Digital Commons Network^™

Semantic Loss-Guided Data-Efficient Supervised Fine-Tuning For Safe Responses In Llms, Yuxiao Lu, Pradeep Varakantham, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Large Language Models (LLMs) generating unsafe responses to toxic prompts is a significant issue in their applications. While various efforts aim to address this safety concern, previous approaches often demand substantial human data collection or rely on the less dependable option of using another LLM to generate corrective data. In this paper, we aim to take this problem and overcome limitations of requiring significant high-quality human data. Our method requires only a small set of unsafe responses to toxic prompts, easily obtained from the unsafe LLM itself. By employing a semantic cost combined with a negative Earth Mover Distance (EMD) …

Bootstrapping Language Models With Dpo Implicit Rewards, Changyu Chen, Zichen Liu, Chao Du, Tianyu Pang, Qian Liu, Arunesh Sinha, Pradeep Varakantham, Min Lin

Research Collection School Of Computing and Information Systems

Human alignment in large language models (LLMs) is an active area of research. A recent groundbreaking work, direct preference optimization (DPO), has greatly simplified the process from past work in reinforcement learning from human feedback (RLHF) by bypassing the reward learning stage in RLHF. DPO, after training, provides an implicit reward model. In this work, we make a novel observation that this implicit reward model can by itself be used in a bootstrapping fashion to further align the LLM. Our approach is to use the rewards from a current LLM model to construct a preference dataset, which is then used …

Minimum Multi-Service Fleet Size Problem: Shareability Graph And Network Flow Approach, Dingtong Yang, Yubin Liu, Hai Wang, Jinhua Zhao, Hamsa Balakrishnan

Research Collection School Of Computing and Information Systems

On-demand, vehicle-based services—such as ride-hailing, food, grocery, and parcel delivery—have become ubiquitous over the past decade. These services can be categorized into four types (Sun et al., 2023): passenger mobility, goods delivery, information acquisition (e.g., probe vehicle for traffic conditions), and mobile server (e.g., vehicle displaying advertisements). Passenger mobility and goods delivery are typically fulfilled by separate fleets, each dedicated to a single service. However, if various services can be pooled and handled simultaneously by a multi-functional fleet while maintaining service quality, the total number of required vehicles and overall vehicle mileage could be significantly reduced. This exciting potential motivates …

Predictive Modelling For Vessel Traffic Flow: A Comprehensive Survey From Statistics To Ai, Deshan. Chen, Chen. Huang, Tengze. Fan, Hoong Chuin Lau, Xinping. Yan

Research Collection School Of Computing and Information Systems

Recognizing the specific complexities of vessel traffic flow, this comprehensive survey exclusively addresses the predictive modelling in maritime transportation, tracing the evolution from conventional statistical approaches to modern artificial intelligence (AI) techniques. The survey examines a broad range of predictive targets, including vessel volume, trajectories, velocities, destinations and traffic patterns. Through bibliometric analysis utilizing Citespace, the central research themes and technological trends characterizing the vessel traffic flow prediction domain have been identified and discussed. Our analysis indicates a clear trend towards AI-based models, highlighting their increasing dominance in enhancing predictive accuracy and efficiency. Additionally, we highlight persistent challenges, such as …

A Functional Software Reference Architecture For Llm-Integrated Systems, Alessio Bucaioni, Martin Weyssow, Junda He, Yunbo Lyu, David Lo

Research Collection School Of Computing and Information Systems

The integration of large language models into software systems is transforming capabilities such as natural language understanding, decision-making, and autonomous task execution. However, the absence of a commonly accepted software reference architecture hinders systematic reasoning about their design and quality attributes. This gap makes it challenging to address critical concerns like privacy, security, modularity, and interoperability, which are increasingly important as these systems grow in complexity and societal impact. In this paper, we describe our emerging results for a preliminary functional reference architecture as a conceptual framework to address these challenges and guide the design, evaluation, and evolution of large …

Bigcodebench: Benchmarking Code Generation With Diverse Function Calls And Complex Instructions, T.Y. Zhuo, M.C. Vu, J. Chim, ..., David Lo

Research Collection School Of Computing and Information Systems

Task automation has been greatly empowered by the recent advances in Large Language Models (LLMs) via Python code, where the tasks ranging from software engineering development to general-purpose reasoning. While current benchmarks have shown that LLMs can solve tasks using programs like human developers, the majority of their evaluations are limited to short and self-contained algorithmic tasks or standalone function calls. Solving challenging and practical tasks requires the capability of utilizing diverse function calls as tools to efficiently implement functionalities like data analysis and web development. In addition, using multiple tools to solve a task needs compositional reasoning by accurately …

Scuzer: A Scheduling Optimization Fuzzer For Tvm, Xiangxiang Chen, Xingwei Lin, Jingyi Wang, Jun Sun, Jiashui Wang, Wenhai Wang

Research Collection School Of Computing and Information Systems

The concept of Deep Learning (DL) compiler was proposed to deploy DL models more efficiently on diverse hardware through optimization techniques. As one of the most popular DL compilers, TVM incorporates three levels (high-level, schedule, and low-level) of optimizations, which can inadvertently introduce code logic bugs and build failure bugs. Among these optimizations, scheduling optimization is the core component of DL compilers, which ensures the acceleration of models on all devices. However, the existing works only focus on the testing of high-level and low-level optimizations in TVM, fail to take the most important and challenging intermediate scheduling optimization layer into …

The Digitalization Of Insolvency Proceedings, Aurelio Gurrea-Martinez

Research Collection Yong Pung How School Of Law

Despite the international divergences existing in the design of insolvency law, there is a common feature of insolvency proceedings that, to a greater or lesser extent, is somehow universal: insolvency proceedings are generally costly and lengthy processes. For that reason, it is not surprising that a significant body of the literature on insolvency law deals with different mechanisms to make insolvency proceedings more efficient. This article examines how technology can contribute to that goal. To that end, it starts by reviewing how countries are deploying, or can deploy, technology in different aspects and stages of insolvency proceedings and how such …

Nurture Asia-Ready Singaporeans To Tap Growing Opportunities In The Region [Interview With The Straits Times], Sandra Davie, Piyush Gupta

Oral History Collection

In an interview with The Straits Times, as chairman of Singapore Management University, DBS Bank chief executive Piyush Gupta said the university should aim to become the “quintessential Asian university”, emulating DBS, which he had turned into the “quintessential Asian bank” since he took over the helm in 2009.

Social Mobility: What We Haven’T Talked About, Jacinth Tan

Asian Management Insights

More balanced understanding may curb unintended negative outcomes. While social mobility provides opportunities for a better life and societal progress, it can also lead to significant challenges, including burnout from hypercompetitive environments, feelings of isolation due to cultural mismatches, and self-blame stemming from the myth of meritocracy. Strengthening social safety nets and providing supportive environments in educational institutions and workplaces can help mitigate the unintended psychological and social costs of mobility. A nuanced approach to social mobility that acknowledges external systemic and psychological barriers, and fosters inclusivity, is necessary to ensure upward mobility benefits society while lowering the risk of …

Why Ai’S Role In Advancing Sustainability Is Underestimated, Lipika Bhattacharya

CCX Research

AI has quietly, but powerfully, woven itself into the fabric of our everyday lives. Yet, AI's potential impact on creating a more sustainable world is undervalued. The author examined artificial intelligence's (AI) role in advancing sustainability. She outlined how AI can be applied in various domains such as agriculture, water management, industry, urban planning, and biodiversity conservation for transformative effects.

A Contrastive Framework With User, Item And Review Alignment For Recommendation, Viet Hoang Dong, Yuan Fang, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

Learning effective latent representations for users and items is the cornerstone of recommender systems. Traditional approaches rely on user-item interaction data to map users and items into a shared latent space, but the sparsity of interactions often poses challenges. While leveraging user reviews could mitigate this sparsity, existing review-aware recommendation models often exhibit two key limitations. First, they typically rely on reviews as additional features, but reviews are not universal, with many users and items lacking them. Second, such approaches do not integrate reviews into the useritem space, leading to potential divergence or inconsistency among user, item, and review representations. …

Birdie: Natural Language-Driven Table Discovery Using Differentiable Search Index, Yuxiang Guo, Zhonghao Hu, Yuren Mao, Baihua Zheng, Yunjun Gao, Mingwei Zhou

Research Collection School Of Computing and Information Systems

Natural language (NL)-driven table discovery identifies relevant tables from large table repositories based on NL queries. While current deep-learning-based methods using the traditional dense vector search pipeline, i.e., representation-index-search, achieve remarkable accuracy, they face several limitations that impede further performance improvements: (i) the errors accumulated during the table representation and indexing phases affect the subsequent search accuracy; and (ii) insufficient query-table interaction hinders effective semantic alignment, impeding accuracy improvements. In this paper, we propose a novel framework Birdie, using a differentiate search index. It unifies the indexing and search into a single encoder-decoder language model, thus getting rid of error …

Mimic: Ai And Ar-Enhanced Multi-Modal, Immersive, Relative Instruction Comprehension, Dhanuja Wanniarachchi, Archan Misra

Research Collection School Of Computing and Information Systems

We present a multimodal instruction comprehension framework, called MImIC, that utilizes visual sensing (including LIDAR and 2D RGB sensing) & AI spatial reasoning capabilities to support more seamless and immersive interaction between humans and AI-driven situated assistive agents. MImIC's key new capability is to support disambiguation of a wider set of relative spatial references that users naturally employ while issuing spatially-situated instructions. To support enhanced visual grounding via a combination of both fully-qualified and relative attribute references, MImIC uses (a) a fine-tuned transformer-based language translation DNN to accurately convert natural verbal commands into a structured set of machine understandable constraints …

Learning: Human Versus Machine, Sanjay Sarma

Asian Management Insights

Outdated education paradigms must be revamped to reclaim the all-important human quality: agency.

Sanjay Sarma, CEO, President, and Dean of the Asia School of Business, Kuala Lumpur, Malaysia and the Fred Fort Flowers (1941) and Daniel Fort Flowers (1941) Professor in Mechanical Engineering at the Massachusetts Institute of Technology (MIT), shares insights on the artificial intelligence (AI)-agency revolution and how the human brain works.

How Can Foreign Commercial Vehicle Manufacturers Succeed In India?, Debjit Roy, Shubham

Asian Management Insights

Seven steps to achieve market entry based on lessons from recent market exits. New entrants need to tailor their trucks for India's geography, infrastructure, and conditions to improve acceptability and market share. Boost demand by building an export-driven business model in India to counter the threat from inadequate and stagnant domestic demand. Align service offerings with customer expectations to gain greater vehicle acceptability.

The Ethics Of Ai Nudges: How Ai Influences Decision-Making, Seema Chokshi

Asian Management Insights

And why decision-makers should care about it. Artificial intelligence (AI) systems, through mechanisms like nudges and choice architecture, actively, yet often subtly, shape human decision-making in everyday life and professional settings. AI systems can prioritise profit or efficiency at the expense of human agency, fairness, and well-being, highlighting the need to balance AI’s capabilities with ethical considerations. The EU AI Act is a landmark framework designed to curb manipulative AI practices, emphasising the protection of human autonomy and accountability in decision-making.

Mind The Green Skills Gap, Panchali Guha

Asian Management Insights

The need to build tomorrow’s sustainable green economy today. Climate change and the shift towards a net zero economy pose significant risks to jobs globally unless workers are equipped with green skills and competencies. There is already a green skills gap in the labour market that will only widen over time if it is not addressed. Comprehensive and coordinated policies must be developed to define and measure green jobs and skills, enhance educational offerings, and provide support for workers and employers during the transition.

Reimagining Education: Keeping The Human In The Loop, Pradeep Varakantham, Sidney Tio

Asian Management Insights

How educators can work with generative artificial intelligence models to improve learning. Artificial intelligence (AI) helps break the mould of one-size-fits-all education by creating personalised learning paths that adapt to each student’s pace and style. By combining human expertise with AI capabilities, educators can create learning experiences that are both structured and flexible, thus getting the best of both worlds. While promising, AI used in educational contexts must carefully navigate privacy concerns, ensure fairness across all student groups, and support appropriate learning progression.

Understanding Individual Agent Importance In Multi-Agent System Via Counterfactual Reasoning, Jianming Chen, Yawen Wang, Junjie Wang, Xiaofei Xie, Jun Hu, Qing Wang, Fanjiang Xu

Research Collection School Of Computing and Information Systems

Explaining multi-agent systems (MAS) is urgent as these systems become increasingly prevalent in various applications. Previous work has provided explanations for the actions or states of agents, yet falls short in understanding the black-boxed agent's importance within a MAS and the overall team strategy. To bridge this gap, we propose EMAI, a novel agent-level explanation approach that evaluates the individual agent's importance. Inspired by counterfactual reasoning, a larger change in reward caused by the randomized action of agent indicates its higher importance. We model it as a MARL problem to capture interactions across agents. Utilizing counterfactual reasoning, EMAI learns the …

Sticky Information Technology Investment: Theory And Empirical Evidence, Peng Liang, Hasan Cavusoglu, Nan Hu

Research Collection School Of Computing and Information Systems

This article provides a new way of thinking about managerial discretion in information technology (IT) investment decisions. We delve into the existence, antecedents, and consequences of sticky IT investment behavior, an understudied managerial deliberate resource commitment decision in response to changes in sales. Guided by downsizing theory, we initially theorize and find that IT investments exhibit stickiness: IT investments move downward less for sales decreases than they move upward for equivalent increases. Then drawing upon agency theory, adjustment costs theory, and managerial expectations theory—which influence managers’ motivation for downsizing—we predict and demonstrate that managers’ empire-building incentives, their avoidance of adjustment …

Understanding The Oss Communities Of Deep Learning Frameworks: A Comparative Case Study Of Pytorch And Tensorflow, Yunqi Chen, Zhiyuan Wan, Yifei Zhuang, Ning Liu, David Lo, Xiaohu Yang

Research Collection School Of Computing and Information Systems

Over the past two decades, deep learning has received tremendous success in developing software systems across various domains. Deep learning frameworks have been proposed to facilitate the development of such software systems, among which, PyTorch and TensorFlow stand out as notable examples. Considerable attention focuses on exploring software engineering practices and addressing diverse technical aspects in developing and deploying deep learning frameworks and software systems. Despite these efforts, little is known about the open source software communities involved in the development of deep learning frameworks. In this article, we perform a comparative investigation into the open source software communities of …

Deepvmunprotect: Neural Network-Based Recovery Of Vm‑Protected Android Apps For Semantics‑Aware Malware Detection, Xin Zhao, Mu Zhang, Xiaopeng Ke, Yu Pan, Yue Duan, Sheng Zhong, Fengyuan Xu

Research Collection School Of Computing and Information Systems

The emerging virtual machine-based Android packers render existing unpacking techniques ineffective. The state-of-the-art unpacker falls short because it relies on unreliable heuristics and manually crafted semantic models. Hence, it cannot precisely recover app semantics necessary for malware detection. In this paper, we propose DeepVMUnProtect, a deep learning-based approach to automatically and accurately capture the semantics of VM-packed code, so as to facilitate semantic-based Android malware classification. Experiments have shown that DeepVMUnProtect outperforms the state-of-the-art tool on recovering opcode semantics in Qihoo(58.3%), Baidu(47.5%) and NMMP (58.8%) respectively, and can enable semantics-aware malware detection which prior work fails to do.

Research On The Impact Of Factors For Successful Digital Transformation On Performance: A Case Study Of The Clothing Industry, Xiaoyun Qian

Dissertations and Theses Collection (Open Access)

In recent years, enterprises in the clothing industry have experiencedvarying degrees of performance decline, primarily influenced bymacroeconomic cyclical factors and intrinsic industry issues. Firstly, under the influence of macroeconomic cycles, the clothing industry has demonstratedstrong cyclical characteristics. Since 2019, weakened global macroeconomic conditions have negatively impacted both clothing exports and domestic sales, coupled with a slowdown in China's macroeconomic growth, puttingsignificant pressure on the overall growth of the clothing sector. Secondly, the industry faces several internal challenges, including rising labor costs, severe supply-demand mismatches, overcapacity on the production side, and longinventory cycles. Digital transformation has emerged as an important optionfor …

The One Generates All Things: Founder Competencies And Firm Performance In Chinese Semiconductor Enterprises, Aiyang Wang

Dissertations and Theses Collection (Open Access)

The semiconductor industry originated in the United States in the 1940s and serves as the cornerstone of the modern information technology industry. Semiconductors, hailed as the "grain of industry", are of utmost significance to China, a country that builds its foundation on manufacturing. With the escalation of China's industrial upgrading and global competition, a large number of semiconductor enterprises have been established in China in recent years.

Based on the Upper Echelons Theory, this paper commences from the literature on founder research in entrepreneurship studies, and in conjunction with small-sample interviews, proposes the "521" model for observing Chinese semiconductor enterprise …

Competitive Advantage Of Short Food Supply Chains For Organic Vegetables In India: A Multi-Stakeholder, Mixed Method Study Of Farmers, Consumers And Intermediaries, Bhoovarahan Thirumalai Nambakkam

Dissertations and Theses Collection (Open Access)

Competitive advantage of Short Food Supply Chains for organic vegetables in India – a multi-stakeholder, mixed method study of farmers, consumers and intermediaries.

Short food supply chains (SFSC) are characterized by one (or zero) intermediaries (structural proximity), short distance (geographic proximity), trusted relationships (relationship proximity) and alignment of values (values proximity) between consumers and farmers.

This multi-method case study investigates proximity of SFSCs as a driver for increased willingness to pay (WTP) by consumers for organic vegetables in a global south developing country - India. The study analyzed revealed preference (published prices of a conventional chain and SFSCs), stated preference …

Exploring Intelligent Manufacturing: How Artificial Intelligence Affects Productivity And Labor Demand At The Enterprise Level, Jie Gu

Dissertations and Theses Collection (Open Access)

Manufacturing is a cornerstone of national economic health and social stability, yet it faces challenges such as declining profits, rising labor costs, and an aging workforce. In China, the manufacturing sector is undergoing a critical transformation, driven by technological advancements like artificial intelligence (AI) and the push for intelligent manufacturing. This study explores how AI revitalizes the manufacturing sector by enhancing enterprise productivity and reshaping labor demand, with a focus on quality inspection processes. Using a leading bearing factory as a case study, the research employs econometric models, A/B testing, and interviews to quantify AI’s impact on production efficiency, costs, …

Analysis On Factors For The Success Of China's Industrial Parks -- "Crown Model" And Its Empirical Research, Ming Qiu

Dissertations and Theses Collection (Open Access)

Since the reform and opening-up policy, China has systematically promoted the development and construction of economic and technological development zones, high-tech industrial development zones, and various types of industry-focused functional parks by drawing on successful international models and integrating them with China’s context. This has been carried out from the central government to local governments to foster the clustering of regional industries, facilitate industrial upgrading, drive large-scale employment, increase GDP, generate continuous tax revenue, and accelerate urbanization. These efforts have been pivotal in transforming local economies and enhancing China’s competitive advantage in the global market. The author, with 20 years …

The Impact Of Marriage Status On Career Aspiration And Performance, Qiang Yi

Dissertations and Theses Collection (Open Access)

This study explores the impact of marital status on employee workplace behavior and job performance. Specifically, it finds that compared to unmarried employees, married employees demonstrate higher career aspirations and job performance. Further analysis reveals that this effect is primarily driven by the enhancement of family and career commitments brought about by marriage. These increased commitments significantly contribute to the improvement of employees' career aspirations and job performance. Moreover, this study examines the gender differences in the influence of marital status on family and career commitments.

The results show that marriage has a stronger effect on promoting family commitments among …

Profiles And Well-Being Of Older Adult Caregivers In Singapore, Yi Wen Tan, Rachel Wen Yi Ngu, Kenneth Choo, Lydia Ng, Wensi Lim

ROSA Research Briefs

In Singapore, the government espouses a “many helping hands” philosophy towards caregiving, where care for older adults is borne by three pillars: the family, the community, and the state (Mehta & Vasoo, 2000). Of these, the family is regarded as the “first line of support”, rendering family caregivers essential to the care of older adults (Ng et al., 2016). Many of these caregivers are themselves older adults, where the average age of caregivers was found to be 62 years (Tan, 2023). As Singapore’s population continues to age, alongside demographic trends of extended longevity and a shrinking population, many more will …