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2024

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A Novel Statistical Approach To Obtain The Best Visibility Slice In Mri Sequence Of Brain Tumors, Hassan Al-Yassin, Mohammed A. Fadhel, Omran Al-Shamma Nov 2024

A Novel Statistical Approach To Obtain The Best Visibility Slice In Mri Sequence Of Brain Tumors, Hassan Al-Yassin, Mohammed A. Fadhel, Omran Al-Shamma

Baghdad Science Journal

Early diagnosis of brain tumor enhances the possibility of patients being cured. With the progress of the use of artificial intelligence in the medical field, the detection of brain tumors has become one of the researchers’ interests. Obtaining which slice in the MRI sequence gives the best visibility of the tumor is still a challenge. This paper introduced a novel statistical approach to extracting the tumor from the patient's MRI scan (sequence). Initially, the probability mass function (PMF) was computed for each image in the sequence. Then, the Kullback-Leibler divergence technique was applied to determine the tumor image(s) that diverged …

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Coupled Of Semi Analytic Approach Associated With Laplace Transform First Step For Solving Matrix Differential Equations Quadratic Form When The Time-Delay In Noise Term, Khalid Hammood Al-Jizani Nov 2024

Coupled Of Semi Analytic Approach Associated With Laplace Transform First Step For Solving Matrix Differential Equations Quadratic Form When The Time-Delay In Noise Term, Khalid Hammood Al-Jizani

Baghdad Science Journal

A novel technique and an efficient modification based on Adomian decomposition method and homotopy approach for finding accurately analytic solutions to non-linear (noise term) quadratic matrix retarded delay equations connected with the method of steps to make the problem more easily is discussed. These approaches more efficiently, effectively and accurately. Wholly integration for homotopy analysis method use in state the wholly integration for Adomian approach. Main advantage of this technique is to get more an accurate and efficient results with more extended of the convergence region of iterative approximate solutions obtained with bigger and whole time interval and to know …

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A New Replacement Model Under Trapezoidal Fuzzy Number Environment, Balaganesan M, Melita Vinoliah E, Krishnaveni G Nov 2024

A New Replacement Model Under Trapezoidal Fuzzy Number Environment, Balaganesan M, Melita Vinoliah E, Krishnaveni G

Baghdad Science Journal

In today’s dynamic world, the replacement of machinery and facilities is a permanent and complicated issue due to rapid technical growth and globalization, which is a shared concern in the minds of the owners of any business. Maintenance is a scheduled procedure to ensure that equipment, systems, or facilities remain normal to perform their intended purpose correctly without risking the loss of service time due to their failure. To maintain a certain degree of consistency, protection, and performance maintenance activities for systems and facilities in good working conditions are indispensable. The repair operation helps to preserve and increase the operating …

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Tackling Toxicity And Harassment In Online Environments Through The Use Of Artificial Intelligence, Heba Saleous Nov 2024

Tackling Toxicity And Harassment In Online Environments Through The Use Of Artificial Intelligence, Heba Saleous

Dissertations

With the increase in popularity of online communities, such as social media platforms, online games, and chatroom servers, there is a need to improve chat and content moderation. Platforms have reported an increase in the prevalence of toxic behavior and hate speech. Meanwhile, moderators are reporting difficulties in keeping up with the amount of data to check as well and the type of content they are exposed to, which further harms their own mental health. The main objective of this work is to address the challenges that exist within online communities with the rising prevalence of hate speech. Additionally, some …

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L&D On-Ramps And Off-Ramps For The Mobility Workforce: A Blueprint For Knowledge Ecosystem Formation In The Fourth Industrial Revolution, Tyler Reeb, Barbara Taylor, James Reuter Nov 2024

L&D On-Ramps And Off-Ramps For The Mobility Workforce: A Blueprint For Knowledge Ecosystem Formation In The Fourth Industrial Revolution, Tyler Reeb, Barbara Taylor, James Reuter

Mineta Transportation Institute

After a yearlong consensus study, this report presents a blueprint with implementation tools and strategies for CSULB and other CSU campuses to adopt a knowledge ecosystem model in higher education. By conducting talent pipeline pilots for internship preparation activities and related survey and focus group research, the research team found near universal support for pursuing university-industry partnerships. Faculty identified extracurricular activities, experiential learning opportunities, and guidance on further education as their top three priorities when mentoring students in professional development. There was, however, a paradoxical perception among faculty about what universities provide in terms of knowledge, skills, and abilities (KSAs) …

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Getting On Board With Incentivising Esg, Shai Ganu Nov 2024

Getting On Board With Incentivising Esg, Shai Ganu

Asian Management Insights

What gets rewarded gets measured and done. Shai Ganu, Managing Director and Global Leader of the Executive Compensation and Board Advisory business at WTW, discusses the increasing adoption of Environmental, Social, and Governance (ESG) metrics in structuring executive compensation. He explores how incorporating ESG goals into incentive plans drives accountability and aligns leadership performance with long-term sustainability objectives.

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Perspectives Through The Lens Of Educators And Students: Teaching Flood Mitigation And Other Controversial Food, Energy, Water Nexus Issues In The Classroom, Sumaiya Tabassum Nov 2024

Perspectives Through The Lens Of Educators And Students: Teaching Flood Mitigation And Other Controversial Food, Energy, Water Nexus Issues In The Classroom, Sumaiya Tabassum

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Science and society are inseparably linked, shaping each other in ways that define our world, emphasizing the need to teach science for empowering students capable of taking meaningful action toward building a sustainable and just society. Developing sustainability competencies in students is an important step toward this goal, with controversial socio-scientific issues (SSIs) providing a valuable teaching context, that encourage students in analyzing interdisciplinary evidence while considering the social, economic impacts of potential solutions. However, recognizing the unique perspectives individuals bring to the classroom is prerequisite for tailoring effective, inclusive instruction, as perspectives often shape learning and classroom-engagement. This study …

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Anti-Corrosion Performance Of Magnesium Potassium Phosphate Cement Coating On Steel Reinforcement: The Effect Of Boric Acid, Fan Zhang, Jihui Qin, Kangyi Cai, John J. Myers, Hongyan Ma Nov 2024

Anti-Corrosion Performance Of Magnesium Potassium Phosphate Cement Coating On Steel Reinforcement: The Effect Of Boric Acid, Fan Zhang, Jihui Qin, Kangyi Cai, John J. Myers, Hongyan Ma

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

It has recently been found that magnesium potassium phosphate cement (MKPC) paste coating applied on the surface of steel reinforcement can effectively retard the onset of corrosion and suppress corrosion reactions. However, the fast-setting nature of MKPC—which is a merit in repair—can be problematic in a practical engineering process of coating the steel reinforcement with MKPC paste. To address this problem, boric acid (H3BO3) was added as a retarder in an MKPC formulation to prolong the setting time. This work investigated the impact of boric acid (at 5% by weight of MgO) on the anti-corrosion performance …

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The Digital Renaissance In Education: Adapting Generative Ai In Pre-Service Teacher And Provider Strategies, Jennifer J. Lesh, Jévaughn J. Lancaster Nov 2024

The Digital Renaissance In Education: Adapting Generative Ai In Pre-Service Teacher And Provider Strategies, Jennifer J. Lesh, Jévaughn J. Lancaster

Faculty and Staff Publications & Presentations

Dr. Lesh's second presentation, "The Digital Renaissance in Education: Adapting Generative AI in Pre-Service Teacher and Provider Strategies," offered insights into the transformative role of generative AI in teacher education. Collaborating with Dr. JeVaughn Lancaster virtually, Lesh and Lancaster shared data from a recent study examining teachers' perceptions of AI in academic research. Findings underscored the potential for AI to enhance educational efficiency while also identifying ethical considerations that must be addressed. Lesh and Lancaster advocated for responsible AI training, stressing that generative AI should augment, not replace, educators' expertise and critical thinking.

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Investigating Social-Ecological Linkages In Baltimore, Md: Environmental Stewardship, Green Stormwater Infrastructure, And Tree Canopy Change At The Neighborhood Level, Sarah Ponte, Nancy F. Sonti, Dexter H. Locke, Jennifer Mullinax, Mitchell Pavao-Zuckerman Nov 2024

Investigating Social-Ecological Linkages In Baltimore, Md: Environmental Stewardship, Green Stormwater Infrastructure, And Tree Canopy Change At The Neighborhood Level, Sarah Ponte, Nancy F. Sonti, Dexter H. Locke, Jennifer Mullinax, Mitchell Pavao-Zuckerman

Cities and the Environment (CATE)

Environmental stewardship organizations in Baltimore play important roles in taking care of the local environment through conservation, management, restoration, monitoring, education, and other efforts. These diverse activities were captured in Baltimore’s Stewardship Mapping and Assessment Project (STEW-MAP) surveys in 2011 and 2019. Despite previous research, knowledge gaps remain about the spatial and temporal dynamics of environmental stewardship groups and their relationships with elements of the built environment, such as green stormwater infrastructure (GSI) and tree canopy cover. Using spatial Bayesian regression, we examine how 1) voluntary GSI, 2) regulatory GSI, 3) tree canopy cover, and 4) tree canopy cover change …

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The Effects Of Wildfires On The Mental And Physical Health Of School-Age Children In North America: A Scoping Review, Sarah Oerther, Sarah Manspeaker, Alison Wix, Daniel Oerther, Carmen Marsit Nov 2024

The Effects Of Wildfires On The Mental And Physical Health Of School-Age Children In North America: A Scoping Review, Sarah Oerther, Sarah Manspeaker, Alison Wix, Daniel Oerther, Carmen Marsit

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Background: Wildfires are occurring more often and with greater intensity, leading to longer and harsher fire seasons. As a result, children are more frequently exposed to wildfire smoke, which increases their risk of mental and physical health effects. Purpose: The purpose of our scoping review is to explore the current literature on what is known about the direct and indirect impacts of wildfires on the mental and physical health of school-age children in North America (5 to 18-year-olds). Methods: A health sciences librarian-assisted literature search, with input from the research team, was performed. Results: A total of 16 studies were …

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Neutrosophic Logic-Based Crop Yield Prediction And Risk Assessment Using Least Squares Regression, M. Srikanth, R.N.V. Jagan Mohan, M. Chandra Naik Nov 2024

Neutrosophic Logic-Based Crop Yield Prediction And Risk Assessment Using Least Squares Regression, M. Srikanth, R.N.V. Jagan Mohan, M. Chandra Naik

Neutrosophic Systems with Applications

Agriculture faces significant challenges due to climate change and unpredictable environmental factors, which impact crop yields and threaten food security. This study proposes a novel approach to crop yield prediction and risk assessment using neutrosophic logic and least squares regression. By integrating these methods, we aim to improve accuracy in predicting crop losses under uncertain conditions. The model classifies crops based on profitability and environmental risks, utilizing the independence test to evaluate the relationships between crop attributes. Our approach leverages deep learning techniques, such as restricted Boltzmann machines (RBM), to enhance the analysis of crop data and provide farmers with …

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The Danger Of Silence: The Negative Effect Of Supreme Court Hesitance To Establish A Bright-Line Rule For Determining Patent Subject Matter Eligibility, Amber N. Roibu Nov 2024

The Danger Of Silence: The Negative Effect Of Supreme Court Hesitance To Establish A Bright-Line Rule For Determining Patent Subject Matter Eligibility, Amber N. Roibu

Touro Law Review

Ambiguity surrounding the interpretation of 35 U.S.C. § 101 and the ultimate application of the Alice/Mayo standard for determining patent subject matter eligibility has long plagued the courts, practitioners, and USPTO examiners alike. Maintaining a standard that leads to sheer confusion and, as a result, inconsistent rulings severely muddles the ultimate goal of patent law, to promote innovation. The Supreme Court has been presented with ample opportunities to address these issues, with the Solicitor General consistently recommending that it hear cases that deal with patent-eligibility debates. Nonetheless, the Supreme Court's continued hesitancy to grant certiorari on these cases only further …

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Addressing Governance Challenges Of Digitalisation And Sustainability: The Case Of Central Bank Digital Currency, Heng Wang Nov 2024

Addressing Governance Challenges Of Digitalisation And Sustainability: The Case Of Central Bank Digital Currency, Heng Wang

Research Collection Yong Pung How School Of Law

Digitalisation and environmental sustainability are widely discussed topics. However, their nexus remains underexplored and can pose significant challenges for governments and industries alike. The environmental implications of digitalisation are becoming increasingly pertinent with the advent of central bank digital currencies (CBDCs) and their inherent energy consumption and production of e-waste. On the other hand, digitalisation could potentially support sustainability efforts. This begs the question of how systems of governance, such as regulatory frameworks and internal organisational governance, should harmonise digitalisation and sustainability goals. Such harmonisation entails ensuring that digitalisation processes are environmentally responsible while exploring how the application and features …

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Media Use, Interpersonal Communication, And Personal Relevance As External And Internal Representations Of Climate Change, Sonny Rosenthal, Pengya Ai Nov 2024

Media Use, Interpersonal Communication, And Personal Relevance As External And Internal Representations Of Climate Change, Sonny Rosenthal, Pengya Ai

Research Collection College of Integrative Studies

Personal relevance is a key driver of individual climate action. It is also related to media use and interpersonal communication, which the current study examines from two perspectives. First, individuals may find climate change personally relevant because they experience it vicariously through the media and other information sources. Second, they may engage with climate change information because the issue is personally relevant. This study tested these models using structural equation modeling of online survey data from representative samples in Singapore (n = 1,997) and the United States (n = 2,009). Findings supported both models, albeit the first one more strongly. …

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Leading Edge Erosion Classification In Offshore Wind Turbines Using Feature Extraction And Classical Machine Learning, Oscar Best, Asiya Khan, Sanjay Sharma, Keri Collins, Mario Gianni Nov 2024

Leading Edge Erosion Classification In Offshore Wind Turbines Using Feature Extraction And Classical Machine Learning, Oscar Best, Asiya Khan, Sanjay Sharma, Keri Collins, Mario Gianni

School of Engineering, Computing and Mathematics

Leading edge (LE) erosion is a type of damage that inhibits the aerodynamic performance of a wind turbine, resulting in high operation and maintenance (O&M) costs. This paper makes use of a small dataset consisting of 50 images of LE erosion and healthy blades for feature extraction and the training of four types of classifiers, namely, support vector machine (SVM), random forest, K-nearest neighbour (KNN), and multi-layer perceptron (MLP). Six feature extraction methods were used with these classifiers to train 24 models. The dataset has also been used to train a convolutional neural network (CNN) model developed using Keras. The …

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Unlocking College Potential: The Role Of Student Expectations And Non-Cognitive Skills In College Success, Gema Zamarro, Malachi Nichols, Julie R. Trivitt, Rian Djita Nov 2024

Unlocking College Potential: The Role Of Student Expectations And Non-Cognitive Skills In College Success, Gema Zamarro, Malachi Nichols, Julie R. Trivitt, Rian Djita

Education Reform Faculty and Graduate Students Publications

Attending college is a significant human capital investment but only about 60% of those who start college will have a completed degree six years later. This makes identifying the skills associated with college success an important policy concern. We surveyed over 1,100 entering college freshmen, majoring in business and engineering at a public university in the US, and combined this information with administrative data to create a comprehensive data set that, in addition to the usual academic performance data, cognitive ability measures, and demographics, also included measures of non-cognitive skills, personality traits, student expectations about college success and performance at …

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Enhancedbert: A Python Software Tailored For Arabic Word Sense Disambiguation, Sanaa Kaddoura, Reem Nassar Nov 2024

Enhancedbert: A Python Software Tailored For Arabic Word Sense Disambiguation, Sanaa Kaddoura, Reem Nassar

All Works

EnhancedBERT is a software framework designed to disambiguate Arabic polysemous terms using advanced natural language processing techniques. It integrates transformer architectures with ensemble methods to achieve high performance in understanding and processing Arabic text. The framework provides a flexible pipeline that can be directly utilized or fine-tuned according to specific needs. EnhancedBERT stands out for its ease of use, leveraging transformer-based models combined with ensemble strategies to provide superior contextual understanding. This contextual awareness makes it an invaluable tool for researchers and practitioners tackling complexities in Arabic language processing.

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Insurrection-Proofing The Courts: Judicial Tools To Protect The Legal System From Litigation Abuse In The Wake Of The 2024 Election, Raymond H. Brescia Nov 2024

Insurrection-Proofing The Courts: Judicial Tools To Protect The Legal System From Litigation Abuse In The Wake Of The 2024 Election, Raymond H. Brescia

SMU Law Review Forum

In the wake of the 2020 presidential election in the United States, lawyers sought to overturn the results of that election filing baseless and far-fetched claims. Courts sanctioned many of those lawyers and at least some of them have been disbarred or are in the last throes of disbarment proceedings. Yet such punishment has come nearly four years after the events that precipitated the need for such professional discipline. Are there things courts can do now, on the immediate eve of the next presidential contest, to “insurrection-proof” their courtrooms to make sure that the legal system is not used, once …

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Padlet As A Tool For Collaborative And Personalized Learning For University Courses, Yi Meng Lau, Wee Ling Loo, Bei Hong, Yuanto Kusnadi Nov 2024

Padlet As A Tool For Collaborative And Personalized Learning For University Courses, Yi Meng Lau, Wee Ling Loo, Bei Hong, Yuanto Kusnadi

Research Collection School Of Computing and Information Systems

This study investigates the effectiveness of Padlet, a technology-enhanced tool, that supports collaborative and personalized learning, and its success in meeting specific learning outcomes and course objectives. We developed a framework that synthesizes the learning characteristics of technology-enabled collaborative and personalized learning, integrating the strengths of both learning modes. Unlike other studies which typically focus on a single discipline, our framework is evaluated with the use of Padlet across four university courses, spanning three disciplines (Information Systems, Economics and Law). Survey results showed that Padlet enhanced both learning types and achieved the desired outcomes. Linear regression analysis underscored Padlet's effectiveness …

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Uncovering Merchants’ Willingness To Wait In On-Demand Food Delivery Markets, Jian Liang, Ya Zhao, Hai Wang, Zuopeng Xiao, Jintao Ke Nov 2024

Uncovering Merchants’ Willingness To Wait In On-Demand Food Delivery Markets, Jian Liang, Ya Zhao, Hai Wang, Zuopeng Xiao, Jintao Ke

Research Collection School Of Computing and Information Systems

While traditional on-demand food delivery services help restaurants reach more customers and enable doorstep deliveries, they also come with drawbacks, such as high commission fees and limited control over the delivery process. White-label food delivery services have emerged as an alternative, ready-to-use platform for restaurants to arrange delivery for customer orders received through their applications or websites, without the constraints imposed by traditional on-demand food delivery platforms or the need to develop an in-house delivery operation. Although several studies have investigated consumer behavior when using traditional on-demand food delivery services, there is limited research on merchants’ behavior when adopting white-label …

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Badfl: Backdoor Attack Defense In Federated Learning From Local Model Perspective, Haiyan Zhang, Xinghua Li, Mengfan Xu, Ximeng Liu, Tong Wu, Jian Weng, Robert H. Deng Nov 2024

Badfl: Backdoor Attack Defense In Federated Learning From Local Model Perspective, Haiyan Zhang, Xinghua Li, Mengfan Xu, Ximeng Liu, Tong Wu, Jian Weng, Robert H. Deng

Research Collection School Of Computing and Information Systems

There is substantial attention to federated learning with its ability to train a powerful global model collaboratively while protecting data privacy. Despite its many advantages, federated learning is vulnerable to backdoor attacks, where an adversary injects malicious weights into the global model, making the global model's targeted predictions incorrect. Existing defenses based on identifying and eliminating malicious weights ignore the similarity variation of the local weights during iterations in the malicious model detection and the presence of benign weights in the malicious model during the malicious local weight elimination, resulting in a poor defense and a degradation of global model …

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Ask-Before-Plan : Proactive Language Agents For Real-World Planning, Xuan Zhang, Yang Deng, Zifeng Ren, See-Kiong Ng, Tat-Seng Chua Nov 2024

Ask-Before-Plan : Proactive Language Agents For Real-World Planning, Xuan Zhang, Yang Deng, Zifeng Ren, See-Kiong Ng, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

The evolution of large language models (LLMs) has enhanced the planning capabilities of language agents in diverse real-world scenarios. Despite these advancements, the potential of LLM-powered agents to comprehend ambiguous user instructions for reasoning and decision-making is still under exploration. In this work, we introduce a new task, Proactive Agent Planning, which requires language agents to predict clarification needs based on user-agent conversation and agent-environment interaction, invoke external tools to collect valid information, and generate a plan to fulfill the user's demands. To study this practical problem, we establish a new benchmark dataset, Ask-before-Plan. To tackle the deficiency of LLMs …

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National Use Of Artificial Intelligence For Eye Screening In Singapore, Dinesh Visva Gunasekeran, Steven Miller, Wynne Hsu, Mong Li, Tym Hon Wong, Mun Tuck Lee, Ecosse Lamoureau, Daniel Shu Wei Ting, Gavin Siew Wei Tan, Tien-Yin Wong Nov 2024

National Use Of Artificial Intelligence For Eye Screening In Singapore, Dinesh Visva Gunasekeran, Steven Miller, Wynne Hsu, Mong Li, Tym Hon Wong, Mun Tuck Lee, Ecosse Lamoureau, Daniel Shu Wei Ting, Gavin Siew Wei Tan, Tien-Yin Wong

Research Collection School Of Computing and Information Systems

Diabetes is a major health care challenge, affecting 10% of the global population. One third of patients with diabetes have an ocular complication known as diabetic retinopathy (DR). DR progression to manifestations such as vision-threatening diabetic retinopathy (VTDR) remains the leading cause of blindness in working-aged adults. Yearly DR screening is a universally recommended practice in primary care settings for patients with diabetes, but it is often difficult to implement due to a lack of staffing and screening capacity in primary care. This case study highlights our experience with developing a medical artificial intelligence (AI) software-as-a-medical-device (SaMD) solution for DR …

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Don’T Just Say “I Don’T Know”! Self-Aligning Large Language Models For Responding To Unknown Questions With Explanations, Yang Deng, Yong Zhao, Moxin Li, See-Kiong Ng, Tat-Seng Chua Nov 2024

Don’T Just Say “I Don’T Know”! Self-Aligning Large Language Models For Responding To Unknown Questions With Explanations, Yang Deng, Yong Zhao, Moxin Li, See-Kiong Ng, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Despite the remarkable abilities of Large Language Models (LLMs) to answer questions, they often display a considerable level of overconfidence even when the question does not have a definitive answer. To avoid providing hallucinated answers to these unknown questions, existing studies typically investigate approaches to refusing to answer these questions. In this work, we propose a novel and scalable self-alignment method to utilize the LLM itself to enhance its response-ability to different types of unknown questions, being capable of not only refusing to answer but also providing explanation to the unanswerability of unknown questions. Specifically, the Self-Align method first employ …

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Selective Annotation Via Data Allocation: These Data Should Be Triaged To Experts For Annotation Rather Than The Model, Chen Huang, Yang Deng, Wenqiang Lei, Jiancheng Lv, Ido Dagan Nov 2024

Selective Annotation Via Data Allocation: These Data Should Be Triaged To Experts For Annotation Rather Than The Model, Chen Huang, Yang Deng, Wenqiang Lei, Jiancheng Lv, Ido Dagan

Research Collection School Of Computing and Information Systems

To obtain high-quality annotations under limited budget, semi-automatic annotation methods are commonly used, where a portion of the data is annotated by experts and a model is then trained to complete the annotations for the remaining data. However, these methods mainly focus on selecting informative data for expert annotations to improve the model predictive ability (i.e., triage-to-human data), while the rest of the data is indiscriminately assigned to model annotation (i.e., triage-to-model data). This may lead to inefficiencies in budget allocation for annotations, as easy data that the model could accurately annotate may be unnecessarily assigned to the expert, and …

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Beyond Persuasion : Towards Conversational Recommender System With Credible Explanations, Peixin Qin, Chen Huang, Yang Deng, Wenqiang Lei, Tat-Seng Chua Nov 2024

Beyond Persuasion : Towards Conversational Recommender System With Credible Explanations, Peixin Qin, Chen Huang, Yang Deng, Wenqiang Lei, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

With the aid of large language models, current conversational recommender system (CRS) has gaining strong abilities to persuade users to accept recommended items. While these CRSs are highly persuasive, they can mislead users by incorporating incredible information in their explanations, ultimately damaging the long-term trust between users and the CRS. To address this, we propose a simple yet effective method, called PC-CRS, to enhance the credibility of CRS’s explanations during persuasion. It guides the explanation generation through our proposed credibility-aware persuasive strategies and then gradually refines explanations via post-hoc self-reflection. Experimental results demonstrate the efficacy of PC-CRS in promoting persuasive …

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Experience As Source For Anticipation And Planning : Experiential Policy Learning For Target-Driven Recommendation Dialogues, Quang Huy Dao, Yang Deng, Khanh-Huyen Bui, Dung D. Le, Lizi Liao Nov 2024

Experience As Source For Anticipation And Planning : Experiential Policy Learning For Target-Driven Recommendation Dialogues, Quang Huy Dao, Yang Deng, Khanh-Huyen Bui, Dung D. Le, Lizi Liao

Research Collection School Of Computing and Information Systems

Target-driven recommendation dialogues present unique challenges in dialogue management due to the necessity of anticipating user interactions for successful conversations. Current methods face significant limitations: (I) inadequate capabilities for conversation anticipation, (II) computational inefficiencies due to costly simulations, and (III) neglect of valuable past dialogue experiences. To address these limitations, we propose a new framework, Experiential Policy Learning (EPL), for enhancing such dialogues. EPL embodies the principle of Learning From Experience, facilitating anticipation with an experiential scoring function that estimates dialogue state potential using similar past interactions stored in long-term memory. To demonstrate its flexibility, we introduce Tree-structured EPL (T-EPL) …

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A Survey Of Ontology Expansion For Conversational Understanding, Jinggui Liang, Yuxia Wu, Yuan Fang, Hao Fei, Lizi Liao Nov 2024

A Survey Of Ontology Expansion For Conversational Understanding, Jinggui Liang, Yuxia Wu, Yuan Fang, Hao Fei, Lizi Liao

Research Collection School Of Computing and Information Systems

In the rapidly evolving field of conversational AI, Ontology Expansion (OnExp) is crucial for enhancing the adaptability and robustness of conversational agents. Traditional models rely on static, predefined ontologies, limiting their ability to handle new and unforeseen user needs. This survey paper provides a comprehensive review of the state-of-the-art techniques in OnExp for conversational understanding. It categorizes the existing literature into three main areas: (1) New Intent Discovery, (2) New Slot-Value Discovery, and (3) Joint OnExp. By examining the methodologies, benchmarks, and challenges associated with these areas, we highlight several emerging frontiers in OnExp to improve agent performance in real-world …

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Consecutive Batch Model Editing With Hook Layers, Shuaiyi Li, Yang Deng, Deng Cai, Hongyuan Lu, Liang Chen, Wai Lam Nov 2024

Consecutive Batch Model Editing With Hook Layers, Shuaiyi Li, Yang Deng, Deng Cai, Hongyuan Lu, Liang Chen, Wai Lam

Research Collection School Of Computing and Information Systems

As the typical retraining paradigm is unacceptably time- and resource-consuming, researchers are turning to model editing to find an effective way that supports both consecutive and batch scenarios to edit the model behavior directly. Despite all these practical expectations, existing model editing methods fail to realize all of them. Furthermore, the memory demands for such sequential model editing approaches tend to be prohibitive, frequently necessitating an external memory that grows incrementally over time. To cope with these challenges, we propose CoachHooK, a model editing method that simultaneously supports sequential and batch editing. CoachHooK is memory-friendly as it only needs a …

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