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Audeter: A Large-Scale Dataset For Deepfake Audio Detection In Open Worlds, Qizhou Wang, Hanxun Huang, Guansong Pang, Sarah Erfani, Christopher Leckie Aug 2026

Audeter: A Large-Scale Dataset For Deepfake Audio Detection In Open Worlds, Qizhou Wang, Hanxun Huang, Guansong Pang, Sarah Erfani, Christopher Leckie

Research Collection School Of Computing and Information Systems

Speech synthesis systems can now produce highly realistic vocalisations that pose significant authenticity challenges. Despite substantial progress in deepfake detection models, their real-world effectiveness is often undermined by evolving distribution shifts between training and test data, driven by the complexity of human speech and the rapid evolution of synthesis systems. Existing datasets suffer from limited real speech diversity, insufficient coverage of recent synthesis systems, and heterogeneous mixtures of deepfake sources, which hinder systematic evaluation and open-world model training. To address these issues, we introduce AUDETER (AUdio DEepfake TEst Range), a large-scale and highly diverse deepfake audio dataset comprising over 4,500 …

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Left: Learnable Fusion Of Tri-View Tokens For Unsupervised Time Series Anomaly Detection, Dezheng Wang, Tong Chen, Guansong Pang, Congyan Chen, Shihua Li, Hongzhi Yin Aug 2026

Left: Learnable Fusion Of Tri-View Tokens For Unsupervised Time Series Anomaly Detection, Dezheng Wang, Tong Chen, Guansong Pang, Congyan Chen, Shihua Li, Hongzhi Yin

Research Collection School Of Computing and Information Systems

As a fundamental data mining task, unsupervised time series anomaly detection (TSAD) aims to build a model for identifying abnormal timestamps without assuming the availability of annotations. A key challenge in unsupervised TSAD is that many anomalies are too subtle to exhibit detectable deviation in any single view (e.g., time domain), and instead manifest as inconsistencies across multiple views like time, frequency, and a mixture of resolutions. However, most cross-view methods rely on feature or score fusion and do not enforce analysis–synthesis consistency, meaning the frequency branch is not required to reconstruct the time signal through an inverse transform, and …

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Timeradar: A Domain-Rotatable Foundation Model For Time Series Anomaly Detection, Hui He, Hezhe Qiao, Yutong Chen, Kun Yi, Guansong Pang Aug 2026

Timeradar: A Domain-Rotatable Foundation Model For Time Series Anomaly Detection, Hui He, Hezhe Qiao, Yutong Chen, Kun Yi, Guansong Pang

Research Collection School Of Computing and Information Systems

Current time series foundation models (TSFMs) primarily focus on learning prevalent and regular patterns within a predefined time or frequency domain to enable supervised downstream tasks (\eg, forecasting). Consequently, they are often ineffective for inherently unsupervised downstream tasks—such as time series anomaly detection (TSAD), which aims to identify rare, irregular patterns. This limitation arises because such abnormal patterns can closely resemble the regular patterns when presented in the same time/frequency domain. To address this issue, we introduce TimeRadar, an innovative TSFM built in a fractional time–frequency domain to support generalist TSAD across diverse unseen datasets. Our key insight is that …

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Task-Aligned Haze Removal With Semantic-Aware Fusion And Contrast Self-Correction, Jinbin Wang, Aiping Yang, Guosong Jiang, Wenlong Yu, Dongwei Ren, Qinghua Hu Aug 2026

Task-Aligned Haze Removal With Semantic-Aware Fusion And Contrast Self-Correction, Jinbin Wang, Aiping Yang, Guosong Jiang, Wenlong Yu, Dongwei Ren, Qinghua Hu

Research Collection School Of Computing and Information Systems

Adverse haze conditions introduce complex degradations that obscure scene details and distort structural cues critical for object detection, posing persistent challenges for vision‐based sensing systems. Although existing haze removal methods have achieved notable improvements in visual clarity, their optimisation objectives are often misaligned with downstream detection requirements, leading to limited detection performance in real‐world scenarios. To address this issue, this work proposes a task‐aligned weakly supervised haze removal framework, termed Dehaze4Detection, which explicitly aligns low‐level restoration with high‐level detection objectives. The framework incorporates a Semantic‐Aware Multi‐Scale Fusion Module (SMFM) that embeds pixel‐level semantic knowledge into the dehazing process, enabling selective …

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Hvi-Cidnet+: Beyond Extreme Darkness For Low-Light Image Enhancement, Kangbiao Shi, Xiaowen Ma, Yixu Feng, Tao Hu, Peng Wu, Guansong Pang, Qingsen Yan Aug 2026

Hvi-Cidnet+: Beyond Extreme Darkness For Low-Light Image Enhancement, Kangbiao Shi, Xiaowen Ma, Yixu Feng, Tao Hu, Peng Wu, Guansong Pang, Qingsen Yan

Research Collection School Of Computing and Information Systems

Low-Light Image Enhancement (LLIE) aims to recover visually pleasing content and details from degraded low-light images. However, existing RGB-based methods often suffer from color bias and brightness artifacts due to inherent high color sensitivity. Although the HSV color space can decouple brightness and color, it introduces noticeable red and black noise artifacts. To address these challenges, we adopt the Horizontal/Vertical-Intensity (HVI) color space for LLIE, which is defined by the HV color map and learnable intensity. The former enforces small distances for red coordinates to alleviate red noise artifacts, while the latter adaptively compresses low-light regions to suppress black noise …

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Towards Confucian Economic Democracy: A Relational Alternative To Possessive Individualism, Sor-Hoon Tan Aug 2026

Towards Confucian Economic Democracy: A Relational Alternative To Possessive Individualism, Sor-Hoon Tan

Research Collection School of Social Sciences

This article offers a Confucian conception of ownership and a different approach to equality based on a concept of relational person that could provide an alternative philosophical framework for economic democracy. The Confucian concept of nonexclusive and nonabsolute co-ownership, conditional on owners fulfilling their social responsibilities and sustained in networks of relationships mitigates the drive to appropriation and resistance to redistribution even without formalizing legal rights of equal ownership. Confucian texts’ condemnation of wide disparities between rich and poor corresponds with distributive ideas that balance equal satisfaction of needs with merit-based incentives for productivity constrained by social harmony. Without advocating …

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When The Best-Fit Model Is Not Best: The Glass Slipper Fallacy And Latent Growth Mixture Modelling, Jonathan L. Chia, Markus Wettstein, Andree Hartanto Aug 2026

When The Best-Fit Model Is Not Best: The Glass Slipper Fallacy And Latent Growth Mixture Modelling, Jonathan L. Chia, Markus Wettstein, Andree Hartanto

Research Collection School of Social Sciences

Despite the use of latent growth mixture modelling (LGMM) to study longitudinal changes, existing practices may inadvertently impede this very investigation. Although subgroup trajectories may theoretically differ in their structure (e.g., some subgroups being linear, some curvilinear), the current convention advocates overreliance on the baseline model to derive subsequent profile trajectories, which may obscure these structural differences. In this article, we provide a brief description of extant LGMM practices, after which we explicate the pitfalls of the current approach. Finally, we provide a principled approach for LGMM research moving forward. Specifically, we recommend specifying a set of theoretically plausible models …

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Artificial Intelligence (Ai) In Forensic Psychology: An Umbrella Review Of Potentials And Pitfalls, Ysabel Thereze Ang Guevarra, Nur Eva Alisha Binte Mohamed Hisham, Andree Hartanto Aug 2026

Artificial Intelligence (Ai) In Forensic Psychology: An Umbrella Review Of Potentials And Pitfalls, Ysabel Thereze Ang Guevarra, Nur Eva Alisha Binte Mohamed Hisham, Andree Hartanto

Research Collection School of Social Sciences

Artificial intelligence (AI) is becoming increasingly embedded within forensic psychological practice, shaping how criminal risk, legal responsibility and public safety are assessed. AI tools are now used in recidivism prediction, behavioural analysis, deception detection and investigative support, high-stakes domains where errors can have profound consequences. Despite this rapid adoption, the existing literature remains fragmented, with most reviews confined to narrow subdomains and offering limited integrated synthesis of AI′s broader role in forensic psychology. Thus, this umbrella review addresses this gap by synthesising findings from 43 reviews obtained from five major databases, namely EBSCOhost ERIC, EBSCOhost PsycInfo, PubMed, Scopus and Web …

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Caring With Ai: The Efficacy Of A Customised Chatgpt-Delivered Self-Compassion Intervention On College Students' Well-Being And Academic Functioning, Tracy Xi Chen, Chi-Ying Cheng, Andree Hartanto Aug 2026

Caring With Ai: The Efficacy Of A Customised Chatgpt-Delivered Self-Compassion Intervention On College Students' Well-Being And Academic Functioning, Tracy Xi Chen, Chi-Ying Cheng, Andree Hartanto

Research Collection School of Social Sciences

College students face various challenges, including academic pressure, social stress, and the transition into adulthood, which can lead to increased anxiety and other mental health issues. By recognizing personal struggles as part of a shared human experience and responding with kindness, self-compassion serves as a powerful strategy for enhancing resilience, facilitating better well-being and performance outcomes. Although effective, Compassion-Focused Therapy often requires substantial resources and time, limiting its applicability to college students. To overcome these barriers, the current study designed and evaluated Your Self-Compassion Companion, a ChatGPT-powered AI chatbot intervention grounded in self-compassion theory and delivered over three weekly 20-min …

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Transnational Social Protections And The Market: Seeking Support From The Global Cruise Industry, Yasmin Y. Ortiga Aug 2026

Transnational Social Protections And The Market: Seeking Support From The Global Cruise Industry, Yasmin Y. Ortiga

Research Collection School of Social Sciences

Migration studies have mostly portrayed employers as paternalistic or exploitative, creating the very conditions that make migrants’ lives insecure and unstable. This paper challenges this view by showing how the market can also be an unlikely source of protections, where extractive work conditions co-exist with a certain degree of social support. Drawing on interviews with 45 Filipino cruise workers during the COVID-19 pandemic, I discuss how migrants used a logic of employee rights to claim benefits such as food, housing and insurance. Cruise lines willingly provided such protections, but only while workers maintained active contracts onboard their ships. Rather than …

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Gender And Professional Identities In Businesswomen’S Negotiation, Chi-Ying Cheng, Amy J. Lim, Yi Wen Tan, Fiona Lee Aug 2026

Gender And Professional Identities In Businesswomen’S Negotiation, Chi-Ying Cheng, Amy J. Lim, Yi Wen Tan, Fiona Lee

Research Collection School of Social Sciences

Gender roles and expectations for women have been shown to account for why women tend to negotiate ineffectively in business settings. Drawing from the psychological literature on multiple identities, this paper examines how individual differences in perceived compatibility between gender and professional identities–captured by the construct Gender-Professional Identity Integration (G-PII)–shape businesswomen’s negotiation behaviors. Two studies examined how G-PII interacts with identity cues and cue valence to influence negotiation outcomes. We found that those who perceived their gender and professional identities as compatible (high G-PII) exhibited an “assimilation” effect–they negotiate more effectively when their professional identity was primed by professional identity …

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The Ambivalent Wisdom Of Moral Disgust, Brandon Yip Aug 2026

The Ambivalent Wisdom Of Moral Disgust, Brandon Yip

Research Collection School of Social Sciences

This paper has two aims. First, to provide a positive account of moral disgust. I suggest that moral disgust is a response to acts that are socially corrosive, namely, acts that undermine the normative structure to which an agent is attuned. I support this analysis with two lines of evidence: (1) moral disgust serves the important function of guarding normative structures from socially corrosive actions and (2) the analysis provides an illuminating explanation of moral disgust in a wide variety of cases. The secondary aim of this paper is to probe the normative implications of my positive account. I suggest …

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Lessons Learned From The Adrenalin Load Disaggregation Challenge, András Balázs Tolnai, Zheng Ma, Igor Sartori, Clayton Miller, Stephen White, Matt Amos, Gustaf Bengtsson, Akram Hameed, Nørregaard Bo Jørgensen Aug 2026

Lessons Learned From The Adrenalin Load Disaggregation Challenge, András Balázs Tolnai, Zheng Ma, Igor Sartori, Clayton Miller, Stephen White, Matt Amos, Gustaf Bengtsson, Akram Hameed, Nørregaard Bo Jørgensen

Research Collection College of Integrative Studies

Crowdsourced data science competitions have emerged as a powerful mechanism for advancing research in energy informatics, offering scalable pathways for developing machine learning solutions that enhance energy efficiency and smart building operations. The ADRENALIN Load Disaggregation Challenge addressed a central problem in energy analytics—non-intrusive load monitoring (NILM) of heating and cooling loads in commercial buildings—while emphasizing the importance of model generalization across different buildings. This paper presents a comprehensive reflection on the lessons learned from organizing and executing the ADRENALIN competition, including technical insights, organizational challenges, and recommendations for future energy data challenges. In addition to the ADRENALIN case, a …

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Misplay Or Malice? Players’ Interpretations Of Poor Gameplay In Competitive Team-Based Multiplayer Online Games, Valerie Yu, Benjamin H. Detenber, Sonny Rosenthal Aug 2026

Misplay Or Malice? Players’ Interpretations Of Poor Gameplay In Competitive Team-Based Multiplayer Online Games, Valerie Yu, Benjamin H. Detenber, Sonny Rosenthal

Research Collection College of Integrative Studies

Research on perceptions of gaming toxicity has focused on its verbal forms, while gameplay-related forms remain relatively understudied. Furthermore, assessments of gameplay actions as toxic may depend on situational considerations. The present study used a controlled experiment to examine player interpretations of gameplay sabotage using pre-recorded gameplay scenarios from the game, League of Legends. We found that the presence of gameplay sabotage elicited stronger negative emotions and triggered greater player-reported intentions to retaliate and correct the offending player than in comparable instances of unintentional poor gameplay. Further exploratory analyses suggested that participants rated poor gameplay as less acceptable in more …

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Definitions And Mathematical Models Of Op Variants, Pieter Vansteenwegen, Aldy Gunawan Aug 2026

Definitions And Mathematical Models Of Op Variants, Pieter Vansteenwegen, Aldy Gunawan

Research Collection School Of Computing and Information Systems

We have described the basic orienteering problem (OP) in Chap. 2, as one known variant of the single vehicle routing problems with profits (VRPP). In this chapter, we introduce the best-known variants of the OP. The first one is the team orienteering problem (TOP). In the TOP multiple routes can be composed to visit a subset of customers. In the context of the game of orienteering, the TOP corresponds to several players of the same team, each collecting profits in parallel, during the same time span. Another well-known variant of the basic OP is the OP with time windows (OPTW), …

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Efficient Test-Time Retrieval Augmented Generation, Hailong Yin, Bin Zhu, Jingjing Chen, Chong-Wah Ngo Aug 2026

Efficient Test-Time Retrieval Augmented Generation, Hailong Yin, Bin Zhu, Jingjing Chen, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Although Large Language Models (LLMs) demonstrate significant capabilities, their reliance on parametric knowledge often leads to inaccuracies. Retrieval Augmented Generation (RAG) mitigates this by incorporating external knowledge, but these methods may introduce irrelevant retrieved documents, leading to inaccurate responses. While the integration methods filter out incorrect answers from multiple responses, but lack external knowledge like RAG methods, and their high costs require balancing overhead with performance gains. To address these issues, we propose an Efficient Test-Time Retrieval-Augmented Generation Framework named ET2RAG to improve the performance of LLMs while maintaining efficiency. Specifically, ET2RAG is a training-free method, that first retrieves the …

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The Treatment Of Digital Assets In Insolvency, Nydia Remolina Leon, Aurelio Gurrea-Martinez, Daniel Liu Aug 2026

The Treatment Of Digital Assets In Insolvency, Nydia Remolina Leon, Aurelio Gurrea-Martinez, Daniel Liu

Research Collection Yong Pung How School Of Law

This article provides a comprehensive analysis of the treatment of digital assets in insolvency. Given that cryptoassets can be the subject of various transactions—including purchase, sale, custody, and lending—understanding their nature and implications in insolvency is relevant for any firm, not just cryptoexchanges. The article begins by offering a general overview of the world of cryptoassets. It then examines the nature of cryptoassets from accounting, financial, and legal perspectives. While much of the literature on insolvency and cryptoassets has primarily focused on the analysis of whether cryptocurrencies constitute property of the estate, this article explores additional issues, such as the …

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Emerging Library Leaders’ Summer School For Asia-Pacific (Ellssa): Smu Libraries Flagship Leadership Development Program For Librarians, Rajendra Munoo, Sumita Govindan Jul 2026

Emerging Library Leaders’ Summer School For Asia-Pacific (Ellssa): Smu Libraries Flagship Leadership Development Program For Librarians, Rajendra Munoo, Sumita Govindan

Research Collection Library

Strong leadership skills are becoming more important for librarians as they deal with rapid digital change in a VUCA world, rising user expectations, and a workforce made up of different generations. The Emerging Library Leaders’ Summer School for Asia-Pacific (ELLSSA) is Singapore Management University (SMU) Libraries’ main leadership development program, created to prepare early‑career librarians and high‑potential staff for future leadership roles across the Asia‑Pacific region and beyond. Recognised by the International Federation of Library Associations and Institutions (IFLA) as one of only a small number of leadership programs in the region, ELLSSA helps address gaps in leadership development within …

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Multimodal Contrastive Spatiotemporal Self-Organizing Neural Networks For In-Home Activity Learning Of Mild Cognitive Impairment, Seng Khoon Teh, Ah-Hwee Tan, Kar Way Tan, Iris Rawtaer Jul 2026

Multimodal Contrastive Spatiotemporal Self-Organizing Neural Networks For In-Home Activity Learning Of Mild Cognitive Impairment, Seng Khoon Teh, Ah-Hwee Tan, Kar Way Tan, Iris Rawtaer

Research Collection School Of Computing and Information Systems

In-home spatiotemporal data, such as the movement trajectory data and the spatial time series data, contains potential predictive utility for detection of geriatric conditions including Mild Cognitive Impairment (MCI), frailty, and cognitive frailty. However, few have explored spatiotemporal learning models for learning and fusion of such disparate spatiotemporal data, owing to the lack of a generalized machine learning model that can jointly model these different spatiotemporal data types. This work reports a multimodal spatiotemporal machine learning model based on a class of self-organizing neural networks that can integrate different spatiotemporal data types for MCI detection. Specifically, Episodic Memory Adaptive Resonance …

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Configuring Agentic Ai Coding Tools: An Exploratory Study, Matthias Galster, Seyedmoein Mohsenimofidi, Jai Lal Lulla, Muhammad Auwal Abubakar, Christoph Treude, Sebastian Baltes Jul 2026

Configuring Agentic Ai Coding Tools: An Exploratory Study, Matthias Galster, Seyedmoein Mohsenimofidi, Jai Lal Lulla, Muhammad Auwal Abubakar, Christoph Treude, Sebastian Baltes

Research Collection School Of Computing and Information Systems

Agentic AI coding tools increasingly automate software development tasks. Developers can configure these tools through versioned repository-level artifacts such as Markdown and JSON files. We present a systematic analysis of configuration mechanisms for agentic AI coding tools, covering Claude Code, GitHub Copilot, Cursor, Gemini, and Codex. We identify eight configuration mechanisms spanning from static context to executable and external integrations and, in an empirical study of 2,853 GitHub repositories, examine whether and how they are adopted, with a detailed analysis of Context Files, Skills, and Subagents. First, Context Files dominate the configuration landscape and are often the sole mechanism in …

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Air: Improving Agent Safety Through Incident Response, Zibo Xiao, Jun Sun, Junjie Chen Jul 2026

Air: Improving Agent Safety Through Incident Response, Zibo Xiao, Jun Sun, Junjie Chen

Research Collection School Of Computing and Information Systems

Large Language Model (LLM) agents are increasingly deployed in practice across a wide range of autonomous applications. Yet current safety mechanisms for LLM agents focus almost exclusively on preventing failures in advance, providing limited capabilities for responding to, containing, or recovering from incidents after they inevitably arise. In this work, we introduce AIR, the first incident response framework for LLM agent systems. AIR defines a domain-specific language for managing the incident response lifecycle autonomously in LLM agent systems, and integrates it into the agent's execution loop to (1) detect incidents via semantic checks grounded in the current environment state and …

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The Allure Of A Slow Life Strategy: How Mating Context And Ecological Harshness Shape Mate Preferences, Lynn K. L. Tan, Nicole Ruiying Chen, Kenneth Tan, Norman P. Li Jul 2026

The Allure Of A Slow Life Strategy: How Mating Context And Ecological Harshness Shape Mate Preferences, Lynn K. L. Tan, Nicole Ruiying Chen, Kenneth Tan, Norman P. Li

Research Collection School of Social Sciences

Although mate preferences have been extensively studied across various factors such as physical attractiveness or social status, their connection to life history strategy remains underexplored. Specifically, do individuals prefer mates who display signs of a fast or slow strategy? And what might qualify these preferences? Drawing from life history theory, we suggest that mate preferences are sensitive to cues of prospective mates' life history strategy, and that these preferences are malleable and shaped by ecological conditions. We hypothesize that in general, individuals will favor slow (versus fast) strategists as a mate. This is because modern environments are generally defined by …

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Cyberbullying Perpetration: A Systematic Review Of Global Prevalence, Profiles, Antecedents, Consequences, And Interventions, Ysabel A. Guevarra, K. T. A. Sandeeshwara Kasturiratna, Charlotte K. Y. Lee, Andree Hartanto Jul 2026

Cyberbullying Perpetration: A Systematic Review Of Global Prevalence, Profiles, Antecedents, Consequences, And Interventions, Ysabel A. Guevarra, K. T. A. Sandeeshwara Kasturiratna, Charlotte K. Y. Lee, Andree Hartanto

Research Collection School of Social Sciences

The anonymity afforded by cyberspace enables individuals to engage in harmful online behaviours, most notably cyberbullying perpetration, which has become a pressing social and psychological concern worldwide. Despite extensive research on its antecedents, outcomes and interventions, insights into cyberbullying perpetration remain scattered, highlighting the value of a comprehensive synthesis to capture its multifaceted nature. This systematic review synthesised findings from 54 meta-analyses, comprising 314 effect sizes (Sample size: Range = 3273–1,479,614, Mdn = 46,604) across diverse populations worldwide. Results indicate that approximately one in ten individuals engage in peer cyberbullying, with even higher prevalence in partner-directed forms such as cyber …

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Spatiotemporal Evolution And Influencing Factors Of The Coupling Coordination Between Agricultural Digitalization And Agricultural New Quality Productive Forces, Yuan Wang, Xiaoyuan Zhao, Chengxue Yang, Min Su Jul 2026

Spatiotemporal Evolution And Influencing Factors Of The Coupling Coordination Between Agricultural Digitalization And Agricultural New Quality Productive Forces, Yuan Wang, Xiaoyuan Zhao, Chengxue Yang, Min Su

Research Collection School of Social Sciences

The mutually reinforcing and coordinated development of Agricultural Digitalization (AD) and Agricultural New Quality Productive Forces (ANQPF) is an important path to achieving the modernization of agriculture and rural areas. Utilizing panel data from 31 provinces spanning 2012 to 2023, this study employs an Improved Coupling Coordination Degree Model (ICCDM), an Obstacle Degree Model (ODM), and a Random Effects Panel Tobit Model to investigate the spatiotemporal evolution patterns and the internal and external determinants of the Coupling Coordination Degree (CCD) between AD and ANQPF. The results indicate that: (1) From 2012 to 2023, both AD and ANQPF exhibited a steady …

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A Framework For Top-K Queries With Constrained Preferences, Kyriakos Mouratidis, Nikolaos Chaloulakos, Bo Tang Jul 2026

A Framework For Top-K Queries With Constrained Preferences, Kyriakos Mouratidis, Nikolaos Chaloulakos, Bo Tang

Research Collection School Of Computing and Information Systems

Traditional rank-aware processing assumes a dataset that contains available options to cover a specific need (e.g., restaurants, hotels, etc) and users who browse that dataset via top-k queries with linear scoring functions, i.e., by ranking the options according to the weighted sum of their attributes, for a set of given weights. In practice, however, user preferences (weights) may only be estimated with bounded accuracy, or may be inherently imprecise due to the inability of a human user to specify exact weight values with absolute accuracy. Motivated by this, we define the constrained-preference top-k (CT) query. Given an approximate description of …

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Robust Graph Learning On The Web: Challenges, Methods, And Applications, Ao Xiang, Yang Liu, Guansong Pang, Yuanhao Ding, Hezhe Qiao, Dawei Cheng, Qing He Jul 2026

Robust Graph Learning On The Web: Challenges, Methods, And Applications, Ao Xiang, Yang Liu, Guansong Pang, Yuanhao Ding, Hezhe Qiao, Dawei Cheng, Qing He

Research Collection School Of Computing and Information Systems

Graph learning is transforming web intelligence, powering applications from recommender systems to anomaly detection. However, most existing approaches implicitly assume ideal conditions where training and testing data are accurate, complete, and free from manipulation. In reality, web environments rarely exhibit such stability. Dynamic user behavior, incomplete or outdated content, adversarial interference, and sudden distribution shifts can all erode the reliability of even state-of-the-art models, leading to biased or unsafe outcomes. This tutorial provides a comprehensive survey of emerging strategies for robust graph learning on the web. We first present a structured taxonomy of the principal robustness threats specific to web …

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Income Tax Over-Withholding And Household Investment Decisions, Xi Novia Chen, Jungbae Kim, Ben Lourie, Chenqi Zhu Jul 2026

Income Tax Over-Withholding And Household Investment Decisions, Xi Novia Chen, Jungbae Kim, Ben Lourie, Chenqi Zhu

Research Collection School Of Accountancy

Over three-quarters of U.S. taxpayers over-withhold taxes, leading to tax refunds. This study explores how over-withholding impacts stock investments by comparing individuals' investment patterns from wages and tax refunds. We find that while some portion of tax refunds are promptly invested, the investment rate is lower than that of wages. This suggests that over-withholding, which alters the label and timing of wages into refunds, influences investment behavior. Our cross-sectional analysis indicates that the differential propensity to invest wages versus tax refunds are more pronounced for individuals with automatic investment setups and lower financial sophistication. These findings underscore the importance of …

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Beyond Earnings Quality: Evaluating The Quality Of Corporate Disclosure Practices, Patricia M. Dechow, Weili Ge, Wei Ting Loh Jul 2026

Beyond Earnings Quality: Evaluating The Quality Of Corporate Disclosure Practices, Patricia M. Dechow, Weili Ge, Wei Ting Loh

Research Collection School Of Accountancy

We propose a framework to assess the decision-usefulness of heterogeneous disclosure practices that managers use to convey information to market participants. We illustrate an application of our framework to non-GAAP earnings, management earnings guidance, and earnings conference calls. We first identify key quality attributes for each disclosure practice and then develop a list of quality metrics that we apply to a small pilot sample. We focus on metrics that are easily measured in real time and discuss the practical challenges of conducting assessments of disclosure quality at the firm-quarter-disclosure level. Our descriptive analysis provides preliminary insights into whether and how …

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Social Mobility Beliefs Predict Competence Stereotype Gaps Between The Poor And Rich, Gregory Tee Hng Tan Jul 2026

Social Mobility Beliefs Predict Competence Stereotype Gaps Between The Poor And Rich, Gregory Tee Hng Tan

Dissertations and Theses Collection (Open Access)

The poor tend to be viewed as less competent than the rich. This dissertation examined whether social mobility beliefs shape perceived rich-poor competence gaps. When society is seen as highly mobile, people may attribute economic outcomes to internal abilities than external constraints, thereby widening the rich-poor competence gap. Conversely, perceiving low mobility may shift explanations away from internal abilities toward external constraints and narrow the gap. Four studies tested this theory. Study 1 examined the relationships between self-reported mobility beliefs, attributions, and competence of rich and poor targets among Singapore and UK participants. While higher mobility beliefs predicted stronger internal …

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Constrained Assortment Optimization Under The Mixed-Logit Model, Hoang Giang Pham, Tien Mai Jul 2026

Constrained Assortment Optimization Under The Mixed-Logit Model, Hoang Giang Pham, Tien Mai

Research Collection School Of Computing and Information Systems

In this paper, we study the assortment optimization problem under the mixed-logit customer choice model. While assortment optimization has been a central topic in revenue management for decades, the mixed-logit model is widely regarded as one of the most general and flexible frameworks for modeling and predicting customer purchasing behavior. The assortment optimization problem is known to be NP-hard to be approximated to any constant factor, even in the unconstrained case. To address this challenge, we first explore the submodularity properties of a simplified version of the objective function to derive novel semi-constant factor approximation solutions for assortment problems under …

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