Digital Commons Network^™

Context-Aware Hierarchical Taxonomy Generation For Scientific Papers Via Llm-Guided Multi-Aspect Clustering, Kun Zhu, Lizi Liao, Yuxuan Gu, Lei Huang, Xiaocheng Feng, Bing Qin

Research Collection School Of Computing and Information Systems

The rapid growth of scientific literature demands efficient methods to organize and synthesize research findings. Existing taxonomy construction methods, leveraging unsupervised clustering or direct prompting of large language models (LLMs), often lack coherence and granularity. We propose a novel context-aware hierarchical taxonomy generation framework that integrates LLM-guided multi-aspect encoding with dynamic clustering. Our method leverages LLMs to identify key aspects of each paper (e.g., methodology, dataset, evaluation) and generates aspect-specific paper summaries, which are then encoded and clustered along each aspect to form a coherent hierarchy. In addition, we introduce a new evaluation benchmark of 156 expert-crafted taxonomies encompassing 11.6k …

Why Stop At One Error? Benchmarking Llms As Data Science Code Debuggers For Multi-Hop And Multi-Bug Errors, Zhiyu Yang, Shuo Wang, Yukun Yan, Yang Deng

Research Collection School Of Computing and Information Systems

LLMs are transforming software development, yet current code generation and code repair benchmarks mainly assess syntactic and functional correctness in simple, single-error cases. LLMs’ capabilities to autonomously find and fix runtime logical errors in complex data science code remain largely unexplored. To address this gap, we introduce DSDBench: the Data Science Debugging Benchmark, the first benchmark for systematic evaluation of LLMs on multi-hop error tracing and multi-bug detection in data science code debugging. DSDBench adapts datasets from existing data science task benchmarks, such as DABench and MatPlotBench, featuring realistic data science debugging tasks with automatically synthesized multi-hop, multi-bug code snippets. …

Temporal And Heterogeneous Graph Neural Network For Remaining Useful Life Prediction, Zhihao Wen, Yuan Fang, Pengcheng Wei, Fayao Liu, Zhenghua Chen, Min Wu

Research Collection School Of Computing and Information Systems

Predicting remaining useful life (RUL) plays a crucial role in the prognostics and health management of industrial systems that involve a variety of interrelated sensors. Given a constant stream of time-series sensory data from such systems, deep learning (DL) models have risen to prominence at identifying complex, nonlinear temporal dependencies in these data. In addition to the temporal dependencies of individual sensors, spatial dependencies emerge as important correlations among these sensors, which can be naturally modeled by a temporal graph that describes time-varying spatial relationships. However, the majority of existing studies have relied on capturing discrete snapshots of this temporal …

Does Generative Ai Facilitate Investor Trading? Early Evidence From Chatgpt Outages, Qiang Cheng, Pengkai Lin, Yue Zhao

Research Collection School Of Accountancy

In this paper, we use ChatGPT outages to provide early evidence on whether investors rely on generative artificial intelligence (GenAI) to perform professional tasks and the associated impact on stock price informativeness. We document a significant decline in stock trading volume during ChatGPT outages. The effect is stronger for firms with corporate news released immediately before or during the outages and for firms with higher ownership held by transient institutional investors. We then document declines in short-run price impact and return variance during the outage periods, consistent with reduced informed trading. Lastly, we document a positive effect of GenAI-assisted trading …

Commentary: Delayed Climate Reporting Requirements Threaten Singapore’S Sustainability Leadership, Jiwei Wang, Holly I. Yang, Liandong Zhang

Research Collection School Of Accountancy

In a commentary by SMU Professor of Accounting (Practice) and Director of Master of Professional Accounting (MPA) and Master of Science in Accounting (MSA) programmes Wang Jiwei, SMU Associate Professor of Accounting, Lee Kong Chian Fellow and Co-Director (Academic Research) of the School of Accountancy Research Centre (SOAR) Holly Yang, and SMU Dean of School of Accountancy and Lee Kong Chian Professor of Accounting Zhang Liandong, they suggested that delaying climate disclosure requirements for small and mid-sized enterprises (SMEs) from 2025 to 2030 could weaken Singapore’s sustainable finance leadership, despite regulators saying the extension would help smaller firms build environmental, …

Discussion Of "Csr And Negative Corporate Events: The Moderating Role Of Managerial Overconfidence", Hye Sun Chang

Research Collection School Of Accountancy

Corporate social responsibility (CSR) refers to the notion that firms are accountable not only to shareholders but also to a broader set of stakeholders including customers, employees, creditors, and the communities in which they operate. Although CSR has long been part of corporate discourse, its prominence has grown with the rise of environmental, social, and governance (ESG) concerns. Today’s consumers and stakeholders are increasingly attentive to issues such as climate change, economic inequality, labor rights, and social justice, prompting firms to align their strategies with evolving societal expectations. Building on this increasingly salient backdrop, Chu et al. (2026), hereafter CCT, …

A Comparison Of Comparisons: Evidence From An International Comparative Study Of 'Smart Cities', Kevin Ward, Teresa Abbruzzese, Tim Bunnell, Paolo Cardullo, I-Chun Catherine Chang, Byron Miller, Ramon Ribera-Fumaz, Haeran Shin, Zachary Spicer, Orlando Woods

Research Collection College of Integrative Studies

Every year the list lengthens of cities with some sort of ‘smart city’ public policy. In some, it emerges as the latest in a long line of urban digital and information communication policies. In others, the introduction of the notion of the ‘smart city’ marks a departure from past approaches to public policy. Additionally, the more studies emerge of actual smart city policies, then the less definitional agreement there seems to be. Nevertheless, that we have witnessed in the last two decades the ‘repeated instance’ of smart cities emerging in cities around the world seems incontrovertible. Like so much urban …

Remaking The Smart City Through The Covid-19 Pandemic: Seoul, Singapore, Taipei, Orlando Woods, I-Chun Catherine Chang, Haeran Shin

Research Collection College of Integrative Studies

The COVID-19 pandemic has proven to be a catalysing force for urban innovation in general, and for smart city agendas specifically, throughout the world. From the development of contact tracing technologies and the enforcement of quarantine and safe distancing measures, to the dissemination of public health information and advancement of telehealth rollouts, the promises of “smart” technologies to reveal and govern patterns of socio-spatial contact and mobility can be found at the core of effective city management during the pandemic. Arguably nowhere is this truer than in the cities of Seoul, Singapore and Taipei, where the Asian developmental state was …

Global Cooling Watch 2025, Omar Abdelaziz, Ray Gluckman, Ian Hamilton, Radhika Khosla, Lily Riahi

Research Collection College of Integrative Studies

The second edition of UNEP’s Global Cooling Watch Report takes a deep dive into one of the decade’s most urgent challenges: surging heat, soaring cooling demand, and stark inequalities in access. Produced by the UNEP-led Cool Coalition, the report provides a comprehensive assessment of the rapidly growing global demand for cooling and the need for climate-friendly solutions to the issue. The 2025 report builds on the first Global Cooling Watch (2023), which established the Sustainable Cooling Pathway framework. The new edition deepens analysis of intensifying extreme heat and its effect on cooling demand, improved assessment of passive cooling, and coverage …

From Great “Liberator” To “Landlord Seeking Rent”: The Implications Of U.S. Reciprocal Tariffs Policy In Asia And Beyond, Henry S. Gao

Research Collection Yong Pung How School Of Law

The post-war international economic order was, to a large extent, underwritten by U.S. leadership. Nowhere was this more visible than in Asia, where the United States not only financed post-colonial development but also provided open access to its huge market, laying the foundation for export-led growth across the region. It underpinned regional stability through a blend of military, diplomatic, and economic engagement, including costly interventions in the Korean and Vietnam wars. That legacy, however, was fundamentally disrupted on April 2, 2025, when the Trump administration unveiled sweeping tariffs targeting key Asian economies. As Singapore’s defense minister wryly observed, the United …

Nationalism And Anglo-American Neo-Colonialism In Southeast Asia, 1945-1965, Wen-Qing (Wei Wenqing) Ngoei

Research Collection College of Integrative Studies

It is tempting to treat the United States’ ill-fated military intervention in Vietnam in the 1960s as the desperate final gasp of a moribund Western imperial system. Certainly, scholars have described Washington’s military debacle in Vietnam as the end of America’s “short-lived empire” in Southeast Asia, emblematic of the broader, decisive triumph of Southeast Asian nationalism over western colonialism. This reading of Southeast Asian countries attaining formal independence after 1945, with tacit assumptions that colonialism and nationalism exist in binary opposition, tends to ossify when the region’s history is viewed through the lens of U.S. defeat in Vietnam.

In contrast, …

Seeing Beyond The State: Private Sector-Led Smart City Governance In Bsd City, Indonesia, Prerona Das, Orlando Woods, Lily Kong

Research Collection College of Integrative Studies

In recent decades new cities have sprung up at a rapid pace, aided by private sector funding (Hogan et al., 2012). Within the realm of smart city development, private sector influence over urban governance has substantially increased, particularly through Public-Private Partnerships (PPPs). However, in Indonesia, there is an emerging trend of the private sector exerting significant control over ‘independent’ greenfield smart cities beyond state-led frameworks. This paper develops the idea of seeing beyond the state which involves looking past conventional state-centered approaches to urban governance. It considers instead how power and control are exercised outside or beyond the usual boundaries …

Scenarios For Csrd Scope Amendments - Advancing Reporting Scope While Reducing Further Burden, Andreas Rasche, Theodor Florian Cojoianu, Andreas G. F. Hoepner, Fabiola Schneider

Research Collection College of Integrative Studies

This paper presents calculations related to the CSRD scope criteria which are modified through the Omnibus I Simplification Package. We show how many companies would be in scope of CSRD when considering the criteria suggested by (a) the Commission’s Omnibus proposal, (b) the position adopted by the Council of the EU, and (c) the European Peoples Party (EPP) proposal in the European Parliament. For each of these three “cases” we show the impact of lowering or increasing the employee-related threshold. 1.    Our calculations demonstrate that the number of in-scope companies varies significantly when modifying the employee threshold. We conclude from …

A Dataset Exploring Urban Comfort Through Novel Wearables And Environmental Surveys, Patrick Chwalek, Sailin Zhong, Nathan Perry, Tianqi Liu, Clayton Miller, Seiied Hamed Alavi, Denis Lalanne, A. Joseph Paradiso

Research Collection College of Integrative Studies

This study presents a comprehensive dataset capturing indoor environmental parameters, physiological responses, and subjective perceptions across three global cities. Utilizing wearable sensors, including smart eyeglasses, and a modified Cozie app, environmental and physiological data were collected, along with pre-screening, onboarding, and recurring surveys. Peripheral cues facilitated participant engagement with micro-EMA surveys, minimizing disruption over a 5-day collection period. The dataset offers insights into urban comfort dynamics, highlighting the interplay between environmental conditions, physiological responses, and subjective perceptions. Researchers can utilize this dataset to deepen their understanding of indoor environmental quality and inform the design of healthier built environments. Access to …

Branch-And-Cut-And-Price For Agile Earth Observation Satellite Scheduling, Guansheng Peng, Jianjiang Wang, Guopeng Song, Aldy Gunawan, Lining Xing, Pieter Vansteenwegen

Research Collection School Of Computing and Information Systems

The Agile Earth Observation Satellite scheduling selects and sequences satellite observations of possible targets on the Earth’s surface, each with a specific profit and multiple time windows. The objective is to maximize the collected profit of all observations completed under some operational constraints. The problem can be modeled as a variant of the Team Orienteering Problem with Time Windows (TOPTW). The key differences with the regular TOPTW are twofold: first, a time-dependent transition time is required for each pair of consecutive observations to adjust the camera’s look angles. Second, the time windows of each target vary during different observation cycles, …

Defects4c: Benchmarking Large Language Model Repair Capability With C/C++ Bugs, Jian Wang, Xiaofei Xie, Qiang Hu, Shangqing Liu, Jiongchi Yu, Jiaolong Kong, Yi Li

Research Collection School Of Computing and Information Systems

Automated Program Repair (APR) plays a critical role in enhancing the quality and reliability of software systems. While substantial progress has been made in Java-based APR, largely facilitated by benchmarks like Defects4J, there remains a significant gap in research on C/C++ program repair, despite the widespread use of C/C++ and the prevalence of associated vulnerabilities. This gap is primarily due to the lack of high-quality, open-source benchmarks tailored for C/C++. To address this issue, we introduce Defects4C, a comprehensive and executable benchmark specifically designed for C/C++ program repair. Our dataset is constructed from real-world C/C++ repositories and includes a large …

Mmlu-Prox: A Multilingual Benchmark For Advanced Large Language Model Evaluation, Weihao Xuan, Et. Al.

Research Collection School Of Computing and Information Systems

Existing large language model (LLM) evaluation benchmarks primarily focus on English, while current multilingual tasks lack parallel questions that specifically assess cross-lingual reasoning abilities. This dual limitation makes it challenging to assess LLMs’ performance in the multilingual setting comprehensively. To fill this gap, we introduce MMLU-ProX, a comprehensive benchmark covering 29 languages, built on an English benchmark. Each language version consists of 11,829 identical questions, enabling direct cross-lingual comparisons. Additionally, to meet efficient evaluation needs, we provide a lite version containing 658 questions per language. To ensure the high quality of MMLU-ProX, we employ a rigorous development process that involves …

Interaction2code: Benchmarking Mllm-Based Interactive Webpage Code Generation From Interactive Prototyping, Jingyu Xiao, Yuxuan Wan, Yintong Huo, Zixin Wang, Xinyi Xu, Wenxuan Wang, Zhiyao Xu, Yuhang Wang, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Multimodal Large Language Models (MLLMs) have demonstrated remarkable performance on the design-to-code task, i.e., generating UI code from UI mock-ups. However, existing benchmarks only contain static web pages for evaluation and ignore the dynamic interaction, limiting the practicality, usability and user engagement of the generated webpages. To bridge these gaps, we present the first systematic investigation of MLLMs in generating interactive webpages. Specifically, we formulate the Interaction-to-Code task and establish the Interaction2Code benchmark, encompassing 127 unique webpages and 374 distinct interactions across 15 webpage types and 31 interaction categories. Through comprehensive experiments utilizing state-of-theart (SOTA) MLLMs, evaluated via both automatic …

Distillcaps: Enhancing Audio-Language Alignment In Captioning Via Retrieval-Augmented Knowledge Distillation, Thinh Pham, Nghiem Diep, Lizi Liao, Binh Nguyen

Research Collection School Of Computing and Information Systems

Automated audio captioning (AAC) benefits from incorporatingexternal context to interpret complex sounds, but doing so withretrieval-augmented generation (RAG) at inference is sometimesinfeasible due to data availability or incurs significant latency andcomplexity. We propose DistillCaps, a novel training-time frame-work that leverages RAG to guide knowledge distillation for im-proved audio-language alignment, while lessening the relianceon retrieval during inference. In our framework, a RAG-equippedteacher model retrieves relevant textual information (e.g., simi-lar captions) for each audio clip and uses it for training to gener-ate context-enriched captions. Simultaneously, a student model istrained to imitate this teacher, learning to produce high-qualitycaptions from audio alone. We further …

Designing For Novice Debuggers: A Pilot Study On An Ai-Assisted Debugging Tool, Oka Kurniawan, Erick Chandra, Christopher M. Poskitt, Yannic Noller, Kenny T.W. Choo, Cyrille Jegourel

Research Collection School Of Computing and Information Systems

Debugging is a fundamental skill that novice programmers must develop. Numerous tools have been created to assist novice programmers in this process. Recently, large language models (LLMs) have been integrated with automated program repair techniques to generate fixes for students' buggy code. However, many of these tools foster an over-reliance on AI and do not actively engage students in the debugging process. In this work, we aim to design an intuitive debugging assistant, CodeHinter, that combines traditional debugging tools with LLM-based techniques to help novice debuggers fix semantic errors while promoting active engagement in the debugging process. We present findings …

Instructors’ Strategies In Creating And Implementing Constructivist Llm-Based Learning Activities, Emily Aurelia, Shun Yi Yeo, Michelle Lui, Effie Lai-Chong Law, Anthony Tang

Research Collection School Of Computing and Information Systems

Large language models (LLMs) are increasingly being integrated into educational settings, enabling more adoption of constructivist teaching and learning approaches in classrooms. This paper explores the strategies instructors are currently using to incorporate LLMs into learning activities that align with constructivist principles, which emphasize that learners actively construct their own knowledge. Through interviews with nine instructors who have designed eleven distinct LLM-based activities and using reflexive thematic analysis, this study identifies various types of learning activities with respect to four different aspects of the constructivist learning theory. The strategies employed and challenges faced to foster constructivist student-LLM interaction were also …

Competition Through Entry Fees Between Auctions For Differentiated Objects, Massimiliano Landi, Domenico Menicucci, Domenico Colucci

Research Collection School Of Economics

This paper considers two competing auctions with objects differentiated according to the random utility framework introduced in Perloff and Salop (1985): bidders privately observe their values for the two objects, and values are ex ante i.i.d. across objects and across bidders. For the case of uniform distribution of values, we show that competition under entry fees is less intense than competition under reserve prices in the sense that sellers are better off, and bidders are worse off when competition takes place with entry fees rather than under reserve prices. The key difference between the two settings is that undercutting under …

Security Modelling For Cyber-Physical Systems: A Systematic Literature Review, Shao Fei Huang, Christopher M. Poskitt, Lwin Khin Shar

Research Collection School Of Computing and Information Systems

Cyber-physical systems are at the intersection of digital technology and engineering domains, rendering them high-value targets of sophisticated and well-funded cybersecurity threat actors. Prominent cybersecurity attacks on CPS have brought attention to the vulnerability of these systems and the inherent weaknesses of critical infrastructure reliant on them. Security modelling for CPS is an important mechanism to systematically identify and assess vulnerabilities, threats, and risks throughout system life cycles, and to ultimately ensure system resilience, safety, and reliability. This survey delves into state-of-the-art research on CPS security modelling, encompassing both threat and attack modelling. While these terms are sometimes used interchangeably, …

Simulated Interactive Debugging, Yannic Noller, Erick Chandra, Srinidhi Chandrashekar, Kenny Choo, Cyrille Jegourel, Oka Kurniawan, Christopher M. Poskitt

Research Collection School Of Computing and Information Systems

Debugging software, i.e., the localization of faults and their repair, is a key activity in software engineering. Therefore, effective and efficient debugging is one of the core skills a software engineer must develop. However, the teaching of debugging techniques is usually very limited or only taught in indirect ways, e.g., during software projects. As a result, most Computer Science (CS) students learn debugging only in an ad-hoc and unstructured way. In this work, we present our approach called Simulated Interactive Debugging that interactively guides students along the debugging process. The guidance aims to empower the students to repair their solutions …

Towards Goal-Oriented Intelligent Tutoring Systems In Online Education, Yang Deng, Zifeng Ren, An Zhang, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Interactive Intelligent Tutoring Systems (ITSs) enhance the learning experience in online education byfostering effective learning through interactive problem-solving. However, many current ITS models do notfully incorporate proactive engagement strategies that optimize educational resources through thoughtfulplanning and assessment. In this work, we propose a novel and practical task of Goal-oriented IntelligentTutoring Systems (GITS), designed to help students achieve proficiency in specific concepts through a tailoredsequence of exercises and evaluations. We introduce a novel graph-based reinforcement learning framework,named Planning-Assessment-Interaction (PAI), to tackle the challenges of goal-oriented policy learningwithin GITS. This framework utilizes cognitive structure information to refine state representation andguide the selection …

A Fake Friend? Ai Companions Are Exactly That, Seow Hon Tan

Research Collection Yong Pung How School Of Law

In a commentary, SMU Associate Professor of Law Tan Seow Hon discussed how AI companions, which promise emotionally intelligent companionship, have blurred the line between human and machine relationships by mimicking empathy, memory, and affection. She suggested that while such technologies may ease loneliness, they risk fostering narcissism, diminishing real human connection, and replacing authentic friendship with comforting illusions that erode the capacity for love and community.

Deep Reinforcement Learning For Solving The Stochastic E-Waste Collection Problem, Dang Viet Anh Nguyen, Aldy Gunawan, Mustafa Misir, Kwan Hui Lim, Pieter Vansteenwegen

Research Collection School Of Computing and Information Systems

With the growing influence of the internet and information technology, Electrical and Electronic Equipment (EEE) has become a gateway to technological innovations. However, discarded devices, also called e-waste, pose a significant threat to the environment and human health if not properly treated, disposed of, or recycled. In this study, we extend a novel model for the e-waste collection in an urban context: the Heterogeneous VRP with Multiple Time Windows and Stochastic Travel Times (HVRP-MTWSTT). We propose a solution method that employs deep reinforcement learning to guide local search heuristics (DRL-LSH). The contributions of this paper are as follows: (1) HVRP-MTWSTT …

Explainable Sentiment Analysis With Deepseek-R1: Performance, Efficiency, And Few-Shot Learning, Donghao Huang, Zhaoxia Wang

Research Collection School Of Computing and Information Systems

Large language models (LLMs) have transformed sentiment analysis, yet balancing accuracy, efficiency, and explainability remains a critical challenge. This study presents the first comprehensive evaluation of DeepSeek-R1—an open-source reasoning model—against OpenAI’s GPT-4o and GPT-4o-mini. We test the full 671B model and its distilled variants, systematically documenting few-shot learning curves. Our experiments show DeepSeek-R1 achieves a 91.39% F1 score on 5-class sentiment and 99.31% accuracy on binary tasks with just 5 shots, an eightfold improvement in few-shot efficiency over GPT-4o. Architecture-specific distillation effects emerge, where a 32B Qwen2.5-based model outperforms the 70B Llama-based variant by 6.69 percentage points. While its reasoning …

Generative Ai And Empirical Software Engineering: A Paradigm Shift, Christoph Treude, Margaret-Anne Storey

Research Collection School Of Computing and Information Systems

The widespread adoption of generative AI in software engineering marks a paradigm shift, offering new opportunities to design and utilize software engineering tools while influencing both developers and the artifacts they create. Traditional empirical methods in software engineering, including quantitative, qualitative, and mixed-method approaches, are well established. However, this paradigm shift introduces novel data types and redefines many concepts in the software engineering process. The roles of developers, users, agents, and researchers increasingly overlap, blurring the distinctions between these social and technical actors within the field. This paper examines how integrating AI into software engineering challenges traditional research paradigms. It …

Pricing Strategies In Global Channels: Considering The Effects Of Parallel Trade, Yuan-Mao Kao, Yang Yang, Shih-Fen Cheng, Cheng-Hung Wu

Research Collection School Of Computing and Information Systems

Pricing a global product differently across multiple regions is a common but controversial practice. Although price differentiation helps capture unique market characteristics, it also encourages parallel trade, which may affect the overall corporate performance of a global company. We study this problem with a single global business unit (GBU) and multiple local business units (LBUs). The GBU manufactures a product and sets a transfer price for supplying the product to all LBUs, and LBUs decide retail prices for their respective regional markets. Customers can purchase products in any region by comparing LBUs’ prices and other parallel-imported factors, and we construct …