in cloud servers bring fresh development opportunities to machine learning, which is applied to build a high-quality machine learning model based on a large training dataset. However, to ensure the privacy of data and facilitate retrieval, data owners often upload encrypted data under their public keys. But it creates new challenges for machine learning to learn a predictive model over these encrypted data under different keys. Most existing …

Apidocbooster: An Extract-Then-Abstract Framework Leveraging Large Language Models For Augmenting Api Documentation, Chengran Yang, Jiakun Liu, Bowen Xu, Christoph Treude, Yunbo Lyu, Junda He, Ming Li, David Lo

Research Collection School Of Computing and Information Systems

API documentation is often the most trusted resource for programming. Many approaches have been proposed to augment API documentation by summarizing complementary information from external resources such as Stack Overflow. Existing extractive-based summarization approaches excel in producing faithful summaries that accurately represent the source content without input length restrictions. Nevertheless, they suffer from inherent readability limitations. On the other hand, our empirical study on the abstractive-based summarization method, i.e., GPT-4, reveals that GPT-4 can generate coherent and concise summaries but presents limitations in terms of informativeness and faithfulness. We introduce APIDocBooster, an extract-then-abstract framework that seamlessly fuses the advantages of …

Studying Satd In Drone Systems With Human-Ai Collaboration, Leevi Rantala, Lwin Khin Shar, Mäntylä Mika V., Wei Minn, Naing Tun Yan

Research Collection School Of Computing and Information Systems

Background: Self-Admitted Technical Debt (SATD) refers to sub-optimal solutions that developers acknowledge within the source code. SATD research originated on Java projects but is expanding to other domains. We focus on SATD in drones, which are used for various critical tasks.Aims: The primary objective is to investigate SATD in drone systems. The second aim is to explore the integration of AI and human collaboration for SATD labelling and classification.Method: We conducted a sample study of SATD comments in drone systems (14 open source, 4 SDKs) to analyse the quantity and types of SATD comments present. Our study incorporates collaboration between …

Map As A By-Product: Collective Landmark Mapping From Imu Data And User-Provided Texts In Situated Tasks, Ryo Yonetani, Kotaro Hara

Research Collection School Of Computing and Information Systems

This paper presents Collective Landmark Mapper, a novel map-as-a-by-product system for generating semantic landmark maps of indoor environments. Consider users engaged in situated tasks that require them to navigate these environments and regularly take notes on their smartphones. Collective Landmark Mapper exploits the smartphone's IMU data and the user's free text input during these tasks to identify a set of landmarks encountered by the user. The identified landmarks are then aggregated across multiple users to generate a unified map representing the positions and semantic information of all landmarks. In developing the proposed system, we focused specifically on retail applications and …

Guiding Multiple Remote Users In Physical Tasks With Language-Driven Robotic Telepresence, Ruyi Li, Jingfei Guo, Xinyi Zhang, Xuji Zhang, Zeqing Li, Jiannan Li, Jiangtao Gong

Research Collection School Of Computing and Information Systems

Remote assistance through robotic telepresence could involve both control and memory challenges, particularly in one expert to multiple workers situation. In this work, we proposed a novelty language-driven interface to facilitate remote collaboration through telepresence robots. Through operations and maintenance expert interviews and a scenario simulation study, we identified key pain points in executing one-expert-multiple-workers remote guidance using the telepresence robot and proposed two design goals, which together consist of five sub-design goals with corresponding features. These features were integrated into a standard telepresence robot, resulting in the development of a Collaborative LLM-based Embodied Assistant Robot, named CLEAR Robot. A …

Implementing Slack-Free Custom Penalty Function For Qubo On Gate-Based Quantum Computers, Xin Wei Lee, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Solving NP-hard constrained combinatorial optimization problems using quantum algorithms remains a challenging yet promising avenue toward quantum advantage. Variational Quantum Algorithms (VQAs), such as the Variational Quantum Eigensolver (VQE), typically require constrained problems to be reformulated as unconstrained ones using penalty methods. A common approach introduces slack variables and quadratic penalties in the QUBO formulation to handle inequality constraints. However, this leads to increased qubit requirements and often distorts the optimization landscape, making it harder to find high-quality feasible solutions. To address these issues, we explore a slack-free formulation that directly encodes inequality constraints using custom penalty functions, specifically the …

Conv4rec: A 1‑By‑1 Convolutional Autoencoder For User Profiling Through Joint Analysis Of Implicit And Explicit Feedbacks, Antoine Ledent, Petr Kasalický, Rodrigo Alves, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

We introduce a new convolutional autoencoder architecture for user modeling and recommendation tasks with several improvements over the state of the art. First, our model has the flexibility to learn a set of associations and combinations between different interaction types in a way that carries over to each user and item. Second, our model is able to learn jointly from both the explicit ratings and the implicit information in the sampling pattern (which we refer to as ”implicit feedback”). It can also make separate predictions for the probability of consuming content and the likelihood of granting it a high rating …

Reimagining U.S. Tort Law For Deepfake Harms: Comparative Insights From China And Singapore, Huijuan Peng, Pey Woan Lee

Research Collection Yong Pung How School Of Law

This Article explores how U.S. tort law can respond more effectively to the distinct harms posed by deepfakes, including reputational injury, identity appropriation, and emotional distress. Traditional tort doctrines, such as defamation, the right of publicity, and intentional infliction of emotional distress (IIED), remain fragmented and ill-suited to the speed, scale, and anonymity of deepfake dissemination. Using a comparative functionalist approach, the Article analyzes how China and Singapore respond to deepfake harms through structurally divergent but functionally instructive frameworks. China’s model combines codified personality rights with intermediary obligations under a civil law regime, while Singapore adopts a hybrid approach that …

Robface: A Test Suite For Efficient Robustness Evaluation Of Face Recognition Systems, Ruihan Zhang, Jun Sun

Research Collection School Of Computing and Information Systems

Face recognition is a widely used authentication technology in practice, where robustness is required. It is thus essential to have an efficient and easy-to-use method for evaluating the robustness of (possibly third-party) trained face recognition systems. Existing approaches to evaluating the robustness of face recognition systems are either based on empirical evaluation (e.g., measuring attacking success rate using state-of-the-art attacking methods) or formal analysis (e.g., measuring the Lipschitz constant). While the former demands significant user efforts and expertise, the latter is extremely time-consuming. In pursuit of a comprehensive, efficient, easy-to-use, and scalable estimation of the robustness of face recognition systems, …

A Settlement By “Any Other Name”: Evaluating The Sustainability Of Settlement Mechanisms, Dorcas Quek Anderson

Research Collection Yong Pung How School Of Law

Private settlements have been consistently encouraged by the Singapore civil justice system. Depending on the context, the settlement may take on many forms, including consent orders and settlement agreements. This begs the question of whether the exact form of settlement matters, or whether a settlement “by any other name” suffices. This article proposes the concept of “sustainable settlements” – comprising the measures of ease of enforcement, finality, and confidentiality – to holistically appraise the effectiveness of settlement mechanisms. The assessment of six settlement mechanisms using these measures clearly indicates that not every mechanism is equally sustainable. Exploring settlement amidst the …

A Difficult Act To Maintain, J.G. Allen

Research Collection Yong Pung How School Of Law

In "Where is Singapore's AI regulation headed?" (Issues, Summer 2025), Manoj Harjani starts by recounting its delicate balancing act in governing artificial intelligence. The city-state is able to maintain credibility on the global stage while remaining pragmatically grounded in technical experimentation, maintaining policy realism without overcommitting to rigid legal frameworks. The choice to adopt a regulatory “light touch” is often framed as a way to maintain flexibility, avoid overregulation, and enable innovation. But this obscures the extent to which this posture is itself a political and economic settlement—one that reinforces Singapore’s position in the global digital economy by facilitating capital …

Bridging The Great Wall: China’S Evolving Cross-Border Data Flow Policies And Implications For Global Data Governance, Sheng Zhang, Henry S. Gao

Research Collection Yong Pung How School Of Law

Despite the rapid expansion of the digital economy, the global regulatory framework for data flows remains fragmented, with countries adopting divergent approaches shaped by their own regulatory priorities. As a key player in the Internet economy, China’s approach to cross-border data flows (CBDF) not only defines its domestic digital landscape but also influences emerging global norms. This paper takes a comprehensive view of the evolution of China’s CBDF regime, examining its development through both domestic and international lenses. Domestically, China’s regulation of CBDF has evolved from a security-first approach to one that seeks to balance security with economic development. This …

Strengthening The International Competitiveness Of Capital Markets: Global Insights And Local Strategies, Aurelio Gurrea-Martinez

Research Collection Yong Pung How School Of Law

Global capital markets are undergoing a profound transformation. Over the past decade, there has been a marked decline in Initial Public Offerings (IPOs) in most advanced economies, including those with highly developed capital markets such as the United Kingdom and the United States. Interestingly, during the same period, countries like Indonesia, Malaysia, Thailand and particularly China, have witnessed a significant increase in the number of listed companies, contributing to making Asia home to approximately 55% of all listed companies worldwide. The decline in IPO activity has prompted many countries and regions around the world, including the United Kingdom, the United …

Oral History Interview With Timothy Clark (Part 2), Timothy Clark

Oral History Collection

The interview covered:

• Teaching and Curriculum
• Research
• Challenges & Future
• Personal Reflections
• Libraries
• Advice
• Advice for Students

High Flying Adored: How Ceo Narcissism Influences Firms’ Responses To Above-Aspiration Performance With Risky Organizational Change, Korcan Kavusan, Daniel Mack, Matthew P. Mount, Gokhan Ertug

Research Collection Lee Kong Chian School Of Business

Research Summary: Research on performance feedback presents conflicting views on how above-aspiration performance influences organizational change. Some studies argue that it constrains change due to a lack of organizational motivation, while others suggest that it enables change by expanding managerial discretion. Reconciling these perspectives, we suggest that managers’ narcissistic tendencies can fundamentally alter how a firm responds to above-aspiration performance. We theorize and find evidence that high-narcissism CEOs respond to above-aspiration performance with more acquisitions—attention-generating actions that align with their self-enhancement motives, while under similar conditions low-narcissism CEOs avoid acquisitions, due to their uncertainty and risk. Our findings highlight the …

Not All Political Ties Are The Same: Firms' Ties To The Government And Pollution, Wen Helena Li, Ilya R. P. Cuypers, Gokhan Ertug, Hari Bapuji, Wei Liu

Research Collection Lee Kong Chian School Of Business

Complementing research on the implications of political ties for firms’ strategic decisions and financial performance, recent studies are increasingly focusing on the environmental consequences of firms’ political connections. We contribute to this stream of work by integrating insights from the literature on political ties and the multifaceted nature of governments to explore how the level of government influences the pollution implications of firms’ political ties. Specifically, we theorize and demonstrate that, in China, firms' achieved political ties with high levels of the government reduce pollution, while such ties with low levels of the government increase it. Furthermore, we examine how …