Towards Machine Learning Interpretability for Tabular Data with Mixed Data Types by Prativa Pokhrel, Alina Lazar

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Balancing Innovation and Tradition: Real-Time, Interactive Learning with LightRAG and Dual-Factor PageRank by Sirisha Velampalli

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Missing Mechanisms of Manipulation in the EU AI Act by Matija Franklin, Hal Ashton, Rebecca Gorman, Stuart Armstrong

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Semi-supervised Learning of Visual Causal Macrovariables by Aruna Jammalamadaka, Lingyi Zhang, Joseph Comer, Sasha Strelnikoff, Ryan Mustari, Tsai-Ching Lu, Rajan Bhattacharyya

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Measuring Outcomes in Healthcare Economics using Artificial Intelligence: with Application to Resource Allocation by Feras A. Batarseh, Chih-Hao Huang

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Training Reinforcement Learning Agents to React to an Ambush for Military Simulations by Timothy Aris, Volkan Ustun, Rajay Kumar

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Improving Word Embedding Using Variational Dropout by Zainab Albujasim, Diana Inkpen, Xuejun Han, Yuhong Guo

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Embedding Ethics Into Artificial Intelligence: Understanding What Can Be Done, What Can't, and What Is Done by Clayton Peterson

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Medical Specialty Classification Using Large Language Models (LLMs) by Surya Kathirvel, Lenin Mookiah

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Visualization of Anomalies using Graph-Based Anomaly Detection by Ramesh Paudel, Lauren Tharp, Dulce Kaiser, William Eberle, Gerald Gannod

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How to Ask the ‘Right’ Questions about Artificial Intelligence in Social Sciences? Human-Centered AI as a Problem and as a Solution by Andrey Rezaev

“…Further, we claim that HCAI is a united idea for the AI community, including social scientists who study machines and algorithms in society. In conclusion, we summarize our argument on why Woolgar’s question is ‘wrong’ and what the ‘right’ questions are for AI research. …”
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TradeWise: Towards Context-Aware Stock Market Predictions with Sentiment and Political Insights by Andreas Marpaung, David Masterson

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Uncertainty of Counterfactuals in Deep Learning by Katherine Elizabeth Brown, Doug Talbert, Steve Talbert

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Improving Reinforcement Learning Experiments in Unity through Waypoint Utilization by Caleb Koresh, Volkan Ustun, Rajay Kumar, Tim Aris

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Challenges of Vehicle Classification Using Acoustics by Raiden Evans, Stephanie Mullins, George Noel

“…Vehicles produce complex sounds from many sources, sound signatures vary between similar vehicles, and background noise has a large impact on audio data. Past research studied different vehicle classification techniques but often relied on datasets with little variation in vehicle model, environmental conditions, or microphones. …”
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Interpreting Predictive Models through Causality: A Query-Driven Methodology by Mahdi Hadj Ali, Yann Le Biannic, Pierre-Henri Wuillemin

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Investigating Lexical and Syntactic Differences in Written and Spoken English Corpora by Mina Rajaei Moghadam, Mosab Rezaei, Miguel Williams, Gülşat Aygen, Reva Freedman

“…The research focuses on syntactic and lexical differences in written books and transcriptions of speeches by United States presidents. …”
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Classifying the Emotional Polarity of Digital Communications Using Large Language Models by Vincent Qin

“… Large Language Models (LLMs) employ deep learning algorithms to generalize patterns in data. Applying these LLMs to classification tasks can reduce the required labor and time. …”
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Towards a multi-modal Deep Learning Architecture for User Modeling by Ange Tato, Roger Nkambou

“…However, there needs to be more research on its use in Intelligent Tutoring Systems or Serious Games, particularly in modeling user behavior during learning or gaming sessions using multi-modal data. …”
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A Comparative Study of Continual, Lifelong, and Online Supervised Learning Libraries by Nicholas Cummins, Brad Killen, Somayeh Bakhtiari Ramezani, Shahram Rahimi, Maria Seale, Sudip Mittal

“…We compare them on the axes of developmental experience and benchmark testing as researchers. Our comparison as developers takes maintenance, documentation, and offerings of state-of-the-art algorithms into account. …”
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