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Exploratory Analysis Of Prerequisites To Teaching Early Perspective Taking In Children With Autism Spectrum Disorder, Zoe Painter Nov 2025

Exploratory Analysis Of Prerequisites To Teaching Early Perspective Taking In Children With Autism Spectrum Disorder, Zoe Painter

Honors College Theses

The purpose of the current study was to determine the effectiveness of a behavioral intervention package for improving perspective-taking skills in children with ASD and specifically extend previous research focused on teaching the ability to identify what others are experiencing through their senses. Less complex verbal behaviors hypothesized to be prerequisites to this skill were first assessed systematically in three male children with ASD receiving ABA services in a community-based clinic, and then participants were taught to predict behavior according to the sensory experiences of others (e.g. after observing that a man sees a fly in his drink, responding the …

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A Comparison Of Comparisons: Evidence From An International Comparative Study Of 'Smart Cities', Kevin Ward, Teresa Abbruzzese, Tim Bunnell, Paolo Cardullo, I-Chun Catherine Chang, Byron Miller, Ramon Ribera-Fumaz, Haeran Shin, Zachary Spicer, Orlando Woods Nov 2025

A Comparison Of Comparisons: Evidence From An International Comparative Study Of 'Smart Cities', Kevin Ward, Teresa Abbruzzese, Tim Bunnell, Paolo Cardullo, I-Chun Catherine Chang, Byron Miller, Ramon Ribera-Fumaz, Haeran Shin, Zachary Spicer, Orlando Woods

Research Collection College of Integrative Studies

Every year the list lengthens of cities with some sort of ‘smart city’ public policy. In some, it emerges as the latest in a long line of urban digital and information communication policies. In others, the introduction of the notion of the ‘smart city’ marks a departure from past approaches to public policy. Additionally, the more studies emerge of actual smart city policies, then the less definitional agreement there seems to be. Nevertheless, that we have witnessed in the last two decades the ‘repeated instance’ of smart cities emerging in cities around the world seems incontrovertible. Like so much urban …

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Global Cooling Watch 2025, Omar Abdelaziz, Ray Gluckman, Ian Hamilton, Radhika Khosla, Lily Riahi Nov 2025

Global Cooling Watch 2025, Omar Abdelaziz, Ray Gluckman, Ian Hamilton, Radhika Khosla, Lily Riahi

Research Collection College of Integrative Studies

The second edition of UNEP’s Global Cooling Watch Report takes a deep dive into one of the decade’s most urgent challenges: surging heat, soaring cooling demand, and stark inequalities in access. Produced by the UNEP-led Cool Coalition, the report provides a comprehensive assessment of the rapidly growing global demand for cooling and the need for climate-friendly solutions to the issue. The 2025 report builds on the first Global Cooling Watch (2023), which established the Sustainable Cooling Pathway framework. The new edition deepens analysis of intensifying extreme heat and its effect on cooling demand, improved assessment of passive cooling, and coverage …

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Home And Religion, Emma Alexandra Grimley, Orlando Woods, Lily Kong Nov 2025

Home And Religion, Emma Alexandra Grimley, Orlando Woods, Lily Kong

Research Collection College of Integrative Studies

This chapter explores how religious practices and identities intersect with the home as both a construct and physical locale and surveys the social science literature on religion in/and the home. We argue that the shifting space-times of religious practice reflect and influence the changeable and porous boundaries between public and private space, the home and beyond the home. This influence is shown by reference to three areas of focus: the home as a private space of and for religion; the use of religion to cross social and spatial boundaries of home; and the reconfiguration of the home in religious practice …

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Global Standards And Local Ambitions Across Green Taxonomies: Climate Change Mitigation From The European Union To South Africa, Theodor Florian Cojoianu, Andreas G. F. Hoepner, Ifigeneia Paliampelou, Anh Vu, Dariusz Wojcik Nov 2025

Global Standards And Local Ambitions Across Green Taxonomies: Climate Change Mitigation From The European Union To South Africa, Theodor Florian Cojoianu, Andreas G. F. Hoepner, Ifigeneia Paliampelou, Anh Vu, Dariusz Wojcik

Research Collection College of Integrative Studies

Country-level green finance taxonomy standards have emerged to provide clarity on environmentally-sustainable economic activities to attract investment, protect financial services consumers, and counteract greenwashing. This paper adopts the Global Production and Financial Network (GPFN) approach and analyses factors affecting the climate change mitigation ambition level of the South African Green Finance Taxonomy (RSA GFT) in comparison with the EU taxonomy, which served as a model for South Africa's (RSA) regulators. It accounts for (i) the interplay between EU’s and RSA’s production and financial networks, and (ii) RSA’s willingness to attract European funding for sustainable development. We find that EU private …

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Sustainable Llm Inference For Edge Ai: Evaluating Quantized Llms For Energy Efficiency, Output Accuracy, And Inference Latency, Erik Johanne Husom, Arda Goknil, Merve Astekin, Lwin Khin Shar, Andre Kasen, Sagar Sen, Benedikt Andreas Mithassel, Ahmet Soylu Nov 2025

Sustainable Llm Inference For Edge Ai: Evaluating Quantized Llms For Energy Efficiency, Output Accuracy, And Inference Latency, Erik Johanne Husom, Arda Goknil, Merve Astekin, Lwin Khin Shar, Andre Kasen, Sagar Sen, Benedikt Andreas Mithassel, Ahmet Soylu

Research Collection School Of Computing and Information Systems

Deploying Large Language Models (LLMs) on edge devices presents significant challenges due to computational constraints, memory limitations, inference speed, and energy consumption. Model quantization has emerged as a key technique to enable efficient LLM inference by reducing model size and computational overhead. In this study, we conduct a comprehensive analysis of 28 quantized LLMs from the Ollama library, which applies by default Post-Training Quantization (PTQ) and weight-only quantization techniques, deployed on an edge device (Raspberry Pi 4 with 4GB RAM). We evaluate energy efficiency, inference performance, and output accuracy across multiple quantization levels and task types. Models are benchmarked on …

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The 10-Year Status Of Pediatric Gastroenterologists' Perception Of Their Roles In The Management Of Childhood Obesity., Sara Karjoo, Senthilkumar Sankararaman, Fotini Tania Mitsinikos, Marwa Abu El Haija, Sheela Mahendra, Ayesha Baig, Ruba A. Abdelhadi, Ruben E. Quiros-Tejeira, Timothy Sentongo Nov 2025

The 10-Year Status Of Pediatric Gastroenterologists' Perception Of Their Roles In The Management Of Childhood Obesity., Sara Karjoo, Senthilkumar Sankararaman, Fotini Tania Mitsinikos, Marwa Abu El Haija, Sheela Mahendra, Ayesha Baig, Ruba A. Abdelhadi, Ruben E. Quiros-Tejeira, Timothy Sentongo

Manuscripts, Articles, Book Chapters and Other Papers

In 2013, a survey of NASPGHAN members on their involvement in managing pediatric obesity revealed that most pediatric gastroenterologists viewed their roles as primarily supportive, focusing on the management of obesity-related gastrointestinal comorbidities. This 10-year follow-up survey, which targeted pediatric gastroenterology programs and practices, found similar perceptions, along with an increased interest in learning about obesity pharmacotherapy. Additionally, most programs and practices reported limited access to dedicated dietitians, a lack of funding, and a desire for greater institutional support for multidisciplinary programs addressing obesity. Notably, none of the funded programs cited philanthropy as a source of funding. These findings underscore …

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Recommendations From Multi-Disciplinary Professionals For Survivor-Informed And Comprehensive Care For Human Trafficking Survivors, Christina Tsoi, Timothy B. Smith, Elizabeth Cutrer-Párraga, Devan Clayton, Joshua M. Marshall, Jamila Mastny Nov 2025

Recommendations From Multi-Disciplinary Professionals For Survivor-Informed And Comprehensive Care For Human Trafficking Survivors, Christina Tsoi, Timothy B. Smith, Elizabeth Cutrer-Párraga, Devan Clayton, Joshua M. Marshall, Jamila Mastny

Faculty Publications

Background: Human trafficking affects millions of people worldwide with multiple adverse outcomes including psychopathology. Although research on human trafficking has become abundant in other academic disciplines (e.g., public health, criminology, social work), healthcare research specific to the mental health treatment of survivors remains limited. Objective: The purpose of this study was to gather recommendations from professionals about mental health treatment of trafficking survivors. Method: Semi-structured interviews were conducted with 21 multidisciplinary professionals working with trafficking survivors. Data were analyzed using qualitative content analysis methodology. Results: An overarching theme derived from the data concerned the recommendation to implement trafficking survivor-informed care, …

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Guided Modes Of Helical Waveguides, Jay Gopalakrishnan, Michael Neunteufel Nov 2025

Guided Modes Of Helical Waveguides, Jay Gopalakrishnan, Michael Neunteufel

Mathematics and Statistics Faculty Publications and Presentations

This paper studies guided transverse scalar modes propagating through helically coiled waveguides. Modeling the modes as solutions of the Helmholtz equation within the three-dimensional (3D) waveguide geometry, a propagation ansatz transforms the mode-finding problem into a 3D quadratic eigenproblem. Through an untwisting map, the problem is shown to be equivalent to a 3D quadratic eigenproblem on a straightened configuration. Next, exploiting the constant torsion and curvature of the Frenet frame of a circular helix, the 3D eigenproblem is further reduced to a two-dimensional (2D) eigenproblem on the waveguide cross section. All three eigenproblems are numerically treated. As expected, significant computational …

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Final Draft Report - Mapping Pfas In Groundwater Of The West Plains, Spokane County, Washington, 2023-2025, Chad Pritchard Nov 2025

Final Draft Report - Mapping Pfas In Groundwater Of The West Plains, Spokane County, Washington, 2023-2025, Chad Pritchard

EWU PFAS Research Collection

Since 2017, per- and polyfluoroalkyl substances (PFAS) have been detected in West Plains groundwater. Sampling conducted by Fairchild Air Force Base (FAFB) and the Environmental Protection Agency (EPA) have measured PFAS concentrations in private wells that exceed drinking water standards. Two known sources of PFAS have been identified on the West Plains: FAFB and Spokane International Airport (SIA). Washington Department of Ecology (Ecology) awarded the City of Medical Lake an area-wide groundwater grant to develop a groundwater model of PFAS contamination in the West Plains, the grant was originally written by Eastern Washington University (EWU) and Spokane County Water Resources …

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Faculty Touchpoint Survey 2025: Key Findings And Recommendations, Lisa A. Marchiondo, Naila V. Decruz-Dixon, Julia Fulghum Nov 2025

Faculty Touchpoint Survey 2025: Key Findings And Recommendations, Lisa A. Marchiondo, Naila V. Decruz-Dixon, Julia Fulghum

ADVANCE Reports

A Spring 2025 climate survey finds that UNM faculty remain committed to their teaching, scholarship, and collegial relationships, despite concerns about research funding, academic freedom, and graduate student recruitment and well-being. The survey also found that faculty have higher levels of stress than in a previous ADVANCE survey, worse psychological well-being, more difficulty concentrating, and more concern about tenure and promotion. A set of recommendations for academic leaders are provided.

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Driving And Beyond, Michele Dinman, Nancy Morrow-Howell Nov 2025

Driving And Beyond, Michele Dinman, Nancy Morrow-Howell

Harvey A. Friedman Center for Aging

Transportation is a daily necessity in our lives, and many of us rely on driving our own automobile to get where we need to go. According to the Federal Highway Administration, in 2023 there were approximately 35 million licensed drivers aged 70 and older—fewer drivers than younger age groups and a group that drives fewer miles.

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The Covid-19 Pandemic’S Effects On Older People, Michele Dinman, Morgan Van Vleck Nov 2025

The Covid-19 Pandemic’S Effects On Older People, Michele Dinman, Morgan Van Vleck

Harvey A. Friedman Center for Aging

The COVID-19 pandemic has had wide ranging effects on people of all ages. In many respects, older people had the same experiences as younger people, but there were some aspects of the pandemic unique to the older population. While COVID-19 cases have been equal among different age groups, older people experienced a greater number of hospitalizations and deaths compared to younger people.

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Enhancing Spatial Understanding In Mixed-Reality Presentations, Nam-Dang Vo, Van-Vinh Thai, Nam-Hoi Do, Viet-Tham Huynh, Anthony Tang, Khan-Duy Le Nov 2025

Enhancing Spatial Understanding In Mixed-Reality Presentations, Nam-Dang Vo, Van-Vinh Thai, Nam-Hoi Do, Viet-Tham Huynh, Anthony Tang, Khan-Duy Le

Research Collection School Of Computing and Information Systems

Mixed reality (MR) presentations often involve a presenter wearing a head-mounted display (HMD) and an audience watching via a large display, making it difficult for audiences to perceive spatial relationships between the presenter and virtual objects. We report two experiments testing three design variations: (1) scene camera placement (audience-aligned vs. opposite), (2) overlaying the presenter’s first-person view, and (3) highlighting objects in the presenter’s view. Results show that audience-aligned cameras and object highlighting improve spatial understanding, while combining third- and first-person views can further aid perception. We derive design guidelines for configuring MR presentations to better support audience comprehension.

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Metacan: Improving Generalizability Of Few‑Shot Anomaly Detection With Meta‑Learning, Zhisheng Lv, Jianfeng Zhang, Songlei Jian, Chenlin Huang, Hongguang Zhang, Guansong Pang, Zhong Liu Nov 2025

Metacan: Improving Generalizability Of Few‑Shot Anomaly Detection With Meta‑Learning, Zhisheng Lv, Jianfeng Zhang, Songlei Jian, Chenlin Huang, Hongguang Zhang, Guansong Pang, Zhong Liu

Research Collection School Of Computing and Information Systems

Few-shot Anomaly Detection (AD) for images aims to detect anomalies with few-shot normal samples from the target dataset. It is a crucial task when only few samples can be obtained, and it is challenging since it needs to be generalized to different domains. Existing methods try to enhance the generalizability of AD by incorporating large vision-language models (LVLMs).However, how to transform category semantic information in LVLMs into anomaly information to improve the generalizability of AD remains a challenge facing existing methods.To address the challenge, we propose a few-shot AD method called MetaCAN, a novel category-to-anomaly network trained with AD meta-learning …

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International Workshop On Multimodal Generative Search And Recommendation (Mmgensr@Cikm 2025), Yi Bin, Haoxuan Li, Haokai Ma, Yang Zhang, Wenjie Wang, Yunshan Ma, Yang Yang, Tat‑Seng Chua Nov 2025

International Workshop On Multimodal Generative Search And Recommendation (Mmgensr@Cikm 2025), Yi Bin, Haoxuan Li, Haokai Ma, Yang Zhang, Wenjie Wang, Yunshan Ma, Yang Yang, Tat‑Seng Chua

Research Collection School Of Computing and Information Systems

Recent breakthroughs in generative Artificial Intelligence (AI) have ignited a revolutionary wave across information retrieval and recommender systems. This workshop serves as a premier interdisciplinary platform to explore how generative models, particularly Large Language Models (LLMs) and Large Multimodal Models (LMMs), are transforming multimodal search and recommendation paradigms [3, 6, 9, 10, 12-14]. We aim to convene researchers and practitioners to discuss innovative architectures, methodologies, and evaluation strategies spanning generative document retrieval [5, 8] generative image retrieval [ 7, 16], grounded answer generation [17], generative recommendation [2, 4, 11], and related tasks involving multiple modalities [1,15]. The workshop will facilitate …

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Instructors’ Strategies In Creating And Implementing Constructivist Llm-Based Learning Activities, Emily Aurelia, Shun Yi Yeo, Michelle Lui, Effie Lai-Chong Law, Anthony Tang Nov 2025

Instructors’ Strategies In Creating And Implementing Constructivist Llm-Based Learning Activities, Emily Aurelia, Shun Yi Yeo, Michelle Lui, Effie Lai-Chong Law, Anthony Tang

Research Collection School Of Computing and Information Systems

Large language models (LLMs) are increasingly being integrated into educational settings, enabling more adoption of constructivist teaching and learning approaches in classrooms. This paper explores the strategies instructors are currently using to incorporate LLMs into learning activities that align with constructivist principles, which emphasize that learners actively construct their own knowledge. Through interviews with nine instructors who have designed eleven distinct LLM-based activities and using reflexive thematic analysis, this study identifies various types of learning activities with respect to four different aspects of the constructivist learning theory. The strategies employed and challenges faced to foster constructivist student-LLM interaction were also …

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Itrusst Consensus On Biophysical Safety For Transcranial Ultrasound Stimulation, Jean François Aubry, David Attali, Mark E. Schafer, Elsa Fouragnan, Charles F. Caskey, Robert Chen, Ghazaleh Darmani, Ellen J. Bubrick, Jérôme Sallet, Christopher R. Butler, Charlotte J. Stagg, Miriam C. Klein-Flügge, Seung Schik Yoo, Christy K. Holland, Bradley Treeby, Eleanor Martin, Lennart Verhagen, Kim Butts Pauly Nov 2025

Itrusst Consensus On Biophysical Safety For Transcranial Ultrasound Stimulation, Jean François Aubry, David Attali, Mark E. Schafer, Elsa Fouragnan, Charles F. Caskey, Robert Chen, Ghazaleh Darmani, Ellen J. Bubrick, Jérôme Sallet, Christopher R. Butler, Charlotte J. Stagg, Miriam C. Klein-Flügge, Seung Schik Yoo, Christy K. Holland, Bradley Treeby, Eleanor Martin, Lennart Verhagen, Kim Butts Pauly

School of Psychology

Transcranial ultrasound stimulation (TUS) is an emerging technology for non-invasive brain stimulation. The International Transcranial Ultrasonic Stimulation Safety and Standards consortium (ITRUSST) has established consensus on considerations for nonsignificant biophysical risk of TUS, drawing upon the literature and established regulations for biomedical devices. Here, we assume the application of TUS to individuals without contraindications, compromised thermoregulation, vascular vulnerabilities, or administered ultrasound contrast agents. In this context, we present a concise yet comprehensive set of levels for nonsignificant risks of TUS application. For mechanical effects, it is non-significant risk if the mechanical index (MI) or the mechanical index for transcranial application …

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Neutrosophic Inference Systems Using Takagi-Sugeno-Kang Model And Its Application, Irfan Deli, Vakkas Ulucay, Zeynep Baser Nov 2025

Neutrosophic Inference Systems Using Takagi-Sugeno-Kang Model And Its Application, Irfan Deli, Vakkas Ulucay, Zeynep Baser

Neutrosophic Sets and Systems

No abstract provided.

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A Certain Algebraic Structure Of Bipolar Single Value Neutrosophic Subgroups And Its Essential Properties, Yousef Al-Qudah, Abdullah Alsoboh, Eman Hussein, Faisal Al-Sharqi, Abdullrahman A. Al Maqbali Nov 2025

A Certain Algebraic Structure Of Bipolar Single Value Neutrosophic Subgroups And Its Essential Properties, Yousef Al-Qudah, Abdullah Alsoboh, Eman Hussein, Faisal Al-Sharqi, Abdullrahman A. Al Maqbali

Neutrosophic Sets and Systems

No abstract provided.

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Mmlu-Prox: A Multilingual Benchmark For Advanced Large Language Model Evaluation, Weihao Xuan, Et. Al. Nov 2025

Mmlu-Prox: A Multilingual Benchmark For Advanced Large Language Model Evaluation, Weihao Xuan, Et. Al.

Research Collection School Of Computing and Information Systems

Existing large language model (LLM) evaluation benchmarks primarily focus on English, while current multilingual tasks lack parallel questions that specifically assess cross-lingual reasoning abilities. This dual limitation makes it challenging to assess LLMs’ performance in the multilingual setting comprehensively. To fill this gap, we introduce MMLU-ProX, a comprehensive benchmark covering 29 languages, built on an English benchmark. Each language version consists of 11,829 identical questions, enabling direct cross-lingual comparisons. Additionally, to meet efficient evaluation needs, we provide a lite version containing 658 questions per language. To ensure the high quality of MMLU-ProX, we employ a rigorous development process that involves …

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From Personas To Talks: Revisiting The Impact Of Personas On Llm-Synthesized Emotional Support Conversations, Shenghan Wu, Yimo Zhu, Wynne Hsu, Mong-Li Lee, Yang Deng Nov 2025

From Personas To Talks: Revisiting The Impact Of Personas On Llm-Synthesized Emotional Support Conversations, Shenghan Wu, Yimo Zhu, Wynne Hsu, Mong-Li Lee, Yang Deng

Research Collection School Of Computing and Information Systems

The rapid advancement of Large Language Models (LLMs) has revolutionized the generation of emotional support conversations (ESC), offering scalable solutions with reduced costs and enhanced data privacy. This paper explores the role of personas in the creation of ESC by LLMs. Our research utilizes established psychological frameworks to measure and infuse persona traits into LLMs, which then generate dialogues in the emotional support scenario. We conduct extensive evaluations to understand the stability of persona traits in dialogues, examining shifts in traits post-generation and their impact on dialogue quality and strategy distribution. Experimental results reveal several notable findings: 1) LLMs can …

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Exploring Autonomous Agents: A Closer Look At Why They Fail When Completing Tasks, Ruofan Lu, Yichen Li, Yintong Huo Nov 2025

Exploring Autonomous Agents: A Closer Look At Why They Fail When Completing Tasks, Ruofan Lu, Yichen Li, Yintong Huo

Research Collection School Of Computing and Information Systems

Autonomous agent systems powered by Large Language Models (LLMs) have demonstrated promising capabilities in automating complex tasks. However, current evaluations largely rely on success rates without systematically analyzing the interactions, communication mechanisms, and failure causes within these systems. To bridge this gap, we present a benchmark of 34 representative programmable tasks designed to rigorously assess autonomous agents. Using this benchmark, we evaluate three popular open-source agent frameworks combined with two LLM backbones, observing a task completion rate of approximately 50%. Through in-depth failure analysis, we develop a three-tier taxonomy of failure causes aligned with task phases, highlighting planning errors, task …

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Envisioning Future Interactive Web Development: Editing Webpage With Natural Language, Truong Hai Dang, Jingyu Xiao, Yintong Huo Nov 2025

Envisioning Future Interactive Web Development: Editing Webpage With Natural Language, Truong Hai Dang, Jingyu Xiao, Yintong Huo

Research Collection School Of Computing and Information Systems

The evolution of web applications relies on iterative code modifications, a process that is traditionally manual and time-consuming. While Large Language Models (LLMs) can generate UI code, their ability to edit existing code from new design requirements (e.g., ”center the logo”) remains a challenge. This is largely due to the absence of large-scale, high-quality tuning data to align model performance with human expectations. In this paper, we introduce a novel, automated data generation pipeline that uses LLMs to synthesize a high-quality fine-tuning dataset for web editing, named Instruct4Edit. Our approach generates diverse instructions, applies the corresponding code modifications, and performs …

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Interaction2code: Benchmarking Mllm-Based Interactive Webpage Code Generation From Interactive Prototyping, Jingyu Xiao, Yuxuan Wan, Yintong Huo, Zixin Wang, Xinyi Xu, Wenxuan Wang, Zhiyao Xu, Yuhang Wang, Michael R. Lyu Nov 2025

Interaction2code: Benchmarking Mllm-Based Interactive Webpage Code Generation From Interactive Prototyping, Jingyu Xiao, Yuxuan Wan, Yintong Huo, Zixin Wang, Xinyi Xu, Wenxuan Wang, Zhiyao Xu, Yuhang Wang, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Multimodal Large Language Models (MLLMs) have demonstrated remarkable performance on the design-to-code task, i.e., generating UI code from UI mock-ups. However, existing benchmarks only contain static web pages for evaluation and ignore the dynamic interaction, limiting the practicality, usability and user engagement of the generated webpages. To bridge these gaps, we present the first systematic investigation of MLLMs in generating interactive webpages. Specifically, we formulate the Interaction-to-Code task and establish the Interaction2Code benchmark, encompassing 127 unique webpages and 374 distinct interactions across 15 webpage types and 31 interaction categories. Through comprehensive experiments utilizing state-of-theart (SOTA) MLLMs, evaluated via both automatic …

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Intentionframe: A Semi-Structured, Multi-Aspect Framework For Fine-Grained Conversational Intention Understanding, Zailong Tian, Zhuoheng Han, Lizi Liao, Lizi Liao Nov 2025

Intentionframe: A Semi-Structured, Multi-Aspect Framework For Fine-Grained Conversational Intention Understanding, Zailong Tian, Zhuoheng Han, Lizi Liao, Lizi Liao

Research Collection School Of Computing and Information Systems

Understanding user intentions in multi-turn dialogues is critical for conversational AI, yet existing approaches—relying on rigid slot-value structures or unstructured free-text—fail to fully capture conversational complexity. In this paper, we propose IntentionFrame, a semi-structured framework inspired by psychological and cognitive intention theories, which organizes conversational intents into four interrelated aspects: situation, emotion, action, and knowledge. This design not only retains interpretability but also provides LLMs with a rich context to accurately parse and respond to nuanced user inputs. To efficiently scale IntentionFrame annotations, we introduce a Weakly-supervised Reinforced Generation (WeRG) method that leverages a small set of high-quality human annotations …

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One Planner To Guide Them All! Learning Adaptive Conversational Planners For Goal-Oriented Dialogues, Huy Dao, Lizi Liao Nov 2025

One Planner To Guide Them All! Learning Adaptive Conversational Planners For Goal-Oriented Dialogues, Huy Dao, Lizi Liao

Research Collection School Of Computing and Information Systems

Goal-oriented dialogues, such as recommendation and negotiation, often require balancing multiple, conflicting objectives. Existing methods typically involve training separate models for specific combinations of objectives, leading to computational and scalability issues. In this work, we aim to develop a new dialogue policy method that can adapt to varying objective preferences at inference time without retraining. This raises several challenges in terms of both (1) optimization strategy and (2) knowledge utilization. To address these, we propose a novel learning framework, Preference Adaptive Dialogue Policy Planner (PADPP), for multi-objective goal-oriented dialogues. Specifically, to tackle the former, we introduce a novel policy optimization …

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Context-Aware Hierarchical Taxonomy Generation For Scientific Papers Via Llm-Guided Multi-Aspect Clustering, Kun Zhu, Lizi Liao, Yuxuan Gu, Lei Huang, Xiaocheng Feng, Bing Qin Nov 2025

Context-Aware Hierarchical Taxonomy Generation For Scientific Papers Via Llm-Guided Multi-Aspect Clustering, Kun Zhu, Lizi Liao, Yuxuan Gu, Lei Huang, Xiaocheng Feng, Bing Qin

Research Collection School Of Computing and Information Systems

The rapid growth of scientific literature demands efficient methods to organize and synthesize research findings. Existing taxonomy construction methods, leveraging unsupervised clustering or direct prompting of large language models (LLMs), often lack coherence and granularity. We propose a novel context-aware hierarchical taxonomy generation framework that integrates LLM-guided multi-aspect encoding with dynamic clustering. Our method leverages LLMs to identify key aspects of each paper (e.g., methodology, dataset, evaluation) and generates aspect-specific paper summaries, which are then encoded and clustered along each aspect to form a coherent hierarchy. In addition, we introduce a new evaluation benchmark of 156 expert-crafted taxonomies encompassing 11.6k …

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Why Stop At One Error? Benchmarking Llms As Data Science Code Debuggers For Multi-Hop And Multi-Bug Errors, Zhiyu Yang, Shuo Wang, Yukun Yan, Yang Deng Nov 2025

Why Stop At One Error? Benchmarking Llms As Data Science Code Debuggers For Multi-Hop And Multi-Bug Errors, Zhiyu Yang, Shuo Wang, Yukun Yan, Yang Deng

Research Collection School Of Computing and Information Systems

LLMs are transforming software development, yet current code generation and code repair benchmarks mainly assess syntactic and functional correctness in simple, single-error cases. LLMs’ capabilities to autonomously find and fix runtime logical errors in complex data science code remain largely unexplored. To address this gap, we introduce DSDBench: the Data Science Debugging Benchmark, the first benchmark for systematic evaluation of LLMs on multi-hop error tracing and multi-bug detection in data science code debugging. DSDBench adapts datasets from existing data science task benchmarks, such as DABench and MatPlotBench, featuring realistic data science debugging tasks with automatically synthesized multi-hop, multi-bug code snippets. …

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The Ai-Powered Learning Loop In Higher Education, Oualid Abidi, Vladimir Dzenopoljac, Aleksandra Dzenopoljac Nov 2025

The Ai-Powered Learning Loop In Higher Education, Oualid Abidi, Vladimir Dzenopoljac, Aleksandra Dzenopoljac

All Works

Purpose – This study examines how generative AI tools affect business students’ academic performance by investigating whether flexible AI policies promote deeper learning, enhance self-efficacy and facilitate tacit knowledge acquisition in a Middle Eastern context, while ensuring efficiency and academic integrity. Design/methodology/approach – A qualitative, exploratory study observed 20 final-year business students in Kuwait during five in-class activities using generative AI tools. Semi-structured interviews complemented the researcher’s observations. Thematic analysis revealed patterns in benefits, challenges and learning processes, leading to the development of the AI-powered learning loop framework to explain academic performance outcomes. Findings – The study indicates that generative …

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