Digital transformation
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Program Skeletons for Automated Program Translation
Source: arXiv AI PapersRead more: Program Skeletons for Automated Program TranslationA new method for translating software between programming languages has been proposed using program skeletons. This approach aims to automate…
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A Dynamic Fusion Model for Consistent Crisis Response
Source: arXiv AI PapersRead more: A Dynamic Fusion Model for Consistent Crisis ResponseA new approach to crisis communication effectively utilizes automated language models while ensuring stylistic consistency. This method addresses a significant…
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Speaking at the Right Level: Literacy-Controlled Counterspeech Generation with RAG-RL
Source: arXiv AI PapersRead more: Speaking at the Right Level: Literacy-Controlled Counterspeech Generation with RAG-RLA new framework, Controlled-Literacy, addresses health misinformation by tailoring counterspeech to different health literacy levels. This approach uses retrieval-augmented generation…
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Momentum-integrated Multi-task Stock Recommendation with Converge-based Optimization
Source: arXiv AI PapersRead more: Momentum-integrated Multi-task Stock Recommendation with Converge-based OptimizationThis study presents a novel framework for stock recommendation using Multi-Task Learning. The proposed MiM-StocR model integrates momentum indicators and…
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Learning Decomposed Contextual Token Representations from Pretrained and Collaborative Signals for Generative Recommendation
Source: arXiv AI PapersRead more: Learning Decomposed Contextual Token Representations from Pretrained and Collaborative Signals for Generative RecommendationThe study introduces DECOR, a new framework for generative recommenders that enhances token adaptability while preserving pretrained semantics. Experiments show…
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SABR: A Stable Adaptive Bitrate Framework Using Behavior Cloning Pretraining and Reinforcement Learning Fine-Tuning
Source: arXiv AI PapersRead more: SABR: A Stable Adaptive Bitrate Framework Using Behavior Cloning Pretraining and Reinforcement Learning Fine-TuningThe SABR framework combines behavior cloning pretraining with reinforcement learning fine-tuning to improve adaptive bitrate control in video streaming. This…
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Distributed Gossip-GAN for Low-overhead CSI Feedback Training in FDD mMIMO-OFDM Systems
Source: arXiv AI PapersRead more: Distributed Gossip-GAN for Low-overhead CSI Feedback Training in FDD mMIMO-OFDM SystemsThe proposed Gossip-GAN framework efficiently reduces the overhead in channel state information (CSI) feedback for massive MIMO systems. It leverages…
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Online Learning Based Efficient Resource Allocation for LoRaWAN Network
Source: arXiv AI PapersRead more: Online Learning Based Efficient Resource Allocation for LoRaWAN NetworkThis research presents two online learning-based frameworks, D-LoRa and CD-LoRa, for optimizing Packet Delivery Ratio and Energy Efficiency in LoRaWAN…
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Towards Scalable O-RAN Resource Management: Graph-Augmented Proximal Policy Optimization
Source: arXiv AI PapersRead more: Towards Scalable O-RAN Resource Management: Graph-Augmented Proximal Policy OptimizationA new framework, GPPO, has been developed to optimize resource management in Open Radio Access Networks. This approach leverages Graph…
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From Noise to Precision: A Diffusion-Driven Approach to Zero-Inflated Precipitation Prediction
Source: arXiv AI PapersRead more: From Noise to Precision: A Diffusion-Driven Approach to Zero-Inflated Precipitation PredictionThe Zero Inflation Diffusion Framework (ZIDF) addresses challenges in precipitation forecasting caused by zero-inflated data. It combines Gaussian perturbation, Transformer-based…