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Articles 2791 - 2820 of 23256
Full-Text Articles in Entire DC Network
Exploring Diffusion Time-Steps For Unsupervised Representation Learning, Zhongqi Yue, Jiankun Wang, Qianru Sun, Lei Ji, Eric I-Chao Chang, Hanwang Zhang
Exploring Diffusion Time-Steps For Unsupervised Representation Learning, Zhongqi Yue, Jiankun Wang, Qianru Sun, Lei Ji, Eric I-Chao Chang, Hanwang Zhang
Research Collection School Of Computing and Information Systems
Representation learning is all about discovering the hidden modular attributes that generate the data faithfully. We explore the potential of Denoising Diffusion Probabilistic Model (DM) in unsupervised learning of the modular attributes. We build a theoretical framework that connects the diffusion time-steps and the hidden attributes, which serves as an effective inductive bias for unsupervised learning. Specifically, the forward diffusion process incrementally adds Gaussian noise to samples at each time-step, which essentially collapses different samples into similar ones by losing attributes, e.g., fine-grained attributes such as texture are lost with less noise added (i.e., early time-steps), while coarse-grained ones such …
Regret-Based Defense In Adversarial Reinforcement Learning, Roman Belaire, Pradeep Varakantham, Thanh Hong Nguyen, David Lo
Regret-Based Defense In Adversarial Reinforcement Learning, Roman Belaire, Pradeep Varakantham, Thanh Hong Nguyen, David Lo
Research Collection School Of Computing and Information Systems
Deep Reinforcement Learning (DRL) policies are vulnerable to adversarial noise in observations, which can have disastrous consequences in safety-critical environments. For instance, a self-driving car receiving adversarially perturbed sensory observations about traffic signs (e.g., a stop sign physically altered to be perceived as a speed limit sign) can be fatal. Leading existing approaches for making RL algorithms robust to an observation-perturbing adversary have focused on (a) regularization approaches that make expected value objectives robust by adding adversarial loss terms; or (b) employing "maximin'' (i.e., maximizing the minimum value) notions of robustness. While regularization approaches are adept at reducing the probability …
Robust Auto-Scaling With Probabilistic Workload Forecasting For Cloud Databases, Haitian Hang, Xiu Tang, Jianling Sun, Lingfeng Bao, David Lo, Haoye Wang
Robust Auto-Scaling With Probabilistic Workload Forecasting For Cloud Databases, Haitian Hang, Xiu Tang, Jianling Sun, Lingfeng Bao, David Lo, Haoye Wang
Research Collection School Of Computing and Information Systems
Auto-scaling is crucial for achieving elasticity in cloud databases as well as other cloud systems. Predictive auto-scaling, which leverages forecasting techniques to adjust resources based on predicted workload, has been widely adopted. However, the inherent inaccuracy of forecasting presents a significant challenge, potentially causing resource under-provisioning. To address this challenge, we propose robust predictive auto-scaling that considers the uncertainty in forecasts. Unlike previous predictive approaches that rely on single-valued forecasts, we leverage probabilistic forecasting techniques to generate quan-tile forecasts, providing a more comprehensive understanding of the potential future workloads. By formulating the auto-scaling problem as a robust optimization problem, we …
Automatic Grading Of Short Answers Using Large Language Models In Software Engineering Courses, Nguyen Binh Duong Ta, Yi Meng Chai
Automatic Grading Of Short Answers Using Large Language Models In Software Engineering Courses, Nguyen Binh Duong Ta, Yi Meng Chai
Research Collection School Of Computing and Information Systems
Short-answer based questions have been used widely due to their effectiveness in assessing whether the desired learning outcomes have been attained by students. However, due to their open-ended nature, many different answers could be considered entirely or partially correct for the same question. In the context of computer science and software engineering courses where the enrolment has been increasing recently, manual grading of short-answer questions is a time-consuming and tedious process for instructors. In software engineering courses, assessments concern not just coding but many other aspects of software development such as system analysis, architecture design, software processes and operation methodologies …
Lecture-Style Tutorial: Towards Graph Foundation Models, Chuan Shi, Cheng Yang, Yuan Fang, Lichao Sun, Philip Yu
Lecture-Style Tutorial: Towards Graph Foundation Models, Chuan Shi, Cheng Yang, Yuan Fang, Lichao Sun, Philip Yu
Research Collection School Of Computing and Information Systems
Emerging as fundamental building blocks for diverse artificial intelligence applications, foundation models have achieved notable success across natural language processing and many other domains. Concurrently, graph machine learning has gradually evolved from shallow methods to deep models to leverage the abundant graph-structured data that constitute an important pillar in the data ecosystem for artificial intelligence. Naturally, the emergence and homogenization capabilities of foundation models have piqued the interest of graph machine learning researchers. This has sparked discussions about developing a next-generation graph learning paradigm, one that is pre-trained on broad graph data and can be adapted to a wide range …
Design Of Off-Grid Lighting Business Models To Serve The Poor: Field Experiments And Structural Analysis, Bhavani Shanker Uppari, Serguei Netessine, Ioana Popescu, Rowan P. Clarke
Design Of Off-Grid Lighting Business Models To Serve The Poor: Field Experiments And Structural Analysis, Bhavani Shanker Uppari, Serguei Netessine, Ioana Popescu, Rowan P. Clarke
Research Collection Lee Kong Chian School Of Business
A significant proportion of the world’s population has no access to grid-based electricity and so relies on off-grid lighting solutions. Rechargeable lamp technology is gaining popularity as an alternative off-grid lighting model in developing countries. In this paper, we explore consumer behavior and the operational inefficiencies that result under this model. Specifically, we are interested in (i) measuring the impact of inconvenience (of travelling to recharge the lamp) along with the impact of liquidity constraints (due to poverty) on lamp usage, and (ii) evaluating the efficacy of strategies that address these factors. We build a structural model of consumers’ recharge …
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 …
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 …
Smu Libraries – An Enabling Partner In Ai Information Literacy, Samantha Seah, Zhe Benedict Yeo, Lukas Tschopp
Smu Libraries – An Enabling Partner In Ai Information Literacy, Samantha Seah, Zhe Benedict Yeo, Lukas Tschopp
Research Collection Library
SMU Libraries plays a pivotal role in advancing AI information literacy within the larger need for digital literacy skills in the SMU community. In this presentation, participants will get an overview of SMU Libraries' engagement and partnerships with the academic community and will showcase initiatives and resources supporting AI literacy. This includes a discussion of insights from the scholarly literature, research findings and critical perspectives to inform teaching and learning practices related to AI. Speakers will share SMU Libraries’ contributions towards awareness and adoption of AI through a portfolio of successful collaborations and initiatives with partners and stakeholders within and …
Smu Opens Representative Office In Vietnam To Boost Knowledge Exchange With Businesses, Academia And Upskill Talent Pipeline Locally, Singapore Management University
Smu Opens Representative Office In Vietnam To Boost Knowledge Exchange With Businesses, Academia And Upskill Talent Pipeline Locally, Singapore Management University
SMU Press Releases and News
Singapore Management University (SMU) announced the establishment of its representative office in Ho Chi Minh City, Vietnam, known as the SMU Overseas Centre Ho Chi Minh City (OCHCMC), taking a significant step in its mission to foster knowledge-sharing and regional collaboration as a gateway university in Asia. This strategic move, which follows the successful launch of SMU's two overseas centres in Jakarta, Indonesia in 2022 and Bangkok, Thailand in 2023 is part of SMU’s Vision 2025 which aims to boost Asian growth by offering a deep understanding of Asia’s economy, polity and society. By utilising the university's resources and offerings, …
Networking Fast And Slow: The Role Of Speed In Tie Formation, Julia Brennecke, Gokhan Ertug, Tom Elfring
Networking Fast And Slow: The Role Of Speed In Tie Formation, Julia Brennecke, Gokhan Ertug, Tom Elfring
Research Collection Lee Kong Chian School Of Business
Growing interest in network dynamics has led to insights about patterns of network change, drivers of tie formation, and the temporal unfolding of the consequences of networks. To this area of inquiry, we introduce networking speed – the time it takes for individuals to form a network tie – as an important but so far largely overlooked aspect. We develop a theory of networking speed that explains how different catalysts enable professionals to introduce variation into the speed with which they form interpersonal network ties. We discuss how such variation in the speed with which ties have been formed influences …
The More The Merrier: How Psychological Standing And Work Group Size Explain Managers' Willingness To Communicate About Unethical Conduct In Their Work Group, Burak Oc, Maryam Kouchaki
The More The Merrier: How Psychological Standing And Work Group Size Explain Managers' Willingness To Communicate About Unethical Conduct In Their Work Group, Burak Oc, Maryam Kouchaki
Research Collection Lee Kong Chian School Of Business
Business ethics research has long examined the dichotomy between remaining silent or reporting ethical misconduct to a third party. Little is known, however, about ethical conversations within a work group after observing misconduct. Specifically, we do not know how many members of their work group individuals choose to communicate with. These conversations could have important implications for creating an ethical workplace. We propose that psychological standing is an important driver of individuals' decisions not to remain silent and to instead raise moral concerns with a greater number of others in their work group. In addition, integrating existing work on structural …
An Integrative Review Of Management Research On Caste: Broadening Our Horizons, Hari Bapuji, Snehanjali Chrispal, Pardeep Singh Attri, Gokhan Ertug, Vivek Soundararajan
An Integrative Review Of Management Research On Caste: Broadening Our Horizons, Hari Bapuji, Snehanjali Chrispal, Pardeep Singh Attri, Gokhan Ertug, Vivek Soundararajan
Research Collection Lee Kong Chian School Of Business
Even though management research on caste is growing, it is not yet on a clear trajectory to realize its vast potential due to varying terminology and framing of caste, the limited incorporation of directly relevant work from proximate disciplines, and the narrow and selective usage of the attributes of caste. To remove these obstacles, we review 259 scholarly works on caste (216 articles and 43 books and research reports) and develop an integrative framework to i) clarify the contemporary manifestations of caste as being a graded hierarchy, an inherited membership, and a set of socially enforced practices, and ii) summarize …
The X-Minute Commute City As A Planning Paradigm: An Evaluation Using Commute And Wellbeing Data From The Singapore Life Panel, Sock Yong Phang, Yeng Cong Wong, Stephen Hoskins
The X-Minute Commute City As A Planning Paradigm: An Evaluation Using Commute And Wellbeing Data From The Singapore Life Panel, Sock Yong Phang, Yeng Cong Wong, Stephen Hoskins
ROSA Journal Articles and Publications
The x-minute city has emerged as a popular concept in transport planning in the past decade. Usually associated with planning for 15-minute neighbourhoods, cities such as Sydney and Singapore have expanded the concept to include setting time targets for commutes. In Singapore, transport planners have committed to long term goals of 20minute neighbourhoods and a 45-minute city (for commuting trips) by 2040. This paper uses a dataset for 2,535 Singapore residents aged 55 to 75 years to investigate three related questions important for evaluating the 45-minute city goal: the predictors of long commutes; the relationship between commute time and life …
Efficiency And Sustainability Of Bond Market: Evidence From Aftermarket Trading Of Us Corporate Bond Offerings, Lisa (Zongfei) Yang, Choo Yong, Jeremy Goh
Efficiency And Sustainability Of Bond Market: Evidence From Aftermarket Trading Of Us Corporate Bond Offerings, Lisa (Zongfei) Yang, Choo Yong, Jeremy Goh
Research Collection Lee Kong Chian School Of Business
We find that for bond offerings that are non-self-marketed, there is a significantly larger proportion of institutional-sized sell trades than buy. In stark contrast, for self-marketed offerings by underwriters, immediate post-offer trading is characterized by a larger proportion of institutional-sized buy trades than sell. We also find evidence suggesting that retail investors, who are initially shut out of the offering deals, buy bonds in the secondary market at a higher price. Our evidence suggests that certain institutional investors receiving allocations of non-self-marketed offerings flip them for a quick profit. The systematic disparity in aftermarket trading immediately following self-marketed versus non-self-marketed …
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 …
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.
The Chemistry Between Us: Illuminating Complementarity Patterns In Interpersonal Role Play Assessment Via Moment-To-Moment Analyses, Christoph N. Herde, Filip Lievens
The Chemistry Between Us: Illuminating Complementarity Patterns In Interpersonal Role Play Assessment Via Moment-To-Moment Analyses, Christoph N. Herde, Filip Lievens
Research Collection Lee Kong Chian School Of Business
In assessment and selection, organizations often include interpersonal interactions because they provide insights into candidates’ interpersonal skills. These skills are then typically assessed via one-shot, retrospective assessor ratings. Unfortunately, the assessment of interpersonal skills at such a trait-like level fails to capture the richness of how the interaction unfolds at the behavioral exchange level within a role-play assessment. This study uses the lens of interpersonal complementarity theory to advance our understanding of interpersonal dynamics in role-play assessment and their effects on assessor ratings. Ninety-six MBA students participated in four different flash role-plays as part of diagnosing their strengths and weaknesses. …
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 …
From The Editors: Mobilizing New Sources Of Data: Opportunities And Recommendations, Denis A. Gregoire, Anne L. J. Ter Wal, Laura M. Little, Sekou Bermiss, Reddi Kotha, Marc Gruber
From The Editors: Mobilizing New Sources Of Data: Opportunities And Recommendations, Denis A. Gregoire, Anne L. J. Ter Wal, Laura M. Little, Sekou Bermiss, Reddi Kotha, Marc Gruber
Research Collection Lee Kong Chian School Of Business
In June 2008, the U.S.-based website Glassdoor.com began posting anonymous company reviews and salary data from current and former employees of various organizations. Doing so not only brought to the world information that had hitherto been restricted to private circles, it spontaneously prompted some organizations to alter their workplace practices (Dineen & Allen, 2016; Dube & Zhu, 2021). At the same time, Glassdoor’s very activities gave rise to a completely new source of data for exploring a wealth of management and organizational phenomena (e.g., Bermiss & McDonald, 2018; Rhee, 2024). As this example illustrates, new data sources can not only …
Why Did Retail Liquidity Programs Fail?, Thomas Ernst, Chester Spatt, Jian Sun
Why Did Retail Liquidity Programs Fail?, Thomas Ernst, Chester Spatt, Jian Sun
Research Collection Lee Kong Chian School Of Business
Five U.S. exchanges have Retail Liquidity Programs, which operate a limit order book only accessible to market orders from retail traders. In theory, this allows competition for segmented retail order flow. In practice, volumes executed in RLPs have been very low, and obtain prices inferior to those offered by off-exchange wholesalers. We trace this failure to three distinct issues: (1) cream-skimming by wholesalers, so that ``retail'' trades in RLPs carry high adverse selection risk, (2) an inability by RLPs to display quotes without pre-trade transparency of available prices, and (3) a lack of trade-through protection, with wholesalers executing trades at …
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 …
Continual Normalization: Rethinking Batch Normalization For Online Continual Learning, Quang Pham, Chenghao Liu, Steven Hoi
Continual Normalization: Rethinking Batch Normalization For Online Continual Learning, Quang Pham, Chenghao Liu, Steven Hoi
Research Collection School Of Computing and Information Systems
Existing continual learning methods use Batch Normalization (BN) to facilitate training and improve generalization across tasks. However, the non-i.i.d and non-stationary nature of continual learning data, especially in the online setting, amplify the discrepancy between training and testing in BN and hinder the performance of older tasks. In this work, we study the cross-task normalization effect of BN in online continual learning where BN normalizes the testing data using moments biased towards the current task, resulting in higher catastrophic forgetting. This limitation motivates us to propose a simple yet effective method that we call Continual Normalization (CN) to facilitate training …
Environmental, Social, And Governance (Esg) And Artificial Intelligence In Finance: State-Of-The-Art And Research Takeaways, Tristan Lim
Research Collection School Of Computing and Information Systems
The rapidly growing research landscape in finance, encompassing environmental, social, and governance (ESG) topics and associated Artificial Intelligence (AI) applications, presents challenges for both new researchers and seasoned practitioners. This study aims to systematically map the research area, identify knowledge gaps, and examine potential research areas for researchers and practitioners. The investigation focuses on three primary research questions: the main research themes concerning ESG and AI in finance, the evolution of research intensity and interest in these areas, and the application and evolution of AI techniques specifically in research studies within the ESG and AI in finance domain. Eight archetypical …
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 …
Flgan: Gan-Based Unbiased Federated Learning Under Non-Iid Settings, Zhuoran Ma, Yang Liu, Yinbin Miao, Guowen Xu, Ximeng Liu, Jianfeng Ma, Robert H. Deng
Flgan: Gan-Based Unbiased Federated Learning Under Non-Iid Settings, Zhuoran Ma, Yang Liu, Yinbin Miao, Guowen Xu, Ximeng Liu, Jianfeng Ma, Robert H. Deng
Research Collection School Of Computing and Information Systems
Federated Learning (FL) suffers from low convergence and significant accuracy loss due to local biases caused by non-Independent and Identically Distributed (non-IID) data. To enhance the non-IID FL performance, a straightforward idea is to leverage the Generative Adversarial Network (GAN) to mitigate local biases using synthesized samples. Unfortunately, existing GAN-based solutions have inherent limitations, which do not support non-IID data and even compromise user privacy. To tackle the above issues, we propose a GAN-based unbiased FL scheme, called FlGan, to mitigate local biases using synthesized samples generated by GAN while preserving user-level privacy in the FL setting. Specifically, FlGan first …
Unleashing The Power Of Clippy In Real-World Rust Projects, Chunmiao Li, Yijun Yu, Haitao Wu, Luca Carlig, Shijie Nie, Lingxiao Jiang
Unleashing The Power Of Clippy In Real-World Rust Projects, Chunmiao Li, Yijun Yu, Haitao Wu, Luca Carlig, Shijie Nie, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
The error messages generated by the Rust compiler (rustc) are useful for developers to identify and diagnose suspicious code segments. Complementing the compiler, linters can also play an important role in promoting the adherence to certain coding style conventions and best practices. Prominent linters utilized in the Rust ecosystem include Clippy [1] and Rustfmt [2]. Among them, the Rust community particularly emphasizes on the importance of heeding the warnings provided by Clippy to mitigate common errors and promote the adoption of idiomatic conventions. Clippy provides a set of more than 600 lints in addition to the built-in rustc lints. These …
My Github Sponsors Profile Is Live!": Investigating The Impact Of Twitter/X Mentions On Github Sponsors, Youmei Fan, Tao Xiao, Hideaki Hata, Christoph Treude, Kenichi Matsumoto
My Github Sponsors Profile Is Live!": Investigating The Impact Of Twitter/X Mentions On Github Sponsors, Youmei Fan, Tao Xiao, Hideaki Hata, Christoph Treude, Kenichi Matsumoto
Research Collection School Of Computing and Information Systems
GitHub Sponsors was launched in 2019, enabling donations to opensource software developers to provide financial support, as per GitHub’s slogan: “Invest in the projects you depend on”. However, a 2022 study on GitHub Sponsors found that only two-fifths of developers who were seeking sponsorship received a donation. The study found that, other than internal actions (such as offering perks to sponsors), developers had advertised their GitHub Sponsors profiles on social media, such as Twitter (also known as X). Therefore, in this work, we investigate the impact of tweets that contain links to GitHub Sponsors profiles on sponsorship, as well as …
Intrafirm Knowledge Sharing In The Investment Research Industry, Artur Hugon, An-Ping Lin, Stanimir Markov
Intrafirm Knowledge Sharing In The Investment Research Industry, Artur Hugon, An-Ping Lin, Stanimir Markov
Research Collection School Of Accountancy
We study interdepartment knowledge sharing in an investment research setting where the benefits are potentially significant for the brokerage and the capital market, but so are the frictions impeding it. Using hand-collected data on equity analyst access to in-house debt research expertise, we find significant benefits to equity analysts in the form of improved ability to forecast cash flows and to anticipate credit rating downgrades. Moreover, we find evidence that access to management and research expertise underlie in-house debt analysts' capacity to generate information beneficial to equity analysts. Finally, these benefits exist only in the presence of a collaborative brokerage …
Concretely Mapped Symbolic Memory Locations For Memory Error Detection, Haoxin Tu, Lingxiao Jiang, Jiaqi Hong, Xuhua Ding, He Jiang
Concretely Mapped Symbolic Memory Locations For Memory Error Detection, Haoxin Tu, Lingxiao Jiang, Jiaqi Hong, Xuhua Ding, He Jiang
Research Collection School Of Computing and Information Systems
Memory allocation is a fundamental operation for managing memory objects in many programming languages. Misusing allocated memory objects (e.g., buffer overflow and use-after-free) can lead to catastrophic consequences. Symbolic execution-based approaches are often used to detect such memory errors, leveraging their capabilities in automatic path exploration and test case generation. However, existing symbolic execution engines face significant limitations in modeling dynamic memory layouts. These engines either represent memory object locations as concrete addresses, limiting analyses to specific address layouts and missing errors that occur at special addresses, or represent locations as simple symbolic variables without sufficient constraints, resulting in memory …