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Effect Of Amended Claim On A Warrant Of Arrest In An Admiralty Action In Rem, Ming En Tor Sep 2023

Effect Of Amended Claim On A Warrant Of Arrest In An Admiralty Action In Rem, Ming En Tor

Research Collection Yong Pung How School Of Law

Suppose I have filed my statement of claim endorsing the writ in rem, and the Registrar has issued a warrant of arrest reflecting this claim. I then proceed to execute a warrant of arrest to arrest a vessel. Now, suppose, however, I later discover that the original claim stated in the warrant of arrest does not exist. I then substitute the original claim with a completely different claim altogether. Can the warrant of arrest be upheld based on the amended claim and/or cause of action, even if it was not so pleaded initially when the action in rem commenced? This …

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Sharing And Caring: Creating A Culture Of Constructive Criticism In Computational Legal Studies, Corinna Coupette, Dirk Hartung Sep 2023

Sharing And Caring: Creating A Culture Of Constructive Criticism In Computational Legal Studies, Corinna Coupette, Dirk Hartung

Research Collection Yong Pung How School Of Law

We introduce seven foundational principles for creating a culture of constructive criticism in computational legal studies. Beginning by challenging the current perception of papers as the primary scholarly output, we call for a more comprehensive interpretation of publications. We then suggest to make these publications computationally reproducible, releasing all of the data and all of the code all of the time, on time, and in the most functioning form feasible. Once all materials are made available by default, we invite constructive criticism in all phases of the publication life cycle. We posit that our proposals will help form our field, …

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Does Abstract Thinking Facilitate Information Processing? Evidence From Financial Analysts, Frank Weikai Li, Rong Wang, Yang Yu, Gloria Yang Yu Sep 2023

Does Abstract Thinking Facilitate Information Processing? Evidence From Financial Analysts, Frank Weikai Li, Rong Wang, Yang Yu, Gloria Yang Yu

Research Collection Lee Kong Chian School Of Business

We study whether abstract thinking – an essential cognitive trait established by psychological and neuroscientific studies – facilitates analysts’ information processing. Exploiting analysts’ questions during earnings calls, we construct an Abstract Thinking Index (ATI) that measures their tendency to involve abstract words, logical reasoning, broader topics, and future outlooks. We find that abstract thinking improves analysts’ forecast accuracy and recommendation informativeness. Consistent with abstract thinking featuring identifying central characteristics and comprehending intangible things, ATI has stronger effects for firms with fundamentals co-moving more with peers and less tangible information. Additional analyses suggest that ATI captures analysts’ cognitive traits rather than …

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Dynamic Scheduling With Uncertain Job Types, Zuo-Jun Max Shen, Jingui Xie, Zhichao Zheng, Han Zhou Sep 2023

Dynamic Scheduling With Uncertain Job Types, Zuo-Jun Max Shen, Jingui Xie, Zhichao Zheng, Han Zhou

Research Collection Lee Kong Chian School Of Business

Uncertain job types can arise as a result of predictive or diagnostic inaccuracy in healthcare or repair service systems and unknown preferences in matching service systems. In this paper, we study systems with multiple types of jobs, in which type information is imperfect and will be updated dynamically. Each job has a prior probability of belonging to a certain type which may be predicted by data, models, or experts. A job can only be processed by the right machine, and a job assigned to the wrong machine must be rescheduled. More information is learned from the mismatch, and job type …

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Revisiting The Design Of Selection Systems In Light Of New Findings Regarding The Validity Of Widely Used Predictors, Paul R. Sackett, Charlene Zhang, Christopher M. Berry, Filip Lievens Sep 2023

Revisiting The Design Of Selection Systems In Light Of New Findings Regarding The Validity Of Widely Used Predictors, Paul R. Sackett, Charlene Zhang, Christopher M. Berry, Filip Lievens

Research Collection Lee Kong Chian School Of Business

Sackett et al. (2022) identified previously unnoticed flaws in the way range restriction corrections have been applied in prior meta-analyses of personnel selection tools. They offered revised estimates of operational validity, which are often quite different from the prior estimates. The present paper attempts to draw out the applied implications of that work. We aim to a) present a conceptual overview of the critique of prior approaches to correction, b) outline the implications of this new perspective for the relative validity of different predictors and for the tradeoff between validity and diversity in selection system design, c) highlight the need …

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The Information In Asset Fire Sales, Sheng Huang, Matthew C. Ringgenberg, Zhe Zhang Sep 2023

The Information In Asset Fire Sales, Sheng Huang, Matthew C. Ringgenberg, Zhe Zhang

Research Collection Lee Kong Chian School Of Business

Asset prices remain depressed for years following mutual fund fire sales, but little is known about the causes of these price drops. We show that asymmetric information generates price pressure during fire sales. We separate trades into expected trades, which assume fund managers scale down their portfolio, and discretionary trades. We find that discretionary trades contain fundamental information, whereas expected trades do not. Moreover, other traders cannot distinguish between discretionary and expected trades. Our findings help explain the magnitude and persistence of fire sale discounts: fund managers choose which assets to sell, and information asymmetries make it difficult for arbitrageurs …

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Public Sentiments And The Influence Of Information-Seeking Preferences On Knowledge, Attitudes, Death Conversation And Receptiveness Towards Palliative Care: Results From A Nationwide Survey In Singapore, Su Lin Yeo, Raymond Han Lip Ng, Tan Ying Peh, May O. Lwin, Poh Heng Chong, Patricia Soek Hui Neo, Jamie Xuelian Zhou, Angel Lee Sep 2023

Public Sentiments And The Influence Of Information-Seeking Preferences On Knowledge, Attitudes, Death Conversation And Receptiveness Towards Palliative Care: Results From A Nationwide Survey In Singapore, Su Lin Yeo, Raymond Han Lip Ng, Tan Ying Peh, May O. Lwin, Poh Heng Chong, Patricia Soek Hui Neo, Jamie Xuelian Zhou, Angel Lee

Research Collection Lee Kong Chian School Of Business

Background: Low awareness about palliative care among the global public and healthcare communities has been frequently cited as a persistent barrier to palliative care acceptance. Given that knowledge shapes attitudes and encourages receptiveness, it is critical to examine factors that influence the motivation to increase knowledge. Health information-seeking from individuals and media has been identified as a key factor, as the process of accessing and interpreting information to enhance knowledge has been shown to positively impact health behaviours. Objective: Our study aimed to uncover public sentiments toward palliative care in Singapore. A conceptual framework was additionally developed to investigate the …

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Data Is The New Gold: A Singapore Perspective On The Duty Of Care Concerning A Dataset’S Role In Contributing To Bias And Ai Hallucinations, Daniel Seah Aug 2023

Data Is The New Gold: A Singapore Perspective On The Duty Of Care Concerning A Dataset’S Role In Contributing To Bias And Ai Hallucinations, Daniel Seah

Research Collection College of Integrative Studies

Amidst the trends and advances in Artificial Intelligence (AI) techniques, the dataset’s key role in creating AI harms is a constant. Yet the literature’s attention is typically focussed on the machinelearning’s role, from which the dataset’s role is examined usually in terms of its potential for bias. Datasets also contribute to AI hallucinations. Again, the literature focuses on the composite roles of datasets and AI models in hallucinations, in isolation from a dataset’s contributory role in creating bias. Therefore, the overlapping and distinctive roles of datasets, as a dual contributor, are understudied in the literature. Through the legal concept of …

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Lean Manufacturing Approach To Increase Packaging Efficiency, Lina Gozali, Irsandy Kurniawan, Aldo Salim, Iveline Anne Marie, Benny Tjahjono, Yun Chia Liang, Aldy Gunawan, Nnovia Hardjo Sie, Yuliani Suseno Aug 2023

Lean Manufacturing Approach To Increase Packaging Efficiency, Lina Gozali, Irsandy Kurniawan, Aldo Salim, Iveline Anne Marie, Benny Tjahjono, Yun Chia Liang, Aldy Gunawan, Nnovia Hardjo Sie, Yuliani Suseno

Research Collection School Of Computing and Information Systems

The company upon which this paper is based engages in flexible packaging production, especially pharmaceutical products with guaranteed quality, trusted by consumers. Its production process includes printing, laminating, and assembling processes. Production activities are done manually and automatically using machines, so various types of waste are often found in these processes, making the level of plant efficiency nonoptimal. This study aims to identify wastes occurring in the production process, especially the production of pollycelonium with three colour variants as the highest demand product, by applying lean manufacturing concepts. The Current Value Stream Mapping (CVSM) used to map the production process …

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Knowledge Representation For Conceptual, Motivational, And Affective Processes In Natural Language Communication, Seng Beng Ho, Zhaoxia Wang, Boon-Kiat Quek, Erik Cambria Aug 2023

Knowledge Representation For Conceptual, Motivational, And Affective Processes In Natural Language Communication, Seng Beng Ho, Zhaoxia Wang, Boon-Kiat Quek, Erik Cambria

Research Collection School Of Computing and Information Systems

Natural language communication is an intricate and complex process. The speaker usually begins with an intention and motivation of what is to be communicated, and what outcomes are expected from the communication, while taking into consideration the listener’s mental model to concoct an appropriate sentence. Likewise, the listener has to interpret the speaker’s message, and respond accordingly, also with the speaker’s mental model in mind. Doing this successfully entails the appropriate representation of the conceptual, motivational, and affective processes that underlie language generation and understanding. Whereas big-data approaches in language processing (such as chatbots and machine translation) have performed well, …

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The United States Vs. China: The Quest For Global Economic Leadership By C. Fred Bergsten, Henry S. Gao Aug 2023

The United States Vs. China: The Quest For Global Economic Leadership By C. Fred Bergsten, Henry S. Gao

Research Collection Yong Pung How School Of Law

This book is one of the latest additions to the voluminous literature exploring two of the biggest geopolitical trends in our age: the rise of China and its changing relationship with the United States. However, two features make this book unique. First is its scope: it is one of a few that specifically focus on the systemic implications to the global economic order arising from the tensions between the two largest economies in the world. Second, its author, C. Fred Bergsten, is one of the most qualified in the world to write on the topic. Bergsten not only is one …

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Decoding The Underlying Meaning Of Multimodal Hateful Memes, Ming Shan Hee, Wen Haw Chong, Roy Ka-Wei Lee Aug 2023

Decoding The Underlying Meaning Of Multimodal Hateful Memes, Ming Shan Hee, Wen Haw Chong, Roy Ka-Wei Lee

Research Collection School Of Computing and Information Systems

Recent studies have proposed models that yielded promising performance for the hateful meme classification task. Nevertheless, these proposed models do not generate interpretable explanations that uncover the underlying meaning and support the classification output. A major reason for the lack of explainable hateful meme methods is the absence of a hateful meme dataset that contains ground truth explanations for benchmarking or training. Intuitively, having such explanations can educate and assist content moderators in interpreting and removing flagged hateful memes. This paper address this research gap by introducing Hateful meme with Reasons Dataset (HatReD), which is a new multimodal hateful meme …

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Decompiling X86 Deep Neural Network Executables, Zhibo Liu, Yuanyuan Yuan, Shuai Wang, Xiaofei Xie, Lei Ma Aug 2023

Decompiling X86 Deep Neural Network Executables, Zhibo Liu, Yuanyuan Yuan, Shuai Wang, Xiaofei Xie, Lei Ma

Research Collection School Of Computing and Information Systems

Due to their widespread use on heterogeneous hardware devices, deep learning (DL) models are compiled into executables by DL compilers to fully leverage low-level hardware primitives. This approach allows DL computations to be undertaken at low cost across a variety of computing platforms, including CPUs, GPUs, and various hardware accelerators. We present BTD (Bin to DNN), a decompiler for deep neural network (DNN) executables. BTD takes DNN executables and outputs full model specifications, including types of DNN operators, network topology, dimensions, and parameters that are (nearly) identical to those of the input models. BTD delivers a practical framework to process …

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Correcting For Range Restriction In Meta-Analysis: A Reply To Oh Et Al. (2023), Paul R. Sackett, Christopher M. Berry, Filip Lievens, Charlene Zhang Aug 2023

Correcting For Range Restriction In Meta-Analysis: A Reply To Oh Et Al. (2023), Paul R. Sackett, Christopher M. Berry, Filip Lievens, Charlene Zhang

Research Collection Lee Kong Chian School Of Business

Oh et al. (2023) question a number of choices made in our article (Sackett et al., 2022); here we respond. They interpret our article as recommending against correcting for range restriction in general in concurrent validation studies; yet, we emphasize that we endorse correction when one has access to the information needed to do so. Our focus was on making range restriction corrections when conducting meta-analyses, where it is common for primary studies to be silent as to the prior basis for selection of the employees later participating in the concurrent validation study. As such, the applicant pool information needed …

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Effects Of A Mindfulness-Based Leadership Training On Leadership Behaviors And Effectiveness, Nina Tan, Eva Katharina Peters, Jochen Reb Aug 2023

Effects Of A Mindfulness-Based Leadership Training On Leadership Behaviors And Effectiveness, Nina Tan, Eva Katharina Peters, Jochen Reb

Research Collection Lee Kong Chian School Of Business

Objectives: Organizations increasingly integrate mindfulness elements into their leadership development. However, there is limited evidence supporting the efficacy of mindfulness-based leadership training (MBLT) due to a scarcity of intervention studies. Theoretically, little is known about mediating mechanisms through which MBLT might affect leadership effectiveness. Thus, this research examined whether MBLT can improve leadership effectiveness and whether leadership behaviors mediated this effect.MethodsWe conducted a quasi-experimental study conducted in a real-world setting with an active control condition. Sixty leaders from various industries participated in either a 2-day intensive MBLT workshop followed by three individual coaching sessions over 3 months, or a presentation …

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Numgpt: Improving Numeracy Ability Of Generative Pre-Trained Models, Zhihua Jin, Xin Jiang, Xiangbo Wang, Qun Liu, Yong Wang, Xiaozhe Ren, Huamin Qu Aug 2023

Numgpt: Improving Numeracy Ability Of Generative Pre-Trained Models, Zhihua Jin, Xin Jiang, Xiangbo Wang, Qun Liu, Yong Wang, Xiaozhe Ren, Huamin Qu

Research Collection School Of Computing and Information Systems

Existing generative pre-trained language models (e.g., GPT) focus on modeling the language structure and semantics of general texts. However, those models do not consider the numerical properties of numbers and cannot perform robustly on numerical reasoning tasks (e.g., math word problems and measurement estimation). In this paper, we propose NumGPT, a generative pre-trained model that explicitly models the numerical properties of numbers in texts. Specifically, it leverages a prototype-based numeral embedding to encode the mantissa of the number and an individual embedding to encode the exponent of the number. A numeral-aware loss function is designed to integrate numerals into the …

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Evolve Path Tracer: Early Detection Of Malicious Addresses In Cryptocurrency, Ling Cheng, Feida Zhu, Yong Wang, Ruicheng Liang, Huiwen Liu Aug 2023

Evolve Path Tracer: Early Detection Of Malicious Addresses In Cryptocurrency, Ling Cheng, Feida Zhu, Yong Wang, Ruicheng Liang, Huiwen Liu

Research Collection School Of Computing and Information Systems

With the boom of cryptocurrency and its concomitant financial risk concerns, detecting fraudulent behaviors and associated malicious addresses has been drawing significant research effort. Most existing studies, however, rely on the full history features or full-fledged address transaction networks, both of which are unavailable in the problem of early malicious address detection and therefore failing them for the task. To detect fraudulent behaviors of malicious addresses in the early stage, we present Evolve Path Tracer, which consists of Evolve Path Encoder LSTM, Evolve Path Graph GCN, and Hierarchical Survival Predictor. Specifically, in addition to the general address features, we propose …

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Proxy Hunting: Understanding And Characterizing Proxy-Based Upgradeable Smart Contracts In Blockchains, William E Iii Bodell, Sajad Meisami, Yue Duan Aug 2023

Proxy Hunting: Understanding And Characterizing Proxy-Based Upgradeable Smart Contracts In Blockchains, William E Iii Bodell, Sajad Meisami, Yue Duan

Research Collection School Of Computing and Information Systems

Upgradeable smart contracts (USCs) have become a key trend in smart contract development, bringing flexibility to otherwise immutable code. However, they also introduce security concerns. On the one hand, they require extensive security knowledge to implement in a secure fashion. On the other hand, they provide new strategic weapons for malicious activities. Thus, it is crucial to fully understand them, especially their security implications in the real-world. To this end, we conduct a large-scale study to systematically reveal the status quo of USCs in the wild. To achieve our goal, we develop a complete USC taxonomy to comprehensively characterize the …

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Transferable Curricula Through Difficulty Conditioned Generators, Sidney Tio, Pradeep Varakantham Aug 2023

Transferable Curricula Through Difficulty Conditioned Generators, Sidney Tio, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Advancements in reinforcement learning (RL) have demonstrated superhuman performance in complex tasks such as Starcraft, Go, Chess etc. However, knowledge transfer from Artificial "Experts" to humans remain a significant challenge. A promising avenue for such transfer would be the use of curricula. Recent methods in curricula generation focuses on training RL agents efficiently, yet such methods rely on surrogate measures to track student progress, and are not suited for training robots in the real world (or more ambitiously humans). In this paper, we introduce a method named Parameterized Environment Response Model (PERM) that shows promising results in training RL agents …

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Ai For Connectivism Learning: Undergraduate Students’ Experiences Of Chatgpt In Advanced Programming Courses, Swapna Gottipati, Kyong Jin Shim, Venky Shankararaman Aug 2023

Ai For Connectivism Learning: Undergraduate Students’ Experiences Of Chatgpt In Advanced Programming Courses, Swapna Gottipati, Kyong Jin Shim, Venky Shankararaman

Research Collection School Of Computing and Information Systems

Advanced programming skills are required for computing courses on merging topics, and students often struggle to develop these skills to solve complex problems. To address this challenge, faculty members provide additional lectures, practice sessions, and educational technology tools. This paper discusses the challenges faced by computer science students in developing advanced programming skills and explores the use of AI chatbots, specifically ChatGPT, as a support tool for learning. We study the engagement and effectiveness of ChatGPT in helping students learn advanced programming skills using two engagement learning frameworks (CIE and MELT) for evaluation. The study involves designing a computing lab …

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Crowdfl: Privacy-Preserving Mobile Crowdsensing System Via Federated Learning, Bowen Zhao, Ximeng Liu, Wei-Neng Chen, Robert H. Deng Aug 2023

Crowdfl: Privacy-Preserving Mobile Crowdsensing System Via Federated Learning, Bowen Zhao, Ximeng Liu, Wei-Neng Chen, Robert H. Deng

Research Collection School Of Computing and Information Systems

As an emerging sensing data collection paradigm, mobile crowdsensing (MCS) enjoys good scalability and low deployment cost but raises privacy concerns. In this paper, we propose a privacy-preserving MCS system called CROWDFL by seamlessly integrating federated learning (FL) into MCS. At a high level, in order to protect participants' privacy and fully explore participants' computing power, participants in CROWDFL locally process sensing data via FL paradigm and only upload encrypted training models to the server. To this end, we design a secure aggregation algorithm (SecAgg) through the threshold Paillier cryptosystem to aggregate training models in an encrypted form. Also, to …

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Fintech Data Infrastructure For Esg Disclosure Compliance, Randall E. Duran, Peter Tierney Aug 2023

Fintech Data Infrastructure For Esg Disclosure Compliance, Randall E. Duran, Peter Tierney

Research Collection School Of Computing and Information Systems

Regulations related to the disclosure of environmental, governance, and social (ESG) factors are evolving rapidly and are a major concern for financial compliance worldwide. Information technology has the potential to reduce the effort and cost of ESG disclosure compliance. However, comprehensive and accurate ESG data are necessary for disclosures. Currently, the availability and quality of underlying data for ESG disclosures vary widely and are often deficient. The process involved with obtaining ESG data is also often inefficient and prone to error. This paper compares the models used and the evolution of Fintech data infrastructure developed to support financial services with …

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Context-Aware Event Forecasting Via Graph Disentanglement, Yunshan Ma, Chenchen Ye, Zijian Wu, Xiang Wang, Yixin Cao, Tat-Seng Chua Aug 2023

Context-Aware Event Forecasting Via Graph Disentanglement, Yunshan Ma, Chenchen Ye, Zijian Wu, Xiang Wang, Yixin Cao, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Event forecasting has been a demanding and challenging task throughout the entire human history. It plays a pivotal role in crisis alarming and disaster prevention in various aspects of the whole society. The task of event forecasting aims to model the relational and temporal patterns based on historical events and makes forecasting to what will happen in the future. Most existing studies on event forecasting formulate it as a problem of link prediction on temporal event graphs. However, such pure structured formulation suffers from two main limitations: 1) most events fall into general and high-level types in the event ontology, …

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Sparsity Brings Vulnerabilities: Exploring New Metrics In Backdoor Attacks, Jianwen Tian, Kefan Qiu, Debin Gao, Zhi Wang, Xiaohui Kuang, Gang Zhao Aug 2023

Sparsity Brings Vulnerabilities: Exploring New Metrics In Backdoor Attacks, Jianwen Tian, Kefan Qiu, Debin Gao, Zhi Wang, Xiaohui Kuang, Gang Zhao

Research Collection School Of Computing and Information Systems

Nowadays, using AI-based detectors to keep pace with the fast iterating of malware has attracted a great attention. However, most AI-based malware detectors use features with vast sparse subspaces to characterize applications, which brings significant vulnerabilities to the model. To exploit this sparsityrelated vulnerability, we propose a clean-label backdoor attack consisting of a dissimilarity metric-based candidate selection and a variation ratio-based trigger construction. The proposed backdoor is verified on different datasets, including a Windows PE dataset, an Android dataset with numerical and boolean feature values, and a PDF dataset. The experimental results show that the attack can slash the accuracy …

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Single-View View Synthesis With Self-Rectified Pseudo-Stereo, Yang Zhou, Hanjie Wu, Wenxi Liu, Zheng Xiong, Jing Qin, Shengfeng He Aug 2023

Single-View View Synthesis With Self-Rectified Pseudo-Stereo, Yang Zhou, Hanjie Wu, Wenxi Liu, Zheng Xiong, Jing Qin, Shengfeng He

Research Collection School Of Computing and Information Systems

Synthesizing novel views from a single view image is a highly ill-posed problem. We discover an effective solution to reduce the learning ambiguity by expanding the single-view view synthesis problem to a multi-view setting. Specifically, we leverage the reliable and explicit stereo prior to generate a pseudo-stereo viewpoint, which serves as an auxiliary input to construct the 3D space. In this way, the challenging novel view synthesis process is decoupled into two simpler problems of stereo synthesis and 3D reconstruction. In order to synthesize a structurally correct and detail-preserved stereo image, we propose a self-rectified stereo synthesis to amend erroneous …

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Multi-Granularity Detector For Vulnerability Fixes, Truong Giang Nguyen, Cong, Thanh Le, Hong Jin Kang, Ratnadira Widyasari, Chengran Yang, Zhipeng Zhao, Bowen Xu, Jiayuan Zhou, Xin Xia, Ahmed E. Hassan, David Lo, David Lo Aug 2023

Multi-Granularity Detector For Vulnerability Fixes, Truong Giang Nguyen, Cong, Thanh Le, Hong Jin Kang, Ratnadira Widyasari, Chengran Yang, Zhipeng Zhao, Bowen Xu, Jiayuan Zhou, Xin Xia, Ahmed E. Hassan, David Lo, David Lo

Research Collection School Of Computing and Information Systems

With the increasing reliance on Open Source Software, users are exposed to third-party library vulnerabilities. Software Composition Analysis (SCA) tools have been created to alert users of such vulnerabilities. SCA requires the identification of vulnerability-fixing commits. Prior works have proposed methods that can automatically identify such vulnerability-fixing commits. However, identifying such commits is highly challenging, as only a very small minority of commits are vulnerability fixing. Moreover, code changes can be noisy and difficult to analyze. We observe that noise can occur at different levels of detail, making it challenging to detect vulnerability fixes accurately. To address these challenges and …

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Mastering Stock Markets With Efficient Mixture Of Diversified Trading Experts, Shuo Sun, Xinrun Wang, Wanqi Xue, Xiaoxuan Lou, Bo An Aug 2023

Mastering Stock Markets With Efficient Mixture Of Diversified Trading Experts, Shuo Sun, Xinrun Wang, Wanqi Xue, Xiaoxuan Lou, Bo An

Research Collection School Of Computing and Information Systems

Quantitative stock investment is a fundamental financial task that highly relies on accurate prediction of market status and profitable investment decision making. Despite recent advances in deep learning (DL) have shown stellar performance on capturing trading opportunities in the stochastic stock market, the performance of existing DL methods is unstable with sensitivity to network initialization and hyperparameter selection. One major limitation of existing works is that investment decisions are made based on one individual neural network predictor with high uncertainty, which is inconsistent with the workflow in real-world trading firms. To tackle this limitation, we propose AlphaMix, a novel three-stage …

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A Reply To Commentaries On “Revisiting The Design Of Selection Systems In Light Of New Findings Regarding The Validity Of Widely Used Predictors”, Paul R. Sackett, Christopher M. Berry, Filip Lievens, Charlene Zhang Aug 2023

A Reply To Commentaries On “Revisiting The Design Of Selection Systems In Light Of New Findings Regarding The Validity Of Widely Used Predictors”, Paul R. Sackett, Christopher M. Berry, Filip Lievens, Charlene Zhang

Research Collection Lee Kong Chian School Of Business

No abstract provided.

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Managing The Creative Frontier Of Generative Ai: The Novelty-Usefulness Tradeoff, Anirban. Mukherjee, Hannah H. Chang Jul 2023

Managing The Creative Frontier Of Generative Ai: The Novelty-Usefulness Tradeoff, Anirban. Mukherjee, Hannah H. Chang

Research Collection Lee Kong Chian School Of Business

In this paper, drawing inspiration from the human creativity literature, we explore the optimal balance between novelty and usefulness in generative Artificial Intelligence (AI) systems. We posit that overemphasizing either aspect can lead to limitations such as hallucinations and memorization. Hallucinations, characterized by AI responses containing random inaccuracies or falsehoods, emerge when models prioritize novelty over usefulness. Memorization, where AI models reproduce content from their training data, results from an excessive focus on usefulness, potentially limiting creativity. To address these challenges, we propose a framework that includes domain-specific analysis, data and transfer learning, user preferences and customization, custom evaluation metrics, …

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Purpose In The For-Profit Firm: A Review And Framework For Management Research, Gerard George, Martine R. Haas, Anita M. Mcgahan, Simon J.D. Schillebeeckx, Paul Tracey Jul 2023

Purpose In The For-Profit Firm: A Review And Framework For Management Research, Gerard George, Martine R. Haas, Anita M. Mcgahan, Simon J.D. Schillebeeckx, Paul Tracey

Research Collection Lee Kong Chian School Of Business

Purpose is a concept often used in managerial communities to signal and define a firm’s benevolent and pluralistic approach to its stakeholders beyond its focus on shareholders. While some evidence has linked purpose to positive organizational outcomes such as growth, employee satisfaction, innovation, and superior stock market performance, the definition and application of purpose in management research has been varied and frequently ambiguous. We review literature streams that invoke purpose in the for-profit firm and propose a unifying definition. Next, we develop a framework to study purpose that decouples its framing and formalization within firms from its realization, thus helping …

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