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Alumni Voices. Beyond Graduation: The Lifelong Global Impact Of A Uk Education, Sladana Krstic, Alexander Towne Jul 2026

Alumni Voices. Beyond Graduation: The Lifelong Global Impact Of A Uk Education, Sladana Krstic, Alexander Towne

Higher education research

The third round of the British Council Alumni Voices survey provides robust and timely evidence of the enduring value of a UK higher education experience. Drawing on three years of longitudinal survey data, supplemented by a number of interviews, the findings highlight how UK education continues to deliver skills, support professional progression, and foster long lasting international networks that extend well beyond graduation and national borders. Nearly three quarters of respondents report that in the last 12 months they have maintained contact with people they first met during their UK studies, and almost 84 percent have recommended a UK study …

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Integrated Optimization Of Farmland Cultivation And Fertilizer Application: Implications For Farm Management And Crop Production, Onur Boyabatli, Lusheng Shao, Yangfang (Helen) Zhou Jul 2026

Integrated Optimization Of Farmland Cultivation And Fertilizer Application: Implications For Farm Management And Crop Production, Onur Boyabatli, Lusheng Shao, Yangfang (Helen) Zhou

Research Collection Lee Kong Chian School Of Business

Motivated by the fresh produce industry, this paper studies a farmer’s joint cultivation and fertilizer (a representative farm input) application decisions facing uncertainties in yield, crop price, and harvesting cost where the latter two are yield dependent and yield is stochastically increasing in the fertilizer application rate. We develop a two-stage stochastic model of a farmer growing a commodity crop in a single season to maximize the expected profit. We then use the model to evaluate the optimal expected harvest volume (a measure of crop production). Our analytical analysis is complemented with numerical experiments calibrated to data. We characterize how …

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Draft Final 2023 Insufficiently Reclaimed Sites Sampling: Bres No. 93 – Soudan Dump Site Evaluation Summary Report, Pioneer Technical Services, Inc. Jul 2026

Draft Final 2023 Insufficiently Reclaimed Sites Sampling: Bres No. 93 – Soudan Dump Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Preparing Today’S Workforce For Tomorrow’S Autonomous Transportation: Bridging Electrical And Civil Engineering Disciplines, Masoud Ghodrat Abadi, Rohollah Moghadam Jul 2026

Preparing Today’S Workforce For Tomorrow’S Autonomous Transportation: Bridging Electrical And Civil Engineering Disciplines, Masoud Ghodrat Abadi, Rohollah Moghadam

Mineta Transportation Institute

Autonomous vehicles (AVs) are expected to transform transportation systems and reshape workforce needs across engineering and related fields. Although existing AV workforce development efforts often emphasize electrical engineering, computer science, and mechanical engineering, transportation engineering remains underrepresented despite its importance to infrastructure, traffic operations, safety, and mobility integration. This study addresses that gap through the development, implementation, and evaluation of an interdisciplinary certificate program, Workforce for Autonomous Vehicle Engineering (WAVE), at California State University, Sacramento. The program was designed to bridge transportation engineering and electrical engineering through a two-step curriculum model consisting of theoretical educational modules and hands-on laboratory activities. …

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The Effectiveness Of Writing Professional Development For Instructional Leaders On Student Academic Outcomes, Kourtney Y. Lavergne Jul 2026

The Effectiveness Of Writing Professional Development For Instructional Leaders On Student Academic Outcomes, Kourtney Y. Lavergne

Electronic Theses and Dissertations

The purpose of this qualitative case study was to explore how elementary instructional leaders in a Southeast Texas school district perceived and utilized the R.A.C.E. (Restate, Answer, Cite, Explain) professional development training as an instructional tool to improve student writing performance. The study was guided by two research questions: (a) How do elementary instructional leaders perceive the R.A.C.E. professional development training as an effective English writing curriculum tool to improve student performance? and (b) How do instructional leaders utilize the R.A.C.E. professional development training to improve student writing performance in their classrooms? The study was grounded in adult learning theory …

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Attendance And Academic Performance: A Comparison Of 4-Day And 5-Day School Week Schedules In Texas High Schools, Cynthia Miles Jul 2026

Attendance And Academic Performance: A Comparison Of 4-Day And 5-Day School Week Schedules In Texas High Schools, Cynthia Miles

Electronic Theses and Dissertations

This quantitative cross-sectional comparable study examined the differences in academic performance and attendance in Texas public high school campuses between those operating on a 4-day instructional week and those operating on a 5-day instructional week. The study used a quantitative, cross-sectional comparable design. The analysis included campus-level data from the Texas Education Agency’s Texas Academic Performance Reports. The independent variable was instructional schedule—either a 4-day or a 5-day instructional week. The dependent variables included campus attendance rates and student performance on the English I and Algebra I End-of-Course (EOC) STAAR (State of Texas Assessments of Academic Readiness) assessments of ninth-grade …

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Knowledge-State Generative Agents For Pre-Assessment Question Evaluation, Ping Fan Ke, Yi Meng Lau, Siaw Ling Lo Jul 2026

Knowledge-State Generative Agents For Pre-Assessment Question Evaluation, Ping Fan Ke, Yi Meng Lau, Siaw Ling Lo

Research Collection School Of Computing and Information Systems

This paper introduces a Knowledge‑State Generative Agent framework for evaluating the quality of pre‑assessment questions. The framework employs large language model (LLM)–based agents prompted to adopt a teacher persona to simulate the responses of students with and without mastery of targeted knowledge components. A preliminary empirical study using archival data from 424 students enrolled in an Information Systems Management course indicates that the proposed approach yields interpretable metrics under Classical Test Theory. Results further show that agents instantiated with the relevant mastered knowledge components exhibit systematically higher performance than agents lacking such mastery. In addition, the study suggests that teacher-persona …

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Dual-Diffusional Generative Fashion Recommendation, Mingzhe Yu, Lei Wu, Qianru Sun, Yunshan Ma Jul 2026

Dual-Diffusional Generative Fashion Recommendation, Mingzhe Yu, Lei Wu, Qianru Sun, Yunshan Ma

Research Collection School Of Computing and Information Systems

Personalized generative recommender systems have emerged as a promising solution for fashion recommendation. However, existing methods primarily rely on implicit visual embeddings from historical interactions, which often contain preference-irrelevant information and result in insufficient user behavior modeling. Moreover, these models typically generate only item images, providing limited interpretability. To address these limitations, we propose DualFashion, a Dual-Diffusional Generative Fashion Recommendation Architecture that jointly models image and text modalities for personalized and explainable recommendation. DualFashion adopts a dual-diffusion Transformer with image and text branches, where structured attribute-level captions and visual outfit information are jointly used as conditioning signals to model user …

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Avadclip: Audio-Visual Collaboration For Robust Video Anomaly Detection, Peng Wu, Wanshun Su, Guansong Pang, Yujia Sun, Qingsen Yan, Peng Wang, Yanning Zhang Jul 2026

Avadclip: Audio-Visual Collaboration For Robust Video Anomaly Detection, Peng Wu, Wanshun Su, Guansong Pang, Yujia Sun, Qingsen Yan, Peng Wang, Yanning Zhang

Research Collection School Of Computing and Information Systems

With the increasing adoption of video anomaly detection in intelligent surveillance domains, conventional visual-only detection approaches often struggle with information insufficiency and high false-positive rates in complex environments. To address these limitations, we present a novel weakly supervised framework that leverages audio-visual collaboration for robust video anomaly detection. Capitalizing on the exceptional cross-modal representation learning capabilities of Contrastive Language-Image Pretraining (CLIP) across visual, audio, and textual domains, our framework introduces two major innovations: an efficient audio-visual fusion that enables adaptive cross-modal integration through lightweight parametric adaptation while maintaining the frozen CLIP backbone, and a novel audio-visual prompt that dynamically enhances …

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2026 July, Morehead State University. Office Of Communications & Marketing. Jul 2026

2026 July, Morehead State University. Office Of Communications & Marketing.

Morehead State Press Release Archive, 1961 to the Present

Press releases for July of 2026.

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Interfacial Redox Mediation By Amine/Alkyne-Functionalized Silicon Nanoparticles: Surfactant-Free Gold Nanoparticle Synthesis, Amber L. Garcia, Brittany Griggs, Brian S. Mitchell, Mark J. Fink, Julie P. Vanegas Jul 2026

Interfacial Redox Mediation By Amine/Alkyne-Functionalized Silicon Nanoparticles: Surfactant-Free Gold Nanoparticle Synthesis, Amber L. Garcia, Brittany Griggs, Brian S. Mitchell, Mark J. Fink, Julie P. Vanegas

Physics & Astronomy Faculty Publications

We develop a surfactant-free synthesis method for gold nanoparticles (AuNPs) using 2-propynylamine-functionalized silicon nanoparticles as integrated redox-active supports. Surface-anchored amine groups act as built-in reducing sites for Au3+ precursors at the hexane–water interface under ambient conditions, enabling in situ AuNP nucleation and growth. Time-resolved UV-vis spectroscopy and dynamic light scattering track the emergence of plasmonic AuNPs, while quantitative morphology analysis reveals a final population dominated by spherical and near-spherical nanoparticles (∼74%), with faceted polyhedral structures (∼4%) and dendritic, hollow, irregular, and rod-like morphologies (∼22%) as minority species. The temporal evolution proceeds from early dendritic and irregular aggregates to a …

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Constraints On Gravitational Waves From The 2024 Vela Pulsar Glitch, A. G. Abac, I. Abouelfettouh, Teviet Creighton, Mario C. Diaz, Raul Alberto Espinosa Perez, J. Lawrence, Francisco Llamas Villarreal, Soma Mukherjee, Volker Quetschke, Miriam Ramos Arevalo, Wenhui Wang Jul 2026

Constraints On Gravitational Waves From The 2024 Vela Pulsar Glitch, A. G. Abac, I. Abouelfettouh, Teviet Creighton, Mario C. Diaz, Raul Alberto Espinosa Perez, J. Lawrence, Francisco Llamas Villarreal, Soma Mukherjee, Volker Quetschke, Miriam Ramos Arevalo, Wenhui Wang

Physics & Astronomy Faculty Publications

Among known neutron stars, the Vela pulsar is one of the best targets for gravitational-wave searches. It is also one of the most prolific in terms of glitches, which are sudden frequency changes in a pulsar’s rotation. Such glitches could cause a variety of transient gravitational-wave signals. Here, we search for signals associated with a Vela glitch on 2024 April 29 in data of the two LIGO detectors from the fourth LIGO–Virgo–KAGRA observing run. We search both for seconds-scale burst-like emission, primarily from fundamental (f-)mode oscillations, and for longer quasi-monochromatic transients up to 4 months in duration, primarily …

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Towards Reliable Large Language Models For Cyber Threat Intelligence, Md Tanvirul Alam Jul 2026

Towards Reliable Large Language Models For Cyber Threat Intelligence, Md Tanvirul Alam

Theses

Cyber Threat Intelligence (CTI) helps security analysts respond to evolving threats, but the evidence it draws on is often scattered across noisy reports, advisories, and threat descriptions. Large language models (LLMs) provide a flexible interface for security analysis, yet reliable use requires grounding their outputs in source evidence, domain schemas, and CTI standards. We address this problem through structured threat representation, task-specific evaluation, and verifier-guided post-training. First, we study how unstructured CTI reports can be converted into structured threat knowledge. We develop an ontology-guided extraction framework that normalizes attack patterns, extracts typed entities and relations, and constructs a threat intelligence …

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Activity Transition Graph Generation: How Far Are We?, Jiakun Liu, Peixin Zhang, Han Hu, Yonghui Liu, Wei Minn, Ferdian Thung, Shahar Maoz, Eran Toch, Debin Gao, David Lo Jul 2026

Activity Transition Graph Generation: How Far Are We?, Jiakun Liu, Peixin Zhang, Han Hu, Yonghui Liu, Wei Minn, Ferdian Thung, Shahar Maoz, Eran Toch, Debin Gao, David Lo

Research Collection School Of Computing and Information Systems

Android applications (i.e., apps) are indispensable nowadays and are getting bigger and bigger with an increasing number offunctionalities. To understand how to access functionalities in an app, prior studies proposed tools to model the transitionsbetween functionalities with the activity transition graph (ATG). ATG is an important data structure and has been used forvarious Android app analyses, including app design, understanding, and testing. However, there is no benchmarking work onATG generation. It is still unclear whether the transitions identified by tools are correct and how many transitions are missed.To fill this gap, we manually identified all transitions in 98 applications to …

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How Cultural Homogeneity Couples With Organizational Climate In Public School Environments, Steven R. Peterson Jul 2026

How Cultural Homogeneity Couples With Organizational Climate In Public School Environments, Steven R. Peterson

All-Inclusive List of Electronic Theses and Dissertations

This quantitative study examines how cultural homogeneity influences teachers’ perceptions of school climate in Indiana public schools. Grounded in systems thinking and organizational theory, the study analyzes how shared values and norms shape teachers’ responses to leadership practices and stakeholder demands. Data were collected from educators using the School Culture Survey and a custom scenario-based climate instrument capturing reactions to organizational challenges. Statistical analyses explored relationships between cultural homogeneity and teachers’ perceptions of stability, workload, and adaptive capacity. Results indicate that alignment in key cultural dimensions—particularly Collaborative Leadership—significantly shapes climate experiences, while overall homogeneity alone does not predict workload pressures. …

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Designing Functional Nanolaminates From Complex Atomic Layer Deposition Reactions, Joseph Joel Muhanga Jul 2026

Designing Functional Nanolaminates From Complex Atomic Layer Deposition Reactions, Joseph Joel Muhanga

Graduate Theses and Dissertations

Atomic layer deposition (ALD) enables precise cycle by cycle control over film thickness and composition. This kind of control is ideal for the engineering of functional nanolaminate coatings with tailored optical properties. Since ALD synthesized composite films are deposited as discrete, stratified layers and not as homogeneously intermixed solids, it is not yet clear when such composites can be be treated with the effective medium approximation (EMA). EMA is simplification that is important to the design of mixed oxide coatings. This dissertation addresses that question using a model system, and then asks whether the same approach can be used to …

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Survey On Learning-Based Dynamic Fault Localization: From Traditional Machine Learning To Large Language Models, Chunyan Liu, Yan Lei, Huan Xie, Jinping Wang, Yue Yu, David Lo Jul 2026

Survey On Learning-Based Dynamic Fault Localization: From Traditional Machine Learning To Large Language Models, Chunyan Liu, Yan Lei, Huan Xie, Jinping Wang, Yue Yu, David Lo

Research Collection School Of Computing and Information Systems

Learning-based dynamic fault localization techniques play a crucial role in the field of software engineering. These techniques dynamically execute test cases to meticulously extract useful knowledge from the execution information in the program, with the aim of identifying fault locations by leveraging machine learning, deep learning, and large language models. Currently, there is already a flourishing body of research that is intensely focused on learning-based dynamic fault localization. Research literature can be categorized into two main aspects for learning-based dynamic fault localization: data-based enhancements (i.e., the datasets) and model-based enhancements (i.e., the suspiciousness algorithms). Thus, we conduct an extensive literature …

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Beyond Hard Constraints: Budget-Conditioned Reachability For Safe Offline Reinforcement Learning, Brahmanage Janaka Chathuranga Thilakarathna, Akshat Kumar Jul 2026

Beyond Hard Constraints: Budget-Conditioned Reachability For Safe Offline Reinforcement Learning, Brahmanage Janaka Chathuranga Thilakarathna, Akshat Kumar

Research Collection School Of Computing and Information Systems

Sequential decision-making using Markov Decision Process underpins many real-world applications. Both model-based and model-free methods have achieved strong results in these settings. However, real-world tasks must balance reward maximization with safety constraints, often conflicting objectives, that can lead to unstable min–max, adversarial optimization. A promising alternative is safety reachability analysis, which precomputes a forward-invariant safe state–action set, ensuring that an agent starting inside this set remains safe indefinitely. Yet, most reachability-based methods address only hard safety constraints, and little work extends reachability to cumulative cost constraints. To address this, first, we define a safety-conditioned reachability set that decouples reward maximization …

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Scattered Hypothesis Generation For Open-Ended Event Forecasting, He Chang, Zhulin Tao, Lifang Yang, Xianglin Huang, Yunshan Ma Jul 2026

Scattered Hypothesis Generation For Open-Ended Event Forecasting, He Chang, Zhulin Tao, Lifang Yang, Xianglin Huang, Yunshan Ma

Research Collection School Of Computing and Information Systems

Despite the importance of open-ended event forecasting for risk management, current LLM-based methods predominantly target only the most probable outcomes, neglecting the intrinsic uncertainty of real-world events. To bridge this gap, we advance open-ended event forecasting from pinpoint forecasting to scatter forecasting by introducing the proxy task of hypothesis generation. This paradigm aims to generate an inclusive and diverse set of hypotheses that broadly cover the space of plausible future events. To this end, we propose SCATTER, a reinforcement learning framework that jointly optimizes inclusiveness and diversity of the hypothesis. Specifically, we design a novel hybrid reward that consists of …

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Mab-Dqa: Addressing Query Aspect Importance In Document Question Answering With Multi-Armed Bandits, Yixin Xiang, Yunshan Ma, Xiaoyu Du, Yibing Chen, Yanxin Zhang, Jinhui Tang Jul 2026

Mab-Dqa: Addressing Query Aspect Importance In Document Question Answering With Multi-Armed Bandits, Yixin Xiang, Yunshan Ma, Xiaoyu Du, Yibing Chen, Yanxin Zhang, Jinhui Tang

Research Collection School Of Computing and Information Systems

Document Question Answering (DQA) involves generating answers from a document based on a user’s query, representing a key task in document understanding. This task requires interpreting visual layouts, which has prompted recent studies to adopt multimodal Retrieval-Augmented Generation (RAG) that processes page images for answer generation. However, in multimodal RAG, visual DQA struggles to utilize a large number of images effectively, as the retrieval stage often retains only a few candidate pages (e.g., Top-4), causing informative but less visually salient content to be overlooked in favor of common yet low-information pages. To address this issue, we propose a Multi-Armed Bandit–based …

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Co-Matching: Towards Human–Model Collaborative Legal Case Matching, Chen Huang, Xinwei Yang, Yang Deng, Wenqiang Lei, Jiancheng Lv, Tat-Seng Chua Jul 2026

Co-Matching: Towards Human–Model Collaborative Legal Case Matching, Chen Huang, Xinwei Yang, Yang Deng, Wenqiang Lei, Jiancheng Lv, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Recent efforts have aimed to improve AI models in legal case matching by integrating legal domain knowledge. However, successful legal case matching requires the tacit knowledge of legal practitioners, which is difficult to verbalize and encode into models. This emphasizes the crucial role of involving legal practitioners in high-stakes legal case matching. To address this, we propose a collaborative matching framework called Co-Matching, which encourages both the model and the legal practitioner to participate in the matching process, integrating tacit knowledge. Unlike existing methods that rely solely on the model, Co-Matching allows both the legal practitioner and the model to …

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Production Of Seismic-Resistant Steel From Scrap With Up To 0.6% Copper, Iman El-Mahallawi, Ahmed Ramadan Seada Dr. Jul 2026

Production Of Seismic-Resistant Steel From Scrap With Up To 0.6% Copper, Iman El-Mahallawi, Ahmed Ramadan Seada Dr.

Mechanical Engineering

Earthquake-resistant steel grades of characteristic value defined by the ratio (UTS/YS) greater than 1.25 are verified through controlling the proportion of alloying elements in steel. This work illustrates a novel idea to produce earthquake-resistant steel grade utilizing steel scrap. Different heats were produced containing varying levels of copper, manganese, and silicon, along with deep desulfurization. The heats were hot rolled to diameters of 10, and 16 mm, followed by Tempcore process. JMatPro software was used to predict the formed phases. The chemical composition was determined by optical emission spectrometry. The tensile properties were determined by tensile testing, and bend testing …

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Global Prevalence Of Internet Gaming Disorder: An Umbrella Review Of Meta-Analytic Evidence And Implications For Child And Adolescent Psychiatry, Elisabeth C. S. Poon, Xun Ci Soh, Trina J. H. Poh, Andre C. S. Tan, Andree Hartanto Jul 2026

Global Prevalence Of Internet Gaming Disorder: An Umbrella Review Of Meta-Analytic Evidence And Implications For Child And Adolescent Psychiatry, Elisabeth C. S. Poon, Xun Ci Soh, Trina J. H. Poh, Andre C. S. Tan, Andree Hartanto

Research Collection School of Social Sciences

Background/Objectives: Internet gaming has become a widespread global activity, raising concerns about the prevalence of Internet Gaming Disorder (IGD). However, existing meta-analyses report highly variable prevalence estimates. This umbrella review aims to clarify the prevalence and variability of IGD by synthesizing evidence from meta-analyses to provide a comprehensive overview of IGD prevalence across populations, age groups, and regions. Methods: Following PRISMA guidelines, systematic searches were carried out across five published literature databases and two supplementary search sources. Title and abstract screening, followed by full-text eligibility assessment, were conducted independently by three authors. The same three authors then performed data extraction …

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Robust Generator Maintenance Schedule For Frequency-Secure Power Systems, Yang Yang, Qiuzhuang Sun, Jimmy Chih-Hsien Peng, Loon Ching Tang, Zhisheng Ye Jul 2026

Robust Generator Maintenance Schedule For Frequency-Secure Power Systems, Yang Yang, Qiuzhuang Sun, Jimmy Chih-Hsien Peng, Loon Ching Tang, Zhisheng Ye

Research Collection College of Integrative Studies

Problem definition: Normal operations of a power system require that alternating current frequency be maintained at a nominal value, for example, 50 Hz, whereas severe deviation from this value due to power deficiencies can cause cascading generator trips. Maintaining the frequency requires adequate inertia and frequency regulation reserve, which are primarily provided by online generators. In daily operations, generators due for preventive maintenance must be taken offline, and thus an improper maintenance schedule could jeopardize frequency security, as exemplified by the recent Texas power blackout. However, this natural nexus between frequency security and maintenance has been over-looked largely in the …

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Online Planning Of Power Flows For Power Systems Against Bushfires Using Spatial Context, Jianyu Xu, Qiuzhuang Sun, Yang Yang, Huadong Mo, Daoyi Dong Jul 2026

Online Planning Of Power Flows For Power Systems Against Bushfires Using Spatial Context, Jianyu Xu, Qiuzhuang Sun, Yang Yang, Huadong Mo, Daoyi Dong

Research Collection College of Integrative Studies

A power station or transmission line can be affected due to bushfires, increasing operation costs. We study a fundamental but challenging problem of planning the optimal power flow (OPF) for power systems under bushfires. We develop a model to capture the stochastic nature of bushfire spread based on Moore’s neighborhood model and propose an online optimization modeling framework to sequentially plan power flows in the electricity network. Our framework assumes that bushfire spread is non-stationary over time and that the spread and containment probabilities are unknown. To address these challenges, we develop a contextual online learning algorithm that treats the …

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Coupled Effects Of Sub-Atmospheric Pressure And Surface Structures On Pool Boiling Performance And Hysteresis Pathways, Mohammad Ishraq Hossain Jul 2026

Coupled Effects Of Sub-Atmospheric Pressure And Surface Structures On Pool Boiling Performance And Hysteresis Pathways, Mohammad Ishraq Hossain

Graduate Theses and Dissertations

The increasing power density of microelectronics has created a need for cooling technologies capable of maintaining low operating temperatures. Sub-atmospheric pool boiling of water is promising because reducing saturation pressure lowers the boiling temperature, enabling two phase cooling within electronics-relevant temperature limits. However, reduced pressure also affects CHF, HTC, and post-CHF recovery. In this work, pool boiling experiments were conducted on flat copper, microchannel copper, and micro-pin-fin copper surfaces over 10–100 kPa to examine the coupled effects of pressure and surface structure. CHF and HTC increased with pressure, while structured surfaces enhanced both relative to flat copper. Surface structure dominated …

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Purifai: Detecting And Fixing Search-Induced Distortions In Web-Augmented Llms, Guoqing Wang, Zhao Zhang, Zeyu Sun, Xiaofei Xie, Yizhou Chen, Yanchao Tan, Dan Hao Jul 2026

Purifai: Detecting And Fixing Search-Induced Distortions In Web-Augmented Llms, Guoqing Wang, Zhao Zhang, Zeyu Sun, Xiaofei Xie, Yizhou Chen, Yanchao Tan, Dan Hao

Research Collection School Of Computing and Information Systems

As Large Language Models (LLMs) increasingly serve as interfaces for proprietary data (e.g., enterprise knowledge bases, legal statutes), ensuring their fidelity to trusted internal information is paramount. While integrating real-time web search can enhance model utility, it introduces a critical vulnerability: the ingestion of conflicting, misleading, or hallucinated content from the open web can override the model's adherence to its verified internal knowledge. We define this failure mode as search-induced distortion, a significant risk in high-stakes domains where the internal knowledge base serves as the absolute ground truth.To address this challenge, we present PurifAI, a proactive, model-agnostic, cache-level purification system …

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Verbalizing Lightgcn: Direct Learning Of Textual Representations From User-Item Interaction Graph Via Llms, Manh-Khanh Ngo Huu, Hady Wirawan Lauw Jul 2026

Verbalizing Lightgcn: Direct Learning Of Textual Representations From User-Item Interaction Graph Via Llms, Manh-Khanh Ngo Huu, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

In this work, we propose VerbaLightGCN, a novel LLM-based recommendation framework that integrates the semantic understanding of LLMs with user-item interaction modeling. Traditional collaborative filtering (CF) models typically embed user and item IDs into a latent space to capture interaction signals. However, pretrained LLMs cannot natively interpret these learned embeddings. To bridge this gap, VerbaLightGCN adopts a CF-as-text paradigm, in which collaborative signals are encoded in textual form and directly learned from the user–item interaction graph, and are then combined with semantic information to construct user and item profiles that function as latent embeddings. Inspired by LightGCN, our method retains …

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Generation-Augmented Video Corpus Moment Retrieval, Mingjin Kuai, Qianyin Xiao, Juncheng Li, Jin Peng, Lizi Liao, Wei Ji Jul 2026

Generation-Augmented Video Corpus Moment Retrieval, Mingjin Kuai, Qianyin Xiao, Juncheng Li, Jin Peng, Lizi Liao, Wei Ji

Research Collection School Of Computing and Information Systems

Video Corpus Moment Retrieval (VCMR) requires models to efficiently retrieve and precisely locate specific moments relevant to natural language queries within a massive, untrimmed video corpus. However, existing discriminative approaches typically rely on shallow visual-textual feature matching mechanisms, which often struggle to capture fine-grained semantic differences. To address this limitation, we propose Video-GAR, a novel framework that reframes the conventional retrieval task from superficial matching to generative understanding, positing that the capability for query reconstruction evidences deep semantic comprehension. Specifically, Video-GAR orchestrates three synergistic components: To overcome the computational efficiency bottleneck, we construct a Bi-Mamba backbone that leverages the linear …

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Advancing Imbalanced Classification Through Representation Learning, Morteza Mohammady Gharasuie Jul 2026

Advancing Imbalanced Classification Through Representation Learning, Morteza Mohammady Gharasuie

Computer Science Theses & Dissertations

Real-world datasets frequently exhibit severe class imbalance, where certain categories are significantly underrepresented relative to others, leading standard empirical risk minimization to bias learning toward majority classes and degrade performance on minority categories. This dissertation addresses imbalanced classification across both structured tabular data and long-tailed visual recognition by developing methods that improve representation learning and decision reliability under skewed distributions. For tabular data, it introduces Conditional Probability Representation (CPR), a target-based encoding framework that embeds feature–label relationships directly into the representation space, enhanced by a progressive feature upgrading mechanism for semi-supervised settings and a class-frequency–aware extension that improves robustness to …

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