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<title>Channels - Leveraging large language models for document classification in the banking sector :: FRELIP Discovery
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Exploratory analysis of logical and intuitive reasoning in large language models
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Biomedical text summarization with large language models: methodologies, challenges, and future directions
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PPA++: Preference Prototype-Aware Learning with Large Language Model for Universal Cross-Domain Recommendation
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Enhancing large language models for scientific entity recognition via fully automated self-distillation
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CDGRS-LOD model: leveraging linked open data in collaborative cross-domain group recommender system
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Large language models for generative recommendation: a systematic review of data-centric taxonomy, evaluation, and human-centric analytics
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A hybrid method for biomedical long-document summarization using an ensemble extraction approach and a transformer-based model
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A Kendall’s rank correlation coefficient-based decision tree for monotonic classification problem
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A continuous, bounded and uniformly converging -normalization approach for improved classification accuracy and feature entropy
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A systematic review of plant leaf disease detection and classification using machine learning and deep learning techniques
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Explainability and uncertainty for time-series classification in cryptocurrency data: a hybrid XAI methodology based on COMTE and LEFTIST
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RG-Hybrid: pure late fusion of RoBERTa and a graph transformer for robust, interpretable sentiment classification
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Current English–Chinese legal language mutual translation based on the comparison of the three theoretical levels of words, sentences, and articles
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A multi-channel sarcasm detection model integrating syntax and semantics
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Arabic word sense disambiguation: a survey in the era of transformer-based models
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Evaluation of Estimation Methods for Simultaneous Equations Models Across Varying Levels of Data Variability
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Limit Order Book Event Stream Prediction with Diffusion Model
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Evaluating Regulatory Compliance in Maturity Models for Patient-Centred Health Data Sharing: A Literature Review
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Fusion of pre-trained model features with style-aware attention for enhanced content-based recommendation system
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F2Fnet: alleviating spectral confusion in time series forecasting via dual Fourier modeling
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Data-driven analysis and prediction of traffic accident dynamics using spatiotemporal modeling and optimized machine learning techniques
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SentiVol-GA: a volatility-scaled genetic fusion of predictive models and financial sentiment for adaptive stock forecasting
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Hybrid recommendation framework: integrating behavioral clustering, network centrality, and advanced deep learning models
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Retrieval-Augmented Generation for AI-Generated Content: A Survey
