Plugging Small Models in Large Language Models for POI Recommendation in Smart Tourism by Hong Zheng, Zhenhui Xu, Qihong Pan, Zhenzhen Zhao, Xiangjie Kong

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Advancing AI in Higher Education: A Comparative Study of Large Language Model-Based Agents for Exam Question Generation, Improvement, and Evaluation by Vlatko Nikolovski, Dimitar Trajanov, Ivan Chorbev

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Integrating Large Language Models and Optimization in Semi- Structured Decision Making: Methodology and a Case Study by Gianpaolo Ghiani, Gianluca Solazzo, Gianluca Elia

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Comparative Analysis of BERT and GPT for Classifying Crisis News with Sudan Conflict as an Example by Yahya Masri, Zifu Wang, Anusha Srirenganathan Malarvizhi, Samir Ahmed, Tayven Stover, David W. S. Wong, Yongyao Jiang, Yun Li, Qian Liu, Mathieu Bere, Daniel Rothbart, Dieter Pfoser, Chaowei Yang

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Enhanced Viral Genome Classification Using Large Language Models by Hemalatha Gunasekaran, Nesaian Reginal Wilfred Blessing, Umar Sathic, Mohammad Shahid Husain

“…Among these are traditional algorithms such as Random Forest (RF), K-nearest neighbors (KNNs), Decision Tree (DT), and Naive Bayes (NB), each offering unique advantages in handling genetic data. …”
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An Industry Application of Secure Augmentation and Gen-AI for Transforming Engineering Design and Manufacturing by Dulana Rupanetti, Corissa Uberecken, Adam King, Hassan Salamy, Cheol-Hong Min, Samantha Schmidgall

“…This paper explores the integration of Large Language Models (LLMs) and secure Gen-AI technologies within engineering design and manufacturing, with a focus on improving inventory management, component selection, and recommendation workflows. …”
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A Data-Driven Intelligent Methodology for Developing Explainable Diagnostic Model for Febrile Diseases by Constance Amannah, Kingsley Friday Attai, Faith-Michael Uzoka

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RU-OLD: A Comprehensive Analysis of Offensive Language Detection in Roman Urdu Using Hybrid Machine Learning, Deep Learning, and Transformer Models by Muhammad Zain, Nisar Hussain, Amna Qasim, Gull Mehak, Fiaz Ahmad, Grigori Sidorov, Alexander Gelbukh

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Text-Guided Synthesis in Medical Multimedia Retrieval: A Framework for Enhanced Colonoscopy Image Classification and Segmentation by Ojonugwa Oluwafemi Ejiga Peter, Opeyemi Taiwo Adeniran, Adetokunbo MacGregor John-Otumu, Fahmi Khalifa, Md Mahmudur Rahman

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Application of Multichannel Active Vibration Control in a Multistage Gear Transmission System by Feng Zhang, Weihao Sun, Chao Liu, Hongchao Xiao, Yong Zhang

“…A piezoelectric actuator is installed on an additional gear shaft to form an active structure and equipped with a signal acquisition system and a control system; the proposed variable-step-size multichannel FxLMS algorithm is experimentally verified. The experimental results show that the proposed multichannel variable-step-size FxLMS algorithm has more accurate convergence accuracy than the traditional FxLMS algorithm, and the convergence accuracy can be increased up to 123%.…”
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Evaluating language model embeddings for Parkinson’s disease cohort harmonization using a novel manually curated variable mapping schema by Yasamin Salimi, Tim Adams, Mehmet Can Ay, Helena Balabin, Marc Jacobs, Martin Hofmann-Apitius

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Evaluation of Different Sensor Systems for Classifying the Behavior of Dairy Cows on Pasture by Barbara Pichlbauer, Jose Maria Chapa Gonzalez, Martin Bobal, Christian Guse, Michael Iwersen, Marc Drillich

“…We recommend using a correction algorithm for 1 min NB data. For the measurement of lying time, the LMs significantly outperformed the ET.…”
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An Experimental Assessment of Transverse Adaptive Fir Filters as Applied to Vibrating Structures Identification by Daniel A. Castello, Fernando A. Rochinha

“…The present work is aimed at assessing the performance of adaptive Finite Impulse Response (FIR) filters on the identification of vibrating structures. Four adaptive algorithms were used: Least Mean Squares (LMS), Normalized Least Mean Squares (NLMS), Transform-Domain Least Mean Squares (TD – LMS) and Set-Membership Binormalized Data-Reusing LMS Algorithm (SM – BNDRLMS). …”
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Code Generation for Collectible Card Games with Complex APIs by John Licato, Logan Fields, Brayden Hollis

“…Given these practical limitations, is it possible to utilize these massive code-generation LMs to write code compatible with a given API? We develop an algorithm that selects code examples using a smaller LM trained to predict which features of an API are likely to be used in the resulting code, which is a simpler problem than actually generating the code. …”
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Mitigating spatial hallucination in large language models for path planning via prompt engineering by Hongjie Zhang, Hourui Deng, Jie Ou, Chaosheng Feng

“…To address this, we propose S2ERS, an LLM-based technique that integrates entity and relation extraction with the on-policy reinforcement learning algorithm Sarsa for optimal path planning. We introduce three key improvements: (1) To tackle the hallucination of spatial, we extract a graph structure of entities and relations from the text-based maze description, aiding LLMs in accurately comprehending spatial relationships. (2) To prevent LLMs from getting trapped in dead ends due to context inconsistency hallucination by long-term reasoning, we insert the state-action value function Q into the prompts, guiding the LLM’s path planning. (3) To reduce the token consumption of LLMs, we utilize multi-step reasoning, dynamically inserting local Q-tables into the prompt to assist the LLM in outputting multiple steps of actions at once. …”
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The use of a convolutional neural network to automate radiologic scoring of computed tomography of paranasal sinuses by Daniel J. Lee, Mohammad Hamghalam, Lily Wang, Hui-Ming Lin, Errol Colak, Muhammad Mamdani, Amber L. Simpson, John M. Lee

“…This proof-of-concept study aimed to develop an automated algorithm combining a convolutional neural network (CNN) for sinus segmentation with post-processing to compute LMS directly from CT scans. …”
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On convergence and stability of adaptive active noise control systems by M. Pawełczyk

“…The problems of convergence and stability of adaptive active noise control systems with the Filtered-Reference LMS algorithm are discussed. First, the assumptions required to derive convergence conditions are collected and addressed. …”
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A Stochastic Total Least Squares Solution of Adaptive Filtering Problem by Shazia Javed, Noor Atinah Ahmad

“…The TLMS algorithm is computationally simpler than the other TLS algorithms and demonstrates a better performance as compared with the least mean square (LMS) and normalized least mean square (NLMS) algorithms. …”
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Can Language Models Improve the Performance of SVD-based Recommender Systems? by Aaron Goldstein, Ayan Dutta

“… Traditional recommendation algorithms cannot provide personalized recommendations based on user preferences provided through text, e.g., “I like movies which take me into a dreamland”. …”
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Active Noise Control Using a Fuzzy Inference System Without Secondary Path Modelling by Sebastian KURCZYK, Marek PAWELCZYK

“…For many adaptive noise control systems the Filtered-Reference LMS, known as the FXLMS algorithm is used to update parameters of the control filter. …”
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