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Late-Night And Early-Morning Train Scheduling With Non-Traffic Hour Maintenance Window In Urban Rail Transit Systems, Yaochen Ma, Hai Yang, Hai Wang Jul 2026

Late-Night And Early-Morning Train Scheduling With Non-Traffic Hour Maintenance Window In Urban Rail Transit Systems, Yaochen Ma, Hai Yang, Hai Wang

Research Collection School Of Computing and Information Systems

Regular maintenance during non-traffic hours (NTH) is vital for the resilience of urban rail transit (URT) systems, yet an insufficient NTH maintenance window poses a challenge for URT systems in various cities. For instance, the Hong Kong MTR Corporation has noted that the required NTH maintenance time often exceeds the available window, prompting service adjustments such as earlier late-night closures and/or later early-morning starts. To address this challenge, this study develops an optimal scheduling framework that links late-night and early-morning URT services through the NTH maintenance window requirement to maximize public welfare. A Decoupled Optimization Model (DOM) first derives closed-form …

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Accountable Agents In Software Engineering: An Analysis Of Terms Of Service And A Research Roadmap, Christoph Treude Jul 2026

Accountable Agents In Software Engineering: An Analysis Of Terms Of Service And A Research Roadmap, Christoph Treude

Research Collection School Of Computing and Information Systems

AI coding assistants and autonomous agents are becoming integral to software development workflows, reshaping how code is produced, reviewed, and maintained. While recent research has focused mainly on the capabilities and impacts of productivity of these systems, much less attention has been paid to accountability: who is responsible when agents generate, modify, or recommend code? In practice, accountability is defined through the Terms of Service (ToS) and related policy documents that govern the use of AI-powered development tools.In this vision paper, we present a comparative analysis of the Terms of Service for widely used AI coding assistants and agent-enabled development …

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Operationalizing Ethics For Ai Agents: How Developers Encode Values Into Repository Context Files, Christoph Treude, Sebastian Baltes, Marc Cheong Jul 2026

Operationalizing Ethics For Ai Agents: How Developers Encode Values Into Repository Context Files, Christoph Treude, Sebastian Baltes, Marc Cheong

Research Collection School Of Computing and Information Systems

As AI coding agents become embedded in software development workflows, developers are beginning to operationalize ethical principles by encoding behavioral rules into repository-level context files for AI agents, such as AGENTS.md files. Rather than examining the ethics of AI agents in the abstract, this vision paper investigates how ethics and values are already being translated for AI agents into actionable instructions that shape agent behavior. Through a preliminary investigation, we find that developers are already embedding guidance related to fairness, accessibility, sustainability, tone, and privacy. These artifacts function as a developer-authored governance layer, translating abstract principles into situated, natural-language directives …

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A Dataset Of Agentic Ai Coding Tool Configurations, Matthias Galster, Seyedmoein Mohsenimofidi, Levi Böhme, Jai Lal Lulla, Muhammad Auwal Abubakar, Christoph Treude, Sebastian Baltes Jul 2026

A Dataset Of Agentic Ai Coding Tool Configurations, Matthias Galster, Seyedmoein Mohsenimofidi, Levi Böhme, Jai Lal Lulla, Muhammad Auwal Abubakar, Christoph Treude, Sebastian Baltes

Research Collection School Of Computing and Information Systems

Agentic AI coding tools such as Claude Code and OpenAI Codex execute multi-step coding tasks with limited human oversight. To steer these tools, developers create repository-level configuration artifacts (e.g., Markdown files) for configuration mechanisms such as Context Files, Skills, Rules, and Hooks. There is no curated dataset yet that captures these configurations at scale. This dataset, collected from open-source GitHub repositories, fills that gap. We selected 40,585 actively maintained repositories through metadata filtering, classified them using GPT-5.2 to identify 36,710 as belonging to engineered software projects, and systematically detected configuration artifacts in these repositories. The dataset covers 4,738 repositories across …

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Spatiotemporal Sycophancy: Negation-Based Gaslighting In Video Large Language Models, Ziyao Tang, Pengkun Jiao, Bin Zhu, Huiyan Qi, Jingjing Chen, Yu-Gang Jiang Jul 2026

Spatiotemporal Sycophancy: Negation-Based Gaslighting In Video Large Language Models, Ziyao Tang, Pengkun Jiao, Bin Zhu, Huiyan Qi, Jingjing Chen, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

Video Large Language Models (Vid-LLMs) have demonstrated remarkable performance in video understanding tasks, yet their robustness under conversational interaction remains largely underexplored. In this paper, we identify spatiotemporal sycophancy, a failure mode in which Vid-LLMs retract initially correct, visually grounded judgments and conform to misleading user feedback under negation-based gaslighting. Rather than merely changing their answers, the models often fabricate unsupported temporal or spatial explanations to justify incorrect revisions. To systematically investigate this phenomenon, we propose a negation-based gaslighting evaluation framework and introduce GasVideo-1000, a curated benchmark designed to probe spatiotemporal sycophancy with clear visual grounding and temporal reasoning requirements. …

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Oscbench: Benchmarking Object State Change In Text-To-Video Generation, Xianjing Han, Bin Zhu, Shiqi Hu, Franklin Mingzhe Li, Patrick Carrington, Roger Zimmermann, Jingjing Chen Jul 2026

Oscbench: Benchmarking Object State Change In Text-To-Video Generation, Xianjing Han, Bin Zhu, Shiqi Hu, Franklin Mingzhe Li, Patrick Carrington, Roger Zimmermann, Jingjing Chen

Research Collection School Of Computing and Information Systems

Text-to-video (T2V) generation models have made rapid progress in producing visually high-quality and temporally coherent videos. However, existing benchmarks primarily focus on perceptual quality, text–video alignment, or physical plausibility, leaving a critical aspect of action understanding largely unexplored: object state change (OSC) explicitly specified in the text prompt. OSC refers to the transformation of an object’s state induced by an action, such as peeling a potato or slicing a lemon. In this paper, we introduce OSCBench, a benchmark specifically designed to assess OSC performance in T2V models. OSCBench is constructed from instructional cooking data and systematically organizes action–object interactions into …

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Tranx-Adapter: Bridging Artifacts And Semantics Within Mllms For Robust Ai-Generated Image Detection, Wenbin Wang, Yuge Huang, Jianqing Xu, Yue Yu, Jiangtao Yan, Shouhong Ding, Pan Zhou, Yong Luo Jul 2026

Tranx-Adapter: Bridging Artifacts And Semantics Within Mllms For Robust Ai-Generated Image Detection, Wenbin Wang, Yuge Huang, Jianqing Xu, Yue Yu, Jiangtao Yan, Shouhong Ding, Pan Zhou, Yong Luo

Research Collection School Of Computing and Information Systems

Rapid advances in AI-generated image (AIGI) technology enable highly realistic synthesis, threatening public information integrity and security. Recent studies have demonstrated that incorporating texture-level artifact features alongside semantic features into multimodal large language models (MLLMs) can enhance their AIGI detection capability. However, our preliminary analyses reveal that artifact features exhibit high intra-feature similarity, leading to an almost uniform attention map after the softmax operation. This phenomenon causes attention dilution, thereby hindering effective fusion between semantic and artifact features. To overcome this limitation, we propose a lightweight fusion adapter, TranX-Adapter, which integrates a Task-aware Optimal-Transport Fusion that leverages the Jensen-Shannon divergence …

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Rendering Data Unlearnable By Exploiting Llm Alignment Mechanisms, Ruihan Zhang, Jun Sun Jul 2026

Rendering Data Unlearnable By Exploiting Llm Alignment Mechanisms, Ruihan Zhang, Jun Sun

Research Collection School Of Computing and Information Systems

Large language models (LLMs) are increasingly trained on massive, heterogeneous text corpora, raising serious concerns about the unauthorised use of proprietary or personal data during model training. In this work, we address the problem of data protection against unwanted model learning in a realistic blackbox setting. We propose Disclaimer Injection, a novel data-level defence that renders text unlearnable to LLMs. Rather than relying on model-side controls or explicit data removal, our approach exploits the models’ own alignment mechanisms: injecting carefully designed alignment-triggers to prevent effective learning. Through layer-wise analysis, we find that finetuning on such protected data induces persistent activation …

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Commentary: Survey Finds Singapore Workers Disengaged - But We Shouldn’T Resign Ourselves To This, Nick Chiam Jul 2026

Commentary: Survey Finds Singapore Workers Disengaged - But We Shouldn’T Resign Ourselves To This, Nick Chiam

Research Collection Yong Pung How School Of Law

If narratives of unhappy and disengaged Singapore workers solidify, there will be less reason to strive for a better workplace, says SMU’s Nick Chiam.

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Locally Robust Implementation Of Efficient Bilateral Trade With Correlated Beliefs, Takashi Kunimoto, Cuiling Zhang Jul 2026

Locally Robust Implementation Of Efficient Bilateral Trade With Correlated Beliefs, Takashi Kunimoto, Cuiling Zhang

Research Collection School Of Economics

We identify the ex ante welfare (EAW) condition as a necessary requirement to implement ex post efficient bilateral trade in any finite type space with interdependent values and correlated beliefs. As these finite settings become finer to approximate a continuous type space, we derive a limit EAW condition by taking the EAW condition in finite settings to its limit. We show that this limit condition trivially holds in the benchmark continuous setting admitting a full-support density function. We then insist on locally robust implementation by requiring efficient trade to be implemented uniformly across all finite type spaces that approximate the …

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Occupation Ladders Over The Business Cycle, Ismail Baydur, Toshihiko Mukoyama Jul 2026

Occupation Ladders Over The Business Cycle, Ismail Baydur, Toshihiko Mukoyama

Research Collection School Of Economics

This paper studies occupational mobility over the business cycle. We divide occupations into two broad groups, “attractive” and “nonattractive”, where we label an occupation attractive if the total net inflow into this occupation through job-to-job transition is positive. We measure total net inflows into both occupation groups. We measure these inflows separately for job-to-job transitions and transitions from unemployment to employment. We find that the net inflow from nonattractive to attractive occupations through job-to-job transitions slows during recessions. The net inflow through transitions from unemployment has a similar cyclicality. This finding suggests a novel cost of recession: during recessions, workers …

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Sustainable Rural Development Under Ecological Civilization: Two Mountains Theory, “Green Rural Revival”, And Post-Productivist Transition In Zhejiang, Qian Forrest Zhang, Jianzhang Luo, Li Zhou Jul 2026

Sustainable Rural Development Under Ecological Civilization: Two Mountains Theory, “Green Rural Revival”, And Post-Productivist Transition In Zhejiang, Qian Forrest Zhang, Jianzhang Luo, Li Zhou

Research Collection School of Social Sciences

Existing studies of China’s overarching ideological framework for national development, “Ecological Civilization”, have focused narrowly on environmental governance; how it reshapes sustainable rural development remains underexplored. This paper pursues two analytically distinct tasks. First, it reconstructs the policy history of how President Xi Jinping’s “Two Mountains” theory was incorporated into the Eco-civilization framework and how Zhejiang Province’s “Green Rural Revival” (GRR) program, as a lived example of Eco-civilization, was elevated as the national template for rural development in 2024. Second, drawing on three cases from a sample of 21 villages in Zhejiang, it identifies three core practices of GRR and …

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Patent Regime Shift And Firm Innovation Strategy: Evidence From The Second Amendment To China's Patent Law, Tony W. Tong, Wenlong He, Liang Chen, Zi-Lin He, Jiangyong Lu Jul 2026

Patent Regime Shift And Firm Innovation Strategy: Evidence From The Second Amendment To China's Patent Law, Tony W. Tong, Wenlong He, Liang Chen, Zi-Lin He, Jiangyong Lu

Research Collection Lee Kong Chian School Of Business

Research Summary: While changes in intellectual property rights (IPR) protection significantly shape firm innovation, the mechanisms driving firms' responses remain poorly understood. Leveraging the Second Amendment to China's Patent Law, which strengthens appropriability particularly for state-owned enterprises (SOEs), as a natural experiment, we show that stronger IPR has mixed effects on SOEs' innovation. While SOEs increase the rate of innovation subsequent to the Amendment, they shift the direction of innovation toward more familiar areas in which they face a lesser need to adjust existing routines. This directional change suggests a quality decline in SOEs' innovation that may be attributed to …

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Through The Lens Of Clarity: Perceived Organizational Tightness Boosts Creativity For Men, But Not For Women, Grace J. H. Lim, Roy Y. J. Chua Jul 2026

Through The Lens Of Clarity: Perceived Organizational Tightness Boosts Creativity For Men, But Not For Women, Grace J. H. Lim, Roy Y. J. Chua

Research Collection Lee Kong Chian School Of Business

A commonly held perspective in the cultural tightness literature is that cultural tightness tends to negatively impact creativity. Yet some findings indicate that this relationship is not strictly negative and that a more nuanced perspective should be considered. Drawing on social information processing (SIP) theory and social role theory, we build theory on how the perception of organizational cultural tightness can increase creativity for some employees, but not for others. Specifically, we propose that perceived organizational tightness—the extent to which one perceives that an organization is characterized by strong norms and sanctions for deviation—increases clarity on creativity evaluation standards and …

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Operational Agency: A Permeable Legal Fiction For Tracing Culpability In Ai Systems, Anirban Mukherjee, Hannah H. Chang Jul 2026

Operational Agency: A Permeable Legal Fiction For Tracing Culpability In Ai Systems, Anirban Mukherjee, Hannah H. Chang

Research Collection Lee Kong Chian School Of Business

Modern artificial intelligence (AI) systems act with a high degree of independence yet lack legal personhood—a paradox that fractures doctrines grounded in human-centric notions of mens rea and actus reus. This Article introduces Operational Agency (OA)—a permeable legal fiction structured as an ex post evidentiary framework—and Operational Agency Graph (OAG)—a tool for mapping causal interactions among human actors, organizations, and AI systems. OA evaluates an AI’s observable operational characteristics: its goal-directedness (as a proxy for intent), predictive processing (as a proxy for foresight), and safety architecture (as a proxy for standard of care). OAG operationalizes that analysis by embedding these …

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Modeling And Forecasting Intraday Spot Volatility, Adam Clements, Daniel P. A. Preve Jul 2026

Modeling And Forecasting Intraday Spot Volatility, Adam Clements, Daniel P. A. Preve

Research Collection School Of Economics

We propose a multiple-equation regression-based method for modeling and forecasting intraday spot volatility. In this approach, intraday intervals are treated as individual time series, deviating from the common practice of treating the data as one continuous sample. Our empirical study, which spans more than two decades and encompasses six US blue-chip stocks, employs the recent OK volatility estimator developed by Li, Wang, and Zhang (2024) to expose the dynamics of latent intraday spot volatility over time. We demonstrate that the proposed method effectively captures the intricate dynamics of intraday spot volatility and find strong evidence that it outperforms a competing …

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Navigating Unemployment Without Unemployment Insurance: Evidence From Singapore, Kim, Lanjie Wang Jul 2026

Navigating Unemployment Without Unemployment Insurance: Evidence From Singapore, Kim, Lanjie Wang

Research Collection School Of Economics

This study investigates the short-term impacts of unemployment among older workers (aged 50–62) in Singapore, a setting with-out public unemployment insurance. Using monthly panel data from the Singapore Life Panel, we analyse dynamic effects onmajor life outcomes such as income, spending, health, and subjective wellbeing over 2 years post-unemployment. Our findingsreveal substantial initial earnings losses with incomplete recovery: income remains 50.7% below pre-unemployment levels after24 months. Despite this persistent income gap, total household expenditure declines by 9.8% on average over 2 years (rangingfrom 7% to 16% across months). The implied two-year marginal propensity to consume is about 0.182, smaller than …

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How Do Sectoral Shocks Shape Future Gdp?, Paul Ho, Danial Lashkari, Pierre-Daniel Sarte Jul 2026

How Do Sectoral Shocks Shape Future Gdp?, Paul Ho, Danial Lashkari, Pierre-Daniel Sarte

Research Collection School Of Economics

A production sector’s size, as measured by its Domar weight, captures the contemporaneous aggregate effect of its productivity shocks. Any future aggregate effects, however, depend on that sector’s participation in the investment network. We derive a dynamic generalization of Hulten’s theorem in an environment with intermediate-input and investment networks. This generalization, implied by production efficiency alone, decomposes each sector’s Domar weight into an impact and a propagation component. The relative size of these components then determines how persistent the aggregate effects of sectoral shocks are, but cannot be known absent information on the economy’s production structure. We show in a …

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The Effect Of Vaccine Mandates On Disease Spread: Evidence From College Covid-19 Mandates, Riley K. Acton, Wenjia Cao, Emily E. Cook, Scott A. Imberman, Michael F. Lovenheim Jul 2026

The Effect Of Vaccine Mandates On Disease Spread: Evidence From College Covid-19 Mandates, Riley K. Acton, Wenjia Cao, Emily E. Cook, Scott A. Imberman, Michael F. Lovenheim

Research Collection School Of Economics

Nearly 700 4-year U.S. colleges mandated students receive COVID-19 vaccinations in fall 2021. Using data on college policies and county health, we estimate how mandates affect surrounding communities. Event studies from August to November 2021 show that mandates covering all colleges in a county reduced COVID-19 deaths by 5.6 per 100,000 persons, a 4.6% reduction in the U.S. total during this period. Mandates reduced COVID cases by 504 and ICU admissions by 16.2 per 100,000, though we see no statistically significant impact on hospitalizations. Impacts are larger in counties with larger college populations and low estimated ex-ante student vaccination rates.

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The Unintended Consequences Of International Student Shortage: Evidence From South Korea, Chung-Yoon Choi, Syngjoo Choi, Seonghoon Kim, Jongkwan Lee Jul 2026

The Unintended Consequences Of International Student Shortage: Evidence From South Korea, Chung-Yoon Choi, Syngjoo Choi, Seonghoon Kim, Jongkwan Lee

Research Collection School Of Economics

We study the role of international students in the higher education sector and the local economy by exploiting a policy reform in South Korea that restricted the admission of foreign students to local universities. By comparing the pre- and post-reform differences across universities with different pre-reform shares of international student enrollment, we show that an international student shortage resulting from this policy reform significantly worsened the financial outcomes of universities and consequently led to reduced investment in their students. We also document that a reduction in the number of international students in local areas decreased native employment, mainly in low-skilled …

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Integrated Optimization Of Farmland Cultivation And Fertilizer Application: Implications For Farm Management And Crop Production, Onur Boyabatli, Lusheng Shao, Yangfang (Helen) Zhou Jul 2026

Integrated Optimization Of Farmland Cultivation And Fertilizer Application: Implications For Farm Management And Crop Production, Onur Boyabatli, Lusheng Shao, Yangfang (Helen) Zhou

Research Collection Lee Kong Chian School Of Business

Motivated by the fresh produce industry, this paper studies a farmer’s joint cultivation and fertilizer (a representative farm input) application decisions facing uncertainties in yield, crop price, and harvesting cost where the latter two are yield dependent and yield is stochastically increasing in the fertilizer application rate. We develop a two-stage stochastic model of a farmer growing a commodity crop in a single season to maximize the expected profit. We then use the model to evaluate the optimal expected harvest volume (a measure of crop production). Our analytical analysis is complemented with numerical experiments calibrated to data. We characterize how …

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Securing A Calibrated Marketing Budget, Junqiu Jiang, Kapil R. Tuli, Nirmalya Kumar Jul 2026

Securing A Calibrated Marketing Budget, Junqiu Jiang, Kapil R. Tuli, Nirmalya Kumar

Research Collection Lee Kong Chian School Of Business

This study investigates the sociopolitical processes underlying the development and approval of marketing budgets in large multinational corporations. While prior research has focused extensively on optimizing the level and allocation of marketing budgets, little attention has been paid to the internal organizational dynamics that shape the marketing budgeting process. Drawing on the theories-in-use of both CMOs and CEOs, this study examines how these executives codevelop a calibrated marketing budget (CMKB)—a budget that aligns expected performance with allocated resources through an iterative, participative process. Field data show that CMOs deploy a set of signals to assuage CEO concerns related to goal …

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The Power And Peril Of Awe In Leadership: Transforming Follower Identity And Behavior, Jack Mcguire, Daniel Mcallister, Jochen Menges, David De Cremer Jul 2026

The Power And Peril Of Awe In Leadership: Transforming Follower Identity And Behavior, Jack Mcguire, Daniel Mcallister, Jochen Menges, David De Cremer

Research Collection Lee Kong Chian School Of Business

Awe is a profound emotion that has captured significant attention within psychological research. While the potential for leaders to inspire awe in followers has received some recognition, systematic research on the nature and effects of awe in leadership—and within organizational contexts more broadly—remains limited. In this article, we offer a conceptual framework that explains the multifaceted and transformative nature of leadership through the power of awe. Specifically, we identify four leader behaviors—charismatic leadership tactics, exceptional performance, problem reframing, and self-sacrificial behavior—that elicit awe among followers. We further propose three variants of awe-inspiring leaders, describing how variation in a leader’s self-construal …

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The Anatomy Of Earnings Conference Calls: An Integrative Framework For Management Research, Matthew P. Mount, Gokhan Ertug, Wei Shi, Tengjian Zou Jul 2026

The Anatomy Of Earnings Conference Calls: An Integrative Framework For Management Research, Matthew P. Mount, Gokhan Ertug, Wei Shi, Tengjian Zou

Research Collection Lee Kong Chian School Of Business

Over the last decade, there has been an explosion in the use of diverse data sources by management scholars to observe and capture managerial and organizational constructs that have historically been difficult to access. This surge has been driven by the growing availability of rich, multi-modal data—textual, image, and audio (Luo, Jia, Ouyang, & Fang, 2024)—together with advances in analytical techniques to process and analyze data, such as computer-aided text analysis (Harrison, Thurgood, Boivie, & Pfarrer, 2019), machine learning (Choudhury, Wang, Carlson, & Khanna, 2019; Harrison, Josefy, Kalm, & Krause, 2023), and deep learning (Gouvard, Goldberg, & Srivastava, 2023). These …

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Keeping Up With The Times? Rethinking Social Evaluations Research Under Contemporary Technological And Sociopolitical Forces, Marco Clemente, Michael Etter, Yuliya Snihur, Gokhan Ertug, Graffin Scott, Anastasiya Zavyalova Jul 2026

Keeping Up With The Times? Rethinking Social Evaluations Research Under Contemporary Technological And Sociopolitical Forces, Marco Clemente, Michael Etter, Yuliya Snihur, Gokhan Ertug, Graffin Scott, Anastasiya Zavyalova

Research Collection Lee Kong Chian School Of Business

The context within which social evaluations form has been fundamentally altered by contemporary forces, such as digital technologies, polarization, activism, politicization of business, and geopolitical tensions. While research on social evaluations has generated rich insights into the formation and development of constructs, such as legitimacy, status, reputation, stigma, trust, and celebrity, much of this work has been developed under the assumptions of relative stability, coherent audiences, and well-defined intermediary roles. These assumptions are increasingly challenged in this changing context, requiring us to rethink the formation and management of social evaluations. The articles in this special issue focus on these changes. …

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Knowledge-State Generative Agents For Pre-Assessment Question Evaluation, Ping Fan Ke, Yi Meng Lau, Siaw Ling Lo Jul 2026

Knowledge-State Generative Agents For Pre-Assessment Question Evaluation, Ping Fan Ke, Yi Meng Lau, Siaw Ling Lo

Research Collection School Of Computing and Information Systems

This paper introduces a Knowledge‑State Generative Agent framework for evaluating the quality of pre‑assessment questions. The framework employs large language model (LLM)–based agents prompted to adopt a teacher persona to simulate the responses of students with and without mastery of targeted knowledge components. A preliminary empirical study using archival data from 424 students enrolled in an Information Systems Management course indicates that the proposed approach yields interpretable metrics under Classical Test Theory. Results further show that agents instantiated with the relevant mastered knowledge components exhibit systematically higher performance than agents lacking such mastery. In addition, the study suggests that teacher-persona …

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Dual-Diffusional Generative Fashion Recommendation, Mingzhe Yu, Lei Wu, Qianru Sun, Yunshan Ma Jul 2026

Dual-Diffusional Generative Fashion Recommendation, Mingzhe Yu, Lei Wu, Qianru Sun, Yunshan Ma

Research Collection School Of Computing and Information Systems

Personalized generative recommender systems have emerged as a promising solution for fashion recommendation. However, existing methods primarily rely on implicit visual embeddings from historical interactions, which often contain preference-irrelevant information and result in insufficient user behavior modeling. Moreover, these models typically generate only item images, providing limited interpretability. To address these limitations, we propose DualFashion, a Dual-Diffusional Generative Fashion Recommendation Architecture that jointly models image and text modalities for personalized and explainable recommendation. DualFashion adopts a dual-diffusion Transformer with image and text branches, where structured attribute-level captions and visual outfit information are jointly used as conditioning signals to model user …

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Avadclip: Audio-Visual Collaboration For Robust Video Anomaly Detection, Peng Wu, Wanshun Su, Guansong Pang, Yujia Sun, Qingsen Yan, Peng Wang, Yanning Zhang Jul 2026

Avadclip: Audio-Visual Collaboration For Robust Video Anomaly Detection, Peng Wu, Wanshun Su, Guansong Pang, Yujia Sun, Qingsen Yan, Peng Wang, Yanning Zhang

Research Collection School Of Computing and Information Systems

With the increasing adoption of video anomaly detection in intelligent surveillance domains, conventional visual-only detection approaches often struggle with information insufficiency and high false-positive rates in complex environments. To address these limitations, we present a novel weakly supervised framework that leverages audio-visual collaboration for robust video anomaly detection. Capitalizing on the exceptional cross-modal representation learning capabilities of Contrastive Language-Image Pretraining (CLIP) across visual, audio, and textual domains, our framework introduces two major innovations: an efficient audio-visual fusion that enables adaptive cross-modal integration through lightweight parametric adaptation while maintaining the frozen CLIP backbone, and a novel audio-visual prompt that dynamically enhances …

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Activity Transition Graph Generation: How Far Are We?, Jiakun Liu, Peixin Zhang, Han Hu, Yonghui Liu, Wei Minn, Ferdian Thung, Shahar Maoz, Eran Toch, Debin Gao, David Lo Jul 2026

Activity Transition Graph Generation: How Far Are We?, Jiakun Liu, Peixin Zhang, Han Hu, Yonghui Liu, Wei Minn, Ferdian Thung, Shahar Maoz, Eran Toch, Debin Gao, David Lo

Research Collection School Of Computing and Information Systems

Android applications (i.e., apps) are indispensable nowadays and are getting bigger and bigger with an increasing number offunctionalities. To understand how to access functionalities in an app, prior studies proposed tools to model the transitionsbetween functionalities with the activity transition graph (ATG). ATG is an important data structure and has been used forvarious Android app analyses, including app design, understanding, and testing. However, there is no benchmarking work onATG generation. It is still unclear whether the transitions identified by tools are correct and how many transitions are missed.To fill this gap, we manually identified all transitions in 98 applications to …

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Survey On Learning-Based Dynamic Fault Localization: From Traditional Machine Learning To Large Language Models, Chunyan Liu, Yan Lei, Huan Xie, Jinping Wang, Yue Yu, David Lo Jul 2026

Survey On Learning-Based Dynamic Fault Localization: From Traditional Machine Learning To Large Language Models, Chunyan Liu, Yan Lei, Huan Xie, Jinping Wang, Yue Yu, David Lo

Research Collection School Of Computing and Information Systems

Learning-based dynamic fault localization techniques play a crucial role in the field of software engineering. These techniques dynamically execute test cases to meticulously extract useful knowledge from the execution information in the program, with the aim of identifying fault locations by leveraging machine learning, deep learning, and large language models. Currently, there is already a flourishing body of research that is intensely focused on learning-based dynamic fault localization. Research literature can be categorized into two main aspects for learning-based dynamic fault localization: data-based enhancements (i.e., the datasets) and model-based enhancements (i.e., the suspiciousness algorithms). Thus, we conduct an extensive literature …

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