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Navigation Beyond Wayfinding: Robots Collaborating With Visually Impaired Users For Environmental Interactions, Shaojun Cai, Nuwan Janaka, Ashwin Ram, Janidu Shehan, Yingjia Wan, Kotaro Hara, David Hsu Mar 2026

Navigation Beyond Wayfinding: Robots Collaborating With Visually Impaired Users For Environmental Interactions, Shaojun Cai, Nuwan Janaka, Ashwin Ram, Janidu Shehan, Yingjia Wan, Kotaro Hara, David Hsu

Research Collection School Of Computing and Information Systems

Robotic guidance systems have shown promise in supporting blind and visually impaired (BVI) individuals with wayfinding and obstacle avoidance. However, most existing systems assume a clear path and do not support a critical aspect of navigation—environmental interactions that require manipulating objects to enable movement. These interactions are challenging for a human–robot pair because they demand (i) precise localization and manipulation of interaction targets (e.g., pressing elevator buttons) and (ii) dynamic coordination between the user’s and robot’s movements (e.g., pulling out a chair to sit). We present a collaborative human–robot approach that combines our robotic guide dog’s precise sensing and localization …

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Private Set Intersection: A Systematic Review, Yunbo Yang, Defan Zhu, Jianting Ning, Qi Feng, Xiaoguo Li, Yuejia Cheng, Guomin Yang, Kui Ren Mar 2026

Private Set Intersection: A Systematic Review, Yunbo Yang, Defan Zhu, Jianting Ning, Qi Feng, Xiaoguo Li, Yuejia Cheng, Guomin Yang, Kui Ren

Research Collection School Of Computing and Information Systems

Various services, such as search engines, are increasingly deployed in cloud-based and distributed systems. However, data are typically managed by trusted servers, making user privacy and data security critical concerns. Private set intersection (PSI) is a powerful cryptographic primitive that enables multiple parties to compute the intersection of their datasets without revealing private inputs. It has been extensively studied over the past two decades, leading to significant gains in computational and communication efficiency. Yet, in many real-world scenarios, revealing the raw intersection may still leak sensitive information. To address this, numerous PSI variants have been developed to meet different application …

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Research On The Influence Mechanism Of Digital Transformation On The International Competitiveness Of The Srdi Smes In China, Bo Sun Mar 2026

Research On The Influence Mechanism Of Digital Transformation On The International Competitiveness Of The Srdi Smes In China, Bo Sun

Dissertations and Theses Collection (Open Access)

With the continuous advancement of digital technologies, the digital economy is increasingly becoming the dominant force in the global economic landscape. Against this backdrop, the digital transformation of China's specialized, refined, distinctive, and innovative (SRDI) small and medium-sized enterprises (SMEs) has transcended beyond mere technological upgrades and evolved into a crucial strategy for these enterprises to build core competitiveness. Despite SRDI SMEs' strong willingness to pursue digital transformation, research is still lacking on how digital transformation efforts translate into international competitiveness Additionally, existing studies on the degree of digitalization have focused on large enterprises or general SMEs, leaving an academic …

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Identifying And Mitigating Api Misuse In Large Language Models, Terry Yue Zhuo, Junda He, Jiamou Sun, Zhenchang Xing, David Lo, John Grundy, Xiaoning Du Mar 2026

Identifying And Mitigating Api Misuse In Large Language Models, Terry Yue Zhuo, Junda He, Jiamou Sun, Zhenchang Xing, David Lo, John Grundy, Xiaoning Du

Research Collection School Of Computing and Information Systems

API misuse in code generated by large language models (LLMs) presents a serious and growing challenge in software development. While LLMs demonstrate impressive code generation capabilities, their interactions with complex library APIs are often error-prone, potentially leading to software failures and vulnerabilities. In this paper, we conduct a large-scale study of API misuse patterns in LLM-generated code, analyzing both method selection and parameter usage across Python and Java, using three representative LLMs (StarCoder-7B, Qwen2.5-Coder-7B, and GitHub Copilot). Based on extensive manual annotation of 3,209 method-level and 3,492 parameter-level misuses, we identify and categorize four recurring misuse types by building on …

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Deep Learning Approaches For Anti-Money Laundering On Mobile Transactions: Review, Framework, And Directions, Jiani Fan, Lwin Khin Shar, Ruichen Zhang, Ziyao Liu, Wenzhuo Yang, Dusit Niyato, Kwok-Yan Lam Mar 2026

Deep Learning Approaches For Anti-Money Laundering On Mobile Transactions: Review, Framework, And Directions, Jiani Fan, Lwin Khin Shar, Ruichen Zhang, Ziyao Liu, Wenzhuo Yang, Dusit Niyato, Kwok-Yan Lam

Research Collection School Of Computing and Information Systems

Money laundering is a financial crime that obscures the origin of illicit funds, necessitating the development and enforcement of anti-money laundering (AML) policies by governments and organizations. The proliferation of mobile payment platforms and smart IoT devices has significantly complicated AML investigations. As payment networks become more interconnected, there is an increasing need for efficient real-time detection to process large volumes of transaction data on heterogeneous payment systems by different operators such as digital currencies, cryptocurrencies, and account-based payments. Most of these mobile payment networks are supported by connected devices, many of which are considered loT devices in the FinTech …

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Invert Your Prompt: Editing-Aware Diffusion Inversion, Yangyang Xu, Wenqi Shao, Yong Du, Haiming Zhu, Yang Zhou, Jiayuan Xie, Ping Luo, Shengfeng He Mar 2026

Invert Your Prompt: Editing-Aware Diffusion Inversion, Yangyang Xu, Wenqi Shao, Yong Du, Haiming Zhu, Yang Zhou, Jiayuan Xie, Ping Luo, Shengfeng He

Research Collection School Of Computing and Information Systems

Recent advancements in text-guided diffusion models have enabled powerful image manipulation capabilities. However, balancing reconstruction fidelity and editability for real images remains a significant challenge. In this work, we introduce Editing Inversion (EditInv), a novel framework that inverts and edits real images for specific editing tasks by optimizing specific prompt embeddings within the extended  space. By leveraging distinct embeddings across different U-Net layers and time steps, EditInv seamlessly integrates inversion and editing through reciprocal optimization, ensuring both high fidelity and precise editability. This hierarchical editing mechanism classifies tasks into structure, appearance, and global edits, optimizing only those embeddings that are …

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Exploring Neural Network Structure Code Reuse In The Open-Source Community For Improving Maintenance, Xiaoning Ren, Yuekun Wang, Chongyang Liu, Yueming Wu, Qiang Hu, Lijun Zhang, Yinxing Xue Mar 2026

Exploring Neural Network Structure Code Reuse In The Open-Source Community For Improving Maintenance, Xiaoning Ren, Yuekun Wang, Chongyang Liu, Yueming Wu, Qiang Hu, Lijun Zhang, Yinxing Xue

Research Collection School Of Computing and Information Systems

Neural networks (NNs) have rapidly advanced, demonstrating exceptional performance across various fields, leading to a surge in open-source NN projects. The complexity and rapid growth of these projects pose significant challenges for maintenance within the open-source community. Given that NN architecture code is the core asset of NN projects, understanding its reuse in the open-source community is essential for effective maintenance, such as reducing redundancy and identifying potential intellectual property violations. While prior studies have examined code reuse in open-source projects, they have two key limitations: They do not specifically address NN structure code, and they rely on manually selected …

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Enterprise Digital Transformation: An Analysis Of Value Creation From An Operational Perspective, Weiguo Ling Mar 2026

Enterprise Digital Transformation: An Analysis Of Value Creation From An Operational Perspective, Weiguo Ling

Dissertations and Theses Collection (Open Access)

Digital transformation has become a critical pathway for the manufacturing sector to break through growth bottlenecks and reshape its core competitiveness. However, in practice, a large number of enterprises are trapped in the transformation paradox of a “discrepancy between perceived consensus and actual outcomes”. The core issue lies in the fact that traditional investment evaluation methods struggle to effectively measure the multi-dimensional value created by digitalization. From the perspective of operational management, this study focuses on the mechanisms and evaluation methods of digital value creation in different manufacturing contexts. A four-dimensional Value Evaluation Framework is proposed, comprise of Value Identification, …

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The Impact Of Service Model Innovation Of Woodworking Machinery Equipment Suppliers On Downstream Furniture Industry Enterprises' Competitiveness, Wenquan Jing Mar 2026

The Impact Of Service Model Innovation Of Woodworking Machinery Equipment Suppliers On Downstream Furniture Industry Enterprises' Competitiveness, Wenquan Jing

Dissertations and Theses Collection (Open Access)

This study examines the impact of service model innovation by woodworking machinery equipment suppliers on the competitiveness of downstream furniture enterprises, focusing on evolving competitive dynamics in equipment manufacturing within the context of service-oriented manufacturing and digital transformation. In the digital economy era, industrial competition is transitioning from traditional product-centric approaches to a value co-creation-oriented paradigm centered on customer value and service capabilities. As a typical equipment manufacturing subsector, the woodworking machinery industry has long relied on equipment sales and after-sales maintenance models that fail to meet downstream furniture enterprises" demands for flexible production, intelligent operation and maintenance, and end-to-end …

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A Closer Look At The Innovator: The Interplay Between Divergent And Convergent Processes Of Self-Regulation, Ronald Bledow, Hye Jung Eun, Lien Vossaert Mar 2026

A Closer Look At The Innovator: The Interplay Between Divergent And Convergent Processes Of Self-Regulation, Ronald Bledow, Hye Jung Eun, Lien Vossaert

Research Collection Lee Kong Chian School Of Business

Creativity and innovation are essential for modern organizations. While abundant research has helped to better understand creativity in everyday work life, considerably less attention has been paid to how individuals achieve creative performance during the implementation of innovation projects. We articulate a dialectical interplay between divergent and convergent processes of self-regulation that supports creative performance in innovation projects. We propose that a divergent exploration orientation contributes to creative performance by inducing a broad search for novelty and by stimulating iteration—repeated cycles of experimentation and refinement. Convergent processes of self-regulation—outcome focus and planning—strengthen the relationship between divergent processes and creative performance. …

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Interest Fit Beyond The Riasec: The Comprehensive Assessment Of Basic Interests-O*Net (Cabin-Net), Chu Chu, Kevin A. Hoff, Zihan Liu, Nicholas F. Heimpel, Anthony Greco, Frederick L. Oswald, James Rounds Mar 2026

Interest Fit Beyond The Riasec: The Comprehensive Assessment Of Basic Interests-O*Net (Cabin-Net), Chu Chu, Kevin A. Hoff, Zihan Liu, Nicholas F. Heimpel, Anthony Greco, Frederick L. Oswald, James Rounds

Research Collection Lee Kong Chian School Of Business

Over the past half-century, Holland’s RIASEC model has dominated vocational interest research. Although the RIASEC categories effectively capture general occupational themes, their breadth obscures meaningful variability across underlying basic interests, which are more refined interest scales. In this research, we adapted the Comprehensive Assessment of Basic Interests (CABIN; Su et ., 2019) to be used alongside O*NET for assessing interest fit, resulting in the 60-item CABIN-NET that measures 20 basic interest scales organized under RIASEC domains. In Study 1, we refined items for the CABIN-NET using a nationally representative adult sample (N = 768). In Studies 2 and 3, we …

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Global Value Chains And Economic Inequality, Vivek Soundararajan, Ari Van Assche, Hari Bapuji, Gokhan Ertug Mar 2026

Global Value Chains And Economic Inequality, Vivek Soundararajan, Ari Van Assche, Hari Bapuji, Gokhan Ertug

Research Collection Lee Kong Chian School Of Business

In their inaugural editorial, Van Assche and De Marchi (2024) argued that meaningful progress in international business policy requires a more fine-grained understanding of how private international business practices intersect with public policy objectives. This editorial builds on that insight by applying it to a critical yet still underexplored issue – one on which we hope to see more research in this journal: the role of multinational enterprises (MNEs) and global value chains (GVCs) in shaping economic inequality within developing economies. Decisions related to sourcing, contracting, and GVC governance are inherently distributional rather than neutral, with important implications for how …

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Collaborative Work Management Technologies And Managerial Intensity In U.S. Corporations: An Examination, Piyush Gulati, Arianna Marchetti, Phanish Puranam Mar 2026

Collaborative Work Management Technologies And Managerial Intensity In U.S. Corporations: An Examination, Piyush Gulati, Arianna Marchetti, Phanish Puranam

Research Collection Lee Kong Chian School Of Business

Do digital technologies reinforce managerial hierarchies or, instead, make them less relevant? We propose that the answer to this question depends on the nature of the technology: specifically, its relative impact on managers' capacity to supervise and on subordinates' need for supervision. Applying this framework to collaborative work management (CWM) technologies that facilitate real-time collaboration, communication, and task coordination, we predict that the adoption of such technologies should reduce managerial intensity and increase decentralization in organizations. To test this prediction, we use a difference-in-differences design on a novel data set built from over 26 million job listings (Lightcast) and over …

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Optimizing And Fortifying Ai Software Through The Lens Of Artifact Synthesis, Jieke Shi Mar 2026

Optimizing And Fortifying Ai Software Through The Lens Of Artifact Synthesis, Jieke Shi

Dissertations and Theses Collection (Open Access)

Artificial Intelligence (AI) has transformed the software landscape, ushering in a new era of intelligent systems that increasingly shape our daily lives. This transformation is evident in various domains, including Software Engineering (SE), where Large Language Models (LLMs) support many development tools, and control systems, where self-driving cars and autonomous drones rely on deep learning models for real-time decision-making. These AI systems are collectively referred to as AI software, with the former categorized as AI4SE software (AI for Software Engineering) and the latter as AI4Control software (AI for Control). As AI software becomes central to modern computing infrastructure, its reliability …

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Governance-By-Support: Non-Financial Incentive, Agency Costs, And Performance In Overseas Projects, Jixiang Lyu Mar 2026

Governance-By-Support: Non-Financial Incentive, Agency Costs, And Performance In Overseas Projects, Jixiang Lyu

Dissertations and Theses Collection (Open Access)

As the Belt and Road Initiative continues to advance, multinational corporations from emerging economies have become increasingly reliant on expatriates to oversee overseas project execution, facilitate technology transfer, and manage on-site coordination. However, in contexts characterized by financial constraints, information opacity, and significant geographic and cultural distance, traditional Western models of expatriate management, which emphasize high compensation and tight monitoring, often prove difficult to sustain in practice. In reality, some firms are able to maintain high levels of expatriate commitment and stable overseas project performance even when expatriate compensation is below market levels. This seemingly anomalous phenomenon poses an interesting …

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A Study On The Relationship Between Traffic Spillover And Rental Rates Of Shopping Centre Stores Based On Consumer Movement Data, Hongjun Zhang Mar 2026

A Study On The Relationship Between Traffic Spillover And Rental Rates Of Shopping Centre Stores Based On Consumer Movement Data, Hongjun Zhang

Dissertations and Theses Collection (Open Access)

This study is based on consumer movement trajectory data and examines the relationship between traffic spillover among stores within shopping centres and their rent ratios, responding to the practical limitation that traditional rental pricing mechanisms often overlook the dynamic structure of customer flows. Using micro-level consumer movement data and store rental data from three shopping centres in Shenzhen, Nanjing, and Chongqing, this paper constructs a store transition network reflecting customer movements between stores. Social network analysis is employed to measure stores’ network influence indicators (such as degree centrality, betweenness centrality, and structural holes) as well as traffic spillover indicators derived …

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Art Pricing And Anti-Corruption Campaigns: Evidence From Repeat Sales Of Chinese Paintings, Yihan Wang Mar 2026

Art Pricing And Anti-Corruption Campaigns: Evidence From Repeat Sales Of Chinese Paintings, Yihan Wang

Dissertations and Theses Collection (Open Access)

My dissertation investigates the impact of China’s anti-corruption campaign on the pricing of traditional Chinese paintings, leveraging a unique dataset of repeat sales transactions. Since the 1990s, China’s art market has experienced explosive growth, becoming the world’s largest by 2011. However, this market is characterized by extreme opacity, facilitating elegant bribery (“ya hui” in Chinese), where artworks serve as vehicles for implicit corruption through inflated auctions or disguised gifts to officials. The launch of the "Eight-point Regulation" in December 2012 marked a significant intensification of anti-corruption efforts, raising the critical question of how such political shocks affect asset pricing in …

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Securing Ai Models Against Backdoors, Jailbreaks, And Prompt Injections, Myat Min Nay Mar 2026

Securing Ai Models Against Backdoors, Jailbreaks, And Prompt Injections, Myat Min Nay

Dissertations and Theses Collection (Open Access)

Deep neural networks (DNNs) and large language models (LLMs) in safety-critical settings face a family of related threats: an adversary can corrupt training so a hidden trigger flips a model’s behavior (backdoor), craft inference-time inputs that override safety alignment (jailbreaks) or smuggle in task-overriding instructions (prompt injections), or steer the model’s stance on whole concepts (semantic inconsistencies). Current defenses address each of these in isolation. This dissertation argues they admit a unified treatment through a shared diagnostic design principle: a matched perturbation, probing, or operating condition exposes a method-specific diagnostic signal in the model’s internal computation or observable behavior, and …

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Efficient Active Training For Deep Lidar Odometry, Beibei Zhou, Zhiyuan Zhang, Zhenbo Song, Jianhui Guo, Hui Kong Mar 2026

Efficient Active Training For Deep Lidar Odometry, Beibei Zhou, Zhiyuan Zhang, Zhenbo Song, Jianhui Guo, Hui Kong

Research Collection School Of Computing and Information Systems

Robust and efficient deep LiDAR odometry models are crucial for accurate localization and 3D reconstruction, but typically require extensive and diverse training data to adapt to diverse environments, leading to inefficiencies. To tackle this, we introduce an active training framework designed to selectively extract training data from diverse environments, thereby reducing the training load and enhancing model generalization. Our framework is based on two key strategies: Initial Training Set Selection (ITSS) and Active Incremental Selection (AIS). ITSS begins by breaking down motion sequences from general weather into nodes and edges for detailed trajectory analysis, prioritizing diverse sequences to form a …

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Opencil: Benchmarking Out-Of-Distribution Detection In Class Incremental Learning, Wenjun Miao, Guansong Pang, Trong-Tung Nguyen, Ruohuan Fang, Jin Zheng, Xiao Bai Mar 2026

Opencil: Benchmarking Out-Of-Distribution Detection In Class Incremental Learning, Wenjun Miao, Guansong Pang, Trong-Tung Nguyen, Ruohuan Fang, Jin Zheng, Xiao Bai

Research Collection School Of Computing and Information Systems

Class incremental learning (CIL) aims to learn a model that can not only incrementally accommodate new classes, but also maintain the learned knowledge of old classes. Out-of-distribution (OOD) detection in CIL is to retain this incremental learning ability, while being able to reject unknown samples that are drawn from different distributions of the learned classes. This capability is crucial to the safety of deploying CIL models in open worlds. However, despite remarkable advancements in the respective CIL and OOD detection, there lacks a systematic and large-scale benchmark to assess the capability of advanced CIL models in detecting OOD samples. To …

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Comprehensively Evaluating The Perception Systems Of Autonomous Vehicles Against Hazards, Xiaodong Zhang, Jie Bao, Jianlei Chi, Jun Sun, Zijiang Yang Mar 2026

Comprehensively Evaluating The Perception Systems Of Autonomous Vehicles Against Hazards, Xiaodong Zhang, Jie Bao, Jianlei Chi, Jun Sun, Zijiang Yang

Research Collection School Of Computing and Information Systems

Perception systems are vital for the safety of autonomous driving. In complex autonomous driving scenarios, autonomous vehicles must overcome various natural hazards, such as heavy rain or raindrops on the camera lens. Therefore, it is essential to conduct comprehensive testing of the perception systems in autonomous vehicles against these hazards, as demanded by the regulatory agencies of many countries for human drivers. Since there are many hazard scenarios, each of which has multiple configurable parameters, the challenges are (1) how do we systematically and adequately test an autonomous vehicle against these hazard scenarios, with measurable outcome; and (2) how do …

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Interpretable Machine Learning For Personalized Profiling Of Mild Cognitive Impairment From Daily Activities, Budhitama Subagdja, Ah-Hwee Tan, Kenneth Kwok, Iris Rawtaer Mar 2026

Interpretable Machine Learning For Personalized Profiling Of Mild Cognitive Impairment From Daily Activities, Budhitama Subagdja, Ah-Hwee Tan, Kenneth Kwok, Iris Rawtaer

Research Collection School Of Computing and Information Systems

Continuous monitoring of individual daily activities is essential to detect mild cognitive impairment (MCI) wherein timely intervention can still be applied to prevent more severe mental decline. Recent approaches in predicting MCI are mostly considering digital biomarkers across individuals but often neglecting specific indicators from a single person over a long period of time. Making this personalized, dynamic, and highly noisy prediction model with irregular distribution of missing information to be explainable and actionable for clinical use, remains a challenge. This paper presents a study on a personalized MCI prediction and profiling from an in-home and mobile cognitive health monitoring …

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A Knowledge Transfer-Based Membrane Evolutionary Algorithm For Solving Large-Scale Sorted Waste Collection Problem With Timeliness, Wenxue Zhang, Boquan Gao, Aldy Gunawan, Yunyun Niu, Jianhua Xiao Mar 2026

A Knowledge Transfer-Based Membrane Evolutionary Algorithm For Solving Large-Scale Sorted Waste Collection Problem With Timeliness, Wenxue Zhang, Boquan Gao, Aldy Gunawan, Yunyun Niu, Jianhua Xiao

Research Collection School Of Computing and Information Systems

The sorted collection of municipal solid waste has emerged as an effective waste management strategy due to varying timeliness requirements across different waste types, giving rise to the critical research challenge of timeliness-based waste collection. While existing algorithms primarily focus on small-scale versions of this problem, solving large-scale timeliness-based waste collection problems remains particularly challenging. To tackle this issue, this paper proposes a knowledge transfer-based membrane evolutionary algorithm. Specifically, the original problem and simplified problem are constructed in different membranes respectively, and the knowledge transfer learning mechanism is incorporated into the membrane evolutionary algorithm, enabling effective information exchange between the …

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Learning To Search For Vehicle Routing With Multiple Time Windows, Kuan Xu, Zhiguang Cao, Chenlong Zheng, Lindong Liu Mar 2026

Learning To Search For Vehicle Routing With Multiple Time Windows, Kuan Xu, Zhiguang Cao, Chenlong Zheng, Lindong Liu

Research Collection School Of Computing and Information Systems

In this study, we propose a reinforcement learning-based adaptive variable neighborhood search (RL-AVNS) method designed for effectively solving the Vehicle Routing Problem with Multiple Time Windows (VRPMTW). Unlike traditional adaptive approaches that rely solely on historical operator performance, our method integrates a reinforcement learning framework to dynamically select neighborhood operators based on real-time solution states and learned experience. We introduce a fitness metric that quantifies customers’ temporal flexibility to improve the shaking phase, and employ a transformer-based neural policy network to intelligently guide operator selection during the local search. Extensive computational experiments are conducted on realistic scenarios derived from the …

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Addressing Graph Heterogeneity And Heterophily From A Spectral Perspective, Kangkang Lu, Yanhua Yu, Ruopei Guo, Nan Cheng, Zhiyong Huang, Yunshan Ma, Meiyu Liang, Yuling Wang, Xiting Qin, Yimeng Ren, Tat-Seng Chua Mar 2026

Addressing Graph Heterogeneity And Heterophily From A Spectral Perspective, Kangkang Lu, Yanhua Yu, Ruopei Guo, Nan Cheng, Zhiyong Huang, Yunshan Ma, Meiyu Liang, Yuling Wang, Xiting Qin, Yimeng Ren, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Graph Neural Networks (GNNs) face two key challenges, heterogeneity and heterophily, which often degrade performance. Existing approaches either focus narrowly on specific meta-paths, limiting their expressiveness, or are expressive but cannot effectively leverage higher-order neighbors. In this paper, we propose the Heterogeneous Heterophilic Spectral Graph Neural Network (H2SGNN), which combines local independent filtering to adaptively handle meta-path subgraphs with varying homophily ratios, and global hybrid filtering to capture high-order neighbor interactions with linear computational complexity. On five heterogeneous graph benchmarks—DBLP, ACM, IMDB, AMiner, and Yelp—H2SGNN consistently outperforms strong baselines, for example, achieving +1.0% Macro-F1 and +1.3% Micro-F1 on IMDB. It …

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Edgeclip: Injecting Edge-Awareness Into Visual-Language Models For Zero-Shot Semantic Segmentation, Jiaxiang Fang, Shiqiang Ma, Guihua Duan, Fei Guo, Shengfeng He Mar 2026

Edgeclip: Injecting Edge-Awareness Into Visual-Language Models For Zero-Shot Semantic Segmentation, Jiaxiang Fang, Shiqiang Ma, Guihua Duan, Fei Guo, Shengfeng He

Research Collection School Of Computing and Information Systems

Effective segmentation of unseen categories in zero-shot semantic segmentation is hindered by models’ limited ability to interpret edges in unfamiliar contexts. In this paper, we propose EdgeCLIP, which addresses this by integrating CLIP with explicit edge-awareness. Based on the premise that edge variation patterns are similar across both seen and unseen class objects, EdgeCLIP introduces the Contextual Edge Sensing module. This module accurately discerns and utilizes edge information, which is crucial in complex border areas where conventional models struggle. Further, our Text-Guided Dense Feature Matching strategy precisely aligns text encodings with corresponding visual edge features, effectively distinguishing them from background …

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The Feelit System: Application Content-Aware Perspectives And Challenges On Understanding User Likes In Social Network Posts, Konstantinos Theocharidis, Hady W. Lauw, Panagiotis Karras Feb 2026

The Feelit System: Application Content-Aware Perspectives And Challenges On Understanding User Likes In Social Network Posts, Konstantinos Theocharidis, Hady W. Lauw, Panagiotis Karras

Research Collection School Of Computing and Information Systems

In a series of our prior works, we study influence and subscription maximization problems in social networks that are based on posts having influential content; as content we consider a set of features where each feature corresponds to a specific social network page, whereas influence and subscription relate to gaining the postlike and subscription-to-brand page of targeted users, respectively; subscription is conceptually achieved as repetitive influence on users. So, both influence and subscription depend on content that gains the likes of users; however, to be realistic, modeling and estimating such likes is a complex problem that has not been adequately …

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Cellscout: Visual Analytics For Mining Biomarkers In Cell State Discovery, Rui Sheng, Zelin Zang, Jiachen Wang, Yan Luo, Zixin Chen, Yan Zhou, Shaolun Ruan, Huamin Qu Feb 2026

Cellscout: Visual Analytics For Mining Biomarkers In Cell State Discovery, Rui Sheng, Zelin Zang, Jiachen Wang, Yan Luo, Zixin Chen, Yan Zhou, Shaolun Ruan, Huamin Qu

Research Collection School Of Computing and Information Systems

Cell state discovery is crucial for understanding biological systems and enhancing medical outcomes. A key aspect of this process is identifying distinct biomarkers that define specific cell states. However, difficulties arise from the co-discovery process of cell states and biomarkers: biologists often use dimensionality reduction to visualize cells in a two-dimensional space. Then they usually interpret visually clustered cells as distinct states, from which they seek to identify unique biomarkers. However, this assumption is often this assumption often fails to hold due to internal inconsistencies in a cluster, making the process trial-and-error and highly uncertain. Therefore, biologists urgently need effective …

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Prompt Tuning Without Labeled Samples For Zero-Shot Node Classification In Text-Attributed Graphs, Sethupathy Parameswaran, Suresh Sundaram, Yuan Fang Feb 2026

Prompt Tuning Without Labeled Samples For Zero-Shot Node Classification In Text-Attributed Graphs, Sethupathy Parameswaran, Suresh Sundaram, Yuan Fang

Research Collection School Of Computing and Information Systems

Node classification is a fundamental problem in information retrieval with many real-world applications, such as community detection in social networks, grouping articles published online and product categorization in e-commerce. Zero-shot node classification in text-attributed graphs (TAGs) presents a significant challenge, particularly due to the absence of labeled data. In this paper, we propose a novel Zero-shot Prompt Tuning (ZPT) framework to address this problem by leveraging a Universal Bimodal Conditional Generator (UBCG). Our approach begins with pre-training a graph-language model to capture both the graph structure and the associated textual descriptions of each node. Following this, a conditional generative model …

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Fortifying The Seams Between C/C++ And Rust: Characterizing Bugs In Interop Tools, Xuemeng Cai, Jiakun Liu, Cunyang Liu, Lingfeng Bao, Yijun Yu, Lingxiao Jiang Feb 2026

Fortifying The Seams Between C/C++ And Rust: Characterizing Bugs In Interop Tools, Xuemeng Cai, Jiakun Liu, Cunyang Liu, Lingfeng Bao, Yijun Yu, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Rust has become increasingly popular in recent years due to its safety and high performance. Despite these advantages, Rust projects rarely start from scratch in practice, and many Rust-based systems instead use hybrid programming, where Rust interoperates with existing C/C++ code. To reduce the manual effort involved in this interoperation (interop) process, several interop tools have been proposed to facilitate hybrid programming between Rust and C/C++. However, the challenges and limitations of these tools remain largely unexplored, leaving developers unclear about the future directions and users unclear about the appropriate usage scenarios. To fill the gap, we mined 320 bugs …

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