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Articles 1 - 30 of 18026
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Anger And Disgust Shape Judgments Of Social Sanctions Across Cultures, Especially In High Individual Autonomy Societies, Per A. Andersson, Andree Hartanto, Et Al
Anger And Disgust Shape Judgments Of Social Sanctions Across Cultures, Especially In High Individual Autonomy Societies, Per A. Andersson, Andree Hartanto, Et Al
Research Collection School of Social Sciences
When someone violates a social norm, others may think that some sanction would be appropriate. We examine how the experience of emotions like anger and disgust relate to the judged appropriateness of sanctions, in a pre-registered analysis of data from a large-scale study in 56 societies. Across the world, we find that individuals who experience anger and disgust over a norm violation are more likely to endorse confrontation, ostracism and, to a smaller extent, gossip. Moreover, we find that the experience of anger is consistently the strongest predictor of judgments of confrontation, compared to other emotions. Although the link between …
Bubbly Booms And Welfare, Feng Dong, Yang Jiao, Haoning Sun
Bubbly Booms And Welfare, Feng Dong, Yang Jiao, Haoning Sun
Research Collection School Of Economics
We show the competing effects of a housing bubble on the real economy by developing a multi-sector dynamic model with housing production. On the one hand, firms can sell or collateralize their housing, so a housing bubble helps firms obtain credit to finance their investment and expand production. On the other hand, a boom in the housing sector crowds out labor in the non-housing sector. We show that housing booms can reduce social welfare both in the steady state and in the transitional dynamics only when the production externalities in the non-housing sector are sufficiently large. We quantitatively evaluate our …
Cross-Exchange Crypto Risk: A High-Frequency Dynamic Network Perspective, Yifu Wang, Wanbo Lu, Min-Bin Liu, Rui Ren, Wolfgang Karl Hardle
Cross-Exchange Crypto Risk: A High-Frequency Dynamic Network Perspective, Yifu Wang, Wanbo Lu, Min-Bin Liu, Rui Ren, Wolfgang Karl Hardle
Sim Kee Boon Institute for Financial Economics
Cross-exchange crypto trading presents inherent risks, particularly for centralized exchanges. Investors observe exacerbating crypto volatility and counterparty risk and would like to quantify these elements of crypto trades. The multiple exchanges require a multivariate view on the structures of risk spillover across exchanges. Here, a Multivariate Heterogeneous AutoRegression (MHAR) model is designed and analyzed, accommodating the stylized facts of crypto markets, including 24/7 trading and the long-memory effect on return variations. The proposed MHAR approach clearly reveals the intensity of interconnectedness among exchanges during extreme events, e.g., the Bitcoin market. Additionally, one observes extremely volatile eigenvector centralities of Futures Exchange …
Hierarchical Damage Correlations For Old Photo Restoration, Weiwei Cai, Xuemiao Xu, Jiajia Xu, Huaidong Zhang, Haoxin Yang, Kun Zhang, Shengfeng He
Hierarchical Damage Correlations For Old Photo Restoration, Weiwei Cai, Xuemiao Xu, Jiajia Xu, Huaidong Zhang, Haoxin Yang, Kun Zhang, Shengfeng He
Research Collection School Of Computing and Information Systems
Restoring old photographs can preserve cherished memories. Previous methods handled diverse damages within the same network structure, which proved impractical. In addition, these methods cannot exploit correlations among artifacts, especially in scratches versus patch-misses issues. Hence, a tailored network is particularly crucial. In light of this, we propose a unified framework consisting of two key components: ScratchNet and PatchNet. In detail, ScratchNet employs the parallel Multi-scale Partial Convolution Module to effectively repair scratches, learning from multi-scale local receptive fields. In contrast, the patch-misses necessitate the network to emphasize global information. To this end, we incorporate a transformer-based encoder and decoder …
Unveiling The Dynamics Of Crisis Events: Sentiment And Emotion Analysis Via Multi-Task Learning With Attention Mechanism And Subject-Based Intent Prediction, Phyo Yi Win Myint, Siaw Ling Lo, Yuhao Zhang
Unveiling The Dynamics Of Crisis Events: Sentiment And Emotion Analysis Via Multi-Task Learning With Attention Mechanism And Subject-Based Intent Prediction, Phyo Yi Win Myint, Siaw Ling Lo, Yuhao Zhang
Research Collection School Of Computing and Information Systems
In the age of rapid internet expansion, social media platforms like Twitter have become crucial for sharing information, expressing emotions, and revealing intentions during crisis situations. They offer crisis responders a means to assess public sentiment, attitudes, intentions, and emotional shifts by monitoring crisis-related tweets. To enhance sentiment and emotion classification, we adopt a transformer-based multi-task learning (MTL) approach with attention mechanism, enabling simultaneous handling of both tasks, and capitalizing on task interdependencies. Incorporating attention mechanism allows the model to concentrate on important words that strongly convey sentiment and emotion. We compare three baseline models, and our findings show that …
Assessing Impact Of Urban Densification On Outdoor Microclimate And Thermal Comfort Using Envi-Met Simulations For Combined Spatial-Climatic Design (Cscd) Approach, Shreya Banerjee, Rachel X.Y. Pek, Sin Kang Yik, Graces N. Ching, Xiang Tian Ho, Dzyuban Yuliya, Peter J. Crank, Juan A. Acero, Winston T. L. Chow
Assessing Impact Of Urban Densification On Outdoor Microclimate And Thermal Comfort Using Envi-Met Simulations For Combined Spatial-Climatic Design (Cscd) Approach, Shreya Banerjee, Rachel X.Y. Pek, Sin Kang Yik, Graces N. Ching, Xiang Tian Ho, Dzyuban Yuliya, Peter J. Crank, Juan A. Acero, Winston T. L. Chow
Research Collection College of Integrative Studies
Future urban planning requires context-specific integration of spatial design and microclimate especially for tropical cities with extreme weather conditions. Thus, we propose a Combined Spatial-Climatic Design approach to assess impact of urban densification on annual outdoor thermal comfort performance employing ENVI-met simulations for Singapore. We first consider building bylaws and residential site guidelines to develop eight urban-density site options for a target population range. We further classify annual weather data into seven weather-types and use them as boundary conditions for the simulations. Comparing such fifty-six combined spatial-climatic simulation outputs by analyzing Outdoor Thermal Comfort Autonomy, we report the influence of …
On-Site Sensory Experience Boosts Acceptance Of Cultivated Chicken, Mark Chong, Angela K. Y. Leung, Tricia Marjorie Fernandez
On-Site Sensory Experience Boosts Acceptance Of Cultivated Chicken, Mark Chong, Angela K. Y. Leung, Tricia Marjorie Fernandez
Research Collection Lee Kong Chian School Of Business
This study set out to assess if presenting cultivated chicken in the context of a familiar meal, in a familiar dining setting, would motivate repeat consumption and recommendation. A survey of 107 diners was conducted at Huber's Butchery and Bistro in Singapore – the world's first butchery to serve cultivated meat – from April to June 2023. The findings showed that eating cultivated chicken significantly boosted post-consumption acceptance levels. In addition, cultivated chicken's tastiness may be a more important factor than its integration into a familiar meal or dish in fostering repeat consumption. Implications for the cultivated meat industry, limitations, …
Silver Screen Reversals Of The Domino Theory: American Cold War Movies And The Re-Imagination Of British Experiences In Southeast Asia, Wen-Qing (Wei Wenqing) Ngoei
Silver Screen Reversals Of The Domino Theory: American Cold War Movies And The Re-Imagination Of British Experiences In Southeast Asia, Wen-Qing (Wei Wenqing) Ngoei
Research Collection School of Social Sciences
This essay examines how Hollywood was affected by the successful anticommunism of Britain and its local allies in Malaya and Singapore, victories that unfolded alongside Vietnam’s mounting crisis in the early 1960s. It shows that American movies of this era which portrayed the intertwining of US and British experiences in 1950s Malaya and 1940s Singapore conveyed an uneasy yet clear optimism about U.S. involvement in Southeast Asia.
An Adaptive Large Neighborhood Search For The Multi-Vehicle Profitable Tour Problem With Flexible Compartments And Mandatory Customers, Vincent F. Yu, Nabila Yuraisyah Salsabila, Aldy Gunawan, Anggun Nurfitriani Handoko
An Adaptive Large Neighborhood Search For The Multi-Vehicle Profitable Tour Problem With Flexible Compartments And Mandatory Customers, Vincent F. Yu, Nabila Yuraisyah Salsabila, Aldy Gunawan, Anggun Nurfitriani Handoko
Research Collection School Of Computing and Information Systems
The home-refill delivery system is a business model that addresses the concerns of plastic waste and its impact on the environment. It allows customers to pick up their household goods at their doorsteps and refill them into their own containers. However, the difficulty in accessing customers’ locations and product consolidations are undeniable challenges. To overcome these issues, we introduce a new variant of the Profitable Tour Problem, named the multi-vehicle profitable tour problem with flexible compartments and mandatory customers (MVPTPFC-MC). The objective is to maximize the difference between the total collected profit and the traveling cost. We model the proposed …
An Evaluation Of Heart Rate Monitoring With In-Ear Microphones Under Motion, Kayla-Jade Butkow, Ting Dang, Andrea Ferlini, Dong Ma, Yang Liu, Cecilia Mascolo
An Evaluation Of Heart Rate Monitoring With In-Ear Microphones Under Motion, Kayla-Jade Butkow, Ting Dang, Andrea Ferlini, Dong Ma, Yang Liu, Cecilia Mascolo
Research Collection School Of Computing and Information Systems
With the soaring adoption of in-ear wearables, the research community has started investigating suitable in-ear heart rate detection systems. Heart rate is a key physiological marker of cardiovascular health and physical fitness. Continuous and reliable heart rate monitoring with wearable devices has therefore gained increasing attention in recent years. Existing heart rate detection systems in wearables mainly rely on photoplethysmography (PPG) sensors, however, these are notorious for poor performance in the presence of human motion. In this work, leveraging the occlusion effect that enhances low-frequency bone-conducted sounds in the ear canal, we investigate for the first time in-ear audio-based motion-resilient …
The Governance Of Director Compensation, Lily Fang, Sterling Huang
The Governance Of Director Compensation, Lily Fang, Sterling Huang
Research Collection School Of Accountancy
The average total compensation of directors in U.S.-listed companies was $342,030 in 2020, 5.06 times the median household income. Directors set their own pay, giving rise to potential self-dealing. We argue and document that in the presence of self-dealing, external mechanisms such as legal standards act as effective means of governance. Following a landmark Delaware court ruling that subjected director pay to a more stringent legal standard, Delaware-incorporated firms reduced director compensation relative to non-Delaware firms and experienced positive and non-transient stock price reactions. Our results indicate that proper governance of director compensation enhances firm value.
Untangling Influence: The Effect Of Follower-Followee Comparison On Social Media Engagement, Yi Peng, Liling Lu
Untangling Influence: The Effect Of Follower-Followee Comparison On Social Media Engagement, Yi Peng, Liling Lu
Research Collection Lee Kong Chian School Of Business
Social media platforms and marketers are keen on identifying truly influential creators. Number of followers (i.e., those who follow creators) and number of followees (i.e., those who are followed by creators) serve as cues to infer creators' influence. However, a cue of creators' actual influence is under-addressed and its effect on social media engagement remains to be explored. This research fills the gap in the literature by investigating how the cue of creators' actual influence (i.e., follower-followee comparison) may affect followers' engagement behavior. The study further examines the moderation effects of media-, topic-, and creator-related factors. The present work leverages …
Allocating Vehicle Registration Permits, Massimiliano Landi, Domenico Menicucci
Allocating Vehicle Registration Permits, Massimiliano Landi, Domenico Menicucci
Research Collection School Of Economics
We compare social welfare, consumer surplus and profits in two different institutional settings in which an item whose quantity is fixed and controlled (vehicle registration permit) is allocated to the buyers of a complementary good (car). In the first setting, which resembles the way in which vehicle registration permits are allocated in Singapore, the central planner runs a uniform price auction for permits in which the consumers who bid the highest receive the permits and pay the highest losing bid. Then each winning consumer purchases a car from a seller. In the alternative setting, the central planner first allocates the …
Learning Adversarial Semantic Embeddings For Zero-Shot Recognition In Open Worlds, Tianqi Li, Guansong Pang, Xiao Bai, Jin Zheng, Lei Zhou, Xin Ning
Learning Adversarial Semantic Embeddings For Zero-Shot Recognition In Open Worlds, Tianqi Li, Guansong Pang, Xiao Bai, Jin Zheng, Lei Zhou, Xin Ning
Research Collection School Of Computing and Information Systems
Zero-Shot Learning (ZSL) focuses on classifying samples of unseen classes with only their side semantic information presented during training. It cannot handle real-life, open-world scenarios where there are test samples of unknown classes for which neither samples (e.g., images) nor their side semantic information is known during training. Open-Set Recognition (OSR) is dedicated to addressing the unknown class issue, but existing OSR methods are not designed to model the semantic information of the unseen classes. To tackle this combined ZSL and OSR problem, we consider the case of “Zero-Shot Open-Set Recognition” (ZS-OSR), where a model is trained under the ZSL …
Diffusion-Based Negative Sampling On Graphs For Link Prediction, Yuan Fang, Yuan Fang
Diffusion-Based Negative Sampling On Graphs For Link Prediction, Yuan Fang, Yuan Fang
Research Collection School Of Computing and Information Systems
Link prediction is a fundamental task for graph analysis with important applications on the Web, such as social network analysis and recommendation systems, etc. Modern graph link prediction methods often employ a contrastive approach to learn robust node representations, where negative sampling is pivotal. Typical negative sampling methods aim to retrieve hard examples based on either predefined heuristics or automatic adversarial approaches, which might be inflexible or difficult to control. Furthermore, in the context of link prediction, most previous methods sample negative nodes from existing substructures of the graph, missing out on potentially more optimal samples in the latent space. …
On The Feasibility Of Simple Transformer For Dynamic Graph Modeling, Yuxia Wu, Yuan Fang, Lizi Liao
On The Feasibility Of Simple Transformer For Dynamic Graph Modeling, Yuxia Wu, Yuan Fang, Lizi Liao
Research Collection School Of Computing and Information Systems
Dynamic graph modeling is crucial for understanding complex structures in web graphs, spanning applications in social networks, recommender systems, and more. Most existing methods primarily emphasize structural dependencies and their temporal changes. However, these approaches often overlook detailed temporal aspects or struggle with long-term dependencies. Furthermore, many solutions overly complicate the process by emphasizing intricate module designs to capture dynamic evolutions. In this work, we harness the strength of the Transformer’s self-attention mechanism, known for adeptly handling long-range dependencies in sequence modeling. Our approach offers a simple Transformer model, called SimpleDyG, tailored for dynamic graph modeling without complex modifications. We …
Multigprompt For Multi-Task Pre-Training And Prompting On Graphs, Xingtong Yu, Chang Zhou, Yuan Fang, Xinming Zhan
Multigprompt For Multi-Task Pre-Training And Prompting On Graphs, Xingtong Yu, Chang Zhou, Yuan Fang, Xinming Zhan
Research Collection School Of Computing and Information Systems
Graph Neural Networks (GNNs) have emerged as a mainstream technique for graph representation learning. However, their efficacy within an end-to-end supervised framework is significantly tied to the availability of task-specific labels. To mitigate labeling costs and enhance robustness in few-shot settings, pre-training on self-supervised tasks has emerged as a promising method, while prompting has been proposed to further narrow the objective gap between pretext and downstream tasks. Although there has been some initial exploration of prompt-based learning on graphs, they primarily leverage a single pretext task, resulting in a limited subset of general knowledge that could be learned from the …
Editorial: Emerging On-Demand Passenger And Logistics Systems: Modelling, Optimization, And Data Analytics, Jintao Ke, Hai Wang, Neda Masoud, Maximilian Schiffer, Goncalo H. A. Correia
Editorial: Emerging On-Demand Passenger And Logistics Systems: Modelling, Optimization, And Data Analytics, Jintao Ke, Hai Wang, Neda Masoud, Maximilian Schiffer, Goncalo H. A. Correia
Research Collection School Of Computing and Information Systems
The proliferation of smart personal devices and mobile internet access has fueled numerous advancements in on-demand transportation services. These services are facilitated by online digital platforms and range from providing rides to delivering products. Their influence is transforming transportation systems and leaving a mark on changing individual mobility, activity patterns, and consumption behaviors. For instance, on-demand transportation companies such as Uber, Lyft, Grab, and DiDi have become increasingly vital for meeting urban transportation needs by connecting available drivers with passengers in real time. The recent surge in door-to-door food delivery (e.g., Uber Eats, DoorDash, Meituan); grocery delivery (e.g., Amazon Fresh, …
Redriver: Runtime Enforcement For Autonomous Vehicles, Yang Sun, Christopher M. Poskitt, Xiaodong Zhang, Jun Sun
Redriver: Runtime Enforcement For Autonomous Vehicles, Yang Sun, Christopher M. Poskitt, Xiaodong Zhang, Jun Sun
Research Collection School Of Computing and Information Systems
Autonomous driving systems (ADSs) integrate sensing, perception, drive control, and several other critical tasks in autonomous vehicles, motivating research into techniques for assessing their safety. While there are several approaches for testing and analysing them in high-fidelity simulators, ADSs may still encounter additional critical scenarios beyond those covered once they are deployed on real roads. An additional level of confidence can be established by monitoring and enforcing critical properties when the ADS is running. Existing work, however, is only able to monitor simple safety properties (e.g., avoidance of collisions) and is limited to blunt enforcement mechanisms such as hitting the …
Exploring The Potential Of Chatgpt In Automated Code Refinement: An Empirical Study, Qi Guo, Shangqing Liu, Junming Cao, Xiaohong Li, Xin Peng, Xiaofei Xie, Bihuan Chen
Exploring The Potential Of Chatgpt In Automated Code Refinement: An Empirical Study, Qi Guo, Shangqing Liu, Junming Cao, Xiaohong Li, Xin Peng, Xiaofei Xie, Bihuan Chen
Research Collection School Of Computing and Information Systems
Code review is an essential activity for ensuring the quality and maintainability of software projects. However, it is a time-consuming and often error-prone task that can significantly impact the development process. Recently, ChatGPT, a cutting-edge language model, has demonstrated impressive performance in various natural language processing tasks, suggesting its potential to automate code review processes. However, it is still unclear how well ChatGPT performs in code review tasks. To fill this gap, in this paper, we conduct the first empirical study to understand the capabilities of ChatGPT in code review tasks, specifically focusing on automated code refinement based on given …
Green Transition And Financial Stability: The Role Of Green Monetary And Macroprudential Policies And Vouchers, Ying Tung Chan, Maria Teresa Punzi, Hong Zhao
Green Transition And Financial Stability: The Role Of Green Monetary And Macroprudential Policies And Vouchers, Ying Tung Chan, Maria Teresa Punzi, Hong Zhao
Sim Kee Boon Institute for Financial Economics
This paper analyzes a mix of alternative policies in supporting the green transition and the phase-out of fossil fuels, without compromising financial stability. An environmental dynamic stochastic general equilibrium (E-DSGE) model with two sectors (green and brown) and endogenous default is developed to assess potential climate-induced financial stability threats that can be mainly generated through physical and transition risks mechanism. Those risks are evaluated through a compound capital depreciation shock and a carbon tax shock. The paper offers several findings. First of all, a too stringent carbon tax would increase the medium-term default rate in both sectors, harming financial stability …
The Status Of Status Research: A Review Of The Types, Functions, Levels And Audiences, Matteo Prato, Gokhan Ertug, Fabrizio Castellucci, Tengjian Zou
The Status Of Status Research: A Review Of The Types, Functions, Levels And Audiences, Matteo Prato, Gokhan Ertug, Fabrizio Castellucci, Tengjian Zou
Research Collection Lee Kong Chian School Of Business
Our review of 154 articles published over the last decade portrays an evolution of status research. This body of literature has transitioned from viewing status as a monolithic construct to appreciating its inherently multidimensional nature, characterized by diverse types, functions, levels, and audience structures. Although this shift has expanded our knowledge, it has also introduced increased complexity and fragmentation. To systematize this scattered work on a multifaceted view of status, we develop a comprehensive framework that integrates the diverse research findings. For each constituent part of this framework, we review key themes and insights in the literature and outline future …
Covid-19 And Management Scholarship: Lessons For Conducting Impactful Research, Gerard George, Gokhan Ertug, Jonathan P. Doh, Johanna Mair, Ajnesh Prasad
Covid-19 And Management Scholarship: Lessons For Conducting Impactful Research, Gerard George, Gokhan Ertug, Jonathan P. Doh, Johanna Mair, Ajnesh Prasad
Research Collection Lee Kong Chian School Of Business
The COVID-19 pandemic provided an opportunity for management scholars to address large-scale and complex societal problems and strive for greater practical and policy impact. A brief overview of the most-cited work on COVID-19 reveals that, compared with their counterparts in other disciplines, leading management journals and professional associations lagged in providing a platform for high-impact research on COVID-19. To help management research play a more active role in responding to similar global challenges in the future, we propose an integrative framework that emphasizes a phenomenon’s impact, the conditions that the phenomenon creates at multiple levels, and the responses of actors …
Wild Bootstrap Inference For Instrumental Variables Regressions With Weak And Few Clusters, Wenjie Wang, Yichong Zhang
Wild Bootstrap Inference For Instrumental Variables Regressions With Weak And Few Clusters, Wenjie Wang, Yichong Zhang
Research Collection School Of Economics
We study the wild bootstrap inference for instrumental variable regressions under an alternative asymptotic framework that the number of independent clusters is fixed, the size of each cluster diverges to infinity, and the within cluster dependence is sufficiently weak. We first show that the wild bootstrap Wald test controls size asymptotically up to a small error as long as the parameters of endogenous variables are strongly identified in at least one of the clusters. Second, we establish the conditions for the bootstrap tests to have power against local alternatives. We further develop a wild bootstrap Anderson–Rubin test for the full-vector …
Housing Markets Since Shapley And Scarf, Mustafa Oguz Afacan, Gaoji Hu, Jiangtao Li
Housing Markets Since Shapley And Scarf, Mustafa Oguz Afacan, Gaoji Hu, Jiangtao Li
Research Collection School Of Economics
Shapley and Scarf (1974) appeared in the first issue of the Journal of Mathematical Economics, and is one of the journal’s most impactful publications. As we approach the remarkable milestone of the journal’s 50th anniversary (1974–2024), this article serves as a commemorative exploration of Shapley and Scarf (1974) and the extensive body of literature that follows it.
Marco: A Stochastic Asynchronous Concolic Explorer, Jie Hu, Yue Duan, Heng Yin
Marco: A Stochastic Asynchronous Concolic Explorer, Jie Hu, Yue Duan, Heng Yin
Research Collection School Of Computing and Information Systems
Concolic execution is a powerful program analysis technique for code path exploration. Despite recent advances that greatly improved the efficiency of concolic execution engines, path constraint solving remains a major bottleneck of concolic testing. An intelligent scheduler for inputs/branches becomes even more crucial. Our studies show that the previously under-studied branch-flipping policy adopted by state-of-the-art concolic execution engines has several limitations. We propose to assess each branch by its potential for new code coverage from a global view, concerning the path divergence probability at each branch. To validate this idea, we implemented a prototype Marco and evaluated it against the …
Siphoned Apart: A Portfolio Perspective On Order Flow Segmentation, Markus Baldauf, Joshua Mollner, Bart Zhou Yueshen
Siphoned Apart: A Portfolio Perspective On Order Flow Segmentation, Markus Baldauf, Joshua Mollner, Bart Zhou Yueshen
Research Collection Lee Kong Chian School Of Business
We study liquidity supply in fragmented markets. Market makers intermediate heterogeneous order flows, trading off spread revenue against inventory costs. Applying our model to payment for order flow (PFOF), we demonstrate that portfolio-based considerations of inventory management incentivize market makers to segment retail orders by siphoning them off-exchange. Banning order flow segmentation reduces total welfare, can make trading more costly for all investors, and can resolve a prisoner's dilemma among market makers. These results differentiate our inventory-based model from the existing information-based theories of PFOF.
Towards Low-Resource Rumor Detection: Unified Contrastive Transfer With Propagation Structure, Hongzhan Lin, Jing Ma, Ruichao Yang, Zhiwei Yang, Mingfei Cheng
Towards Low-Resource Rumor Detection: Unified Contrastive Transfer With Propagation Structure, Hongzhan Lin, Jing Ma, Ruichao Yang, Zhiwei Yang, Mingfei Cheng
Research Collection School Of Computing and Information Systems
The truth is significantly hampered by massive rumors that spread along with breaking news or popular topics. Since there is sufficient corpus gathered from the same domain for model training, existing rumor detection algorithms show promising performance on yesterday's news. However, due to a lack of substantial training data and prior expert knowledge, they are poor at spotting rumors concerning unforeseen events, especially those propagated in different languages (i.e., low-resource regimes). In this paper, we propose a simple yet effective framework with unified contrastive transfer learning, to detect rumors by adapting the features learned from well-resourced rumor data to that …
Acav: A Framework For Automatic Causality Analysis In Autonomous Vehicle Accident Recordings, Huijia Sun, Christopher M. Poskitt, Yang Sun, Jun Sun, Yuqi Chen
Acav: A Framework For Automatic Causality Analysis In Autonomous Vehicle Accident Recordings, Huijia Sun, Christopher M. Poskitt, Yang Sun, Jun Sun, Yuqi Chen
Research Collection School Of Computing and Information Systems
The rapid progress of autonomous vehicles (AVs) has brought the prospect of a driverless future closer than ever. Recent fatalities, however, have emphasized the importance of safety validation through large-scale testing. Multiple approaches achieve this fully automatically using high-fidelity simulators, i.e., by generating diverse driving scenarios and evaluating autonomous driving systems (ADSs) against different test oracles. While effective at finding violations, these approaches do not identify the decisions and actions that caused them -- information that is critical for improving the safety of ADSs. To address this challenge, we propose ACAV, an automated framework designed to conduct causality analysis for …
The Future Of The International Financial System: The Emerging Cbdc Network And Its Impact On Regulation, Heng Wang, Simin Gao
The Future Of The International Financial System: The Emerging Cbdc Network And Its Impact On Regulation, Heng Wang, Simin Gao
Research Collection Yong Pung How School Of Law
Central bank digital currency (CBDC) is a digital form of fiat currency. CBDC has the potential to be a game challenger in the international financial system, bringing increased complexities arising from technology and regulatory considerations, as well as generating greater currency competition. As more states begin exploring CBDC, the interactions between actors may lead to the emergence of a new CBDC network. What shape would the emerging CBDC network take? What would its network effects be? What would be the impact of the CBDC network on the international financial system, or the global financial network? This article explores these questions …