Mitigating Knowledge Conflicts in Language Model-Driven Question Answering

H Cao, Z Zhang, X Li, C Wu, H Zhang… - arXiv preprint arXiv …, 2024 - arxiv.org
Knowledge-aware sequence to sequence generation tasks such as document question
answering and abstract summarization typically requires two types of knowledge: encoded …

Applications of Large Language Models in Multimodal Learning

P Yu, X Xu, J Wang - Journal of Computer Technology and Applied …, 2024 - suaspress.org
In this paper, we provide a systematic review of the emerging field on applications for Large
Language Models (LLMs) in multimodal learning, especially how such methodologies help …

Developing Cryptocurrency Trading Strategy Based on Autoencoder-CNN-GANs Algorithms

Z Hu, R Yu, Z Zhang, H Zheng, Q Liu… - arXiv preprint arXiv …, 2024 - arxiv.org
This paper leverages machine learning algorithms to forecast and analyze financial time
series. The process begins with a denoising autoencoder to filter out random noise …

[PDF][PDF] Low-Carbon Power Technology Innovation: Addressing Environmental Protection, Land Use, and Community Rights

D Luo - 2024 - preprints.org
The rapid advancement of low-carbon technologies, such as wind and nuclear power,
introduces critical ethical challenges, including conflicts between environmental protection …

A Comprehensive Review of Reinforcement Learning in Intelligent Allocation and Optimization of Educational Resources

Z Zhao - Journal of Economic Theory and Business …, 2024 - suaspress.org
Educational resource imbalances pose considerable barriers to accomplishing equitable
opportunities to learn worldwide. Traditional approaches to resource allocation frequently …

Overview of Multimodal Generative Models in Natural Language Processing and Computer Vision

L Li - Journal of Computer Technology and Applied …, 2024 - suaspress.org
Multimodal generative models have become essential in the deep learning renaissance, as
they provide unparalleled flexibility over a diverse context of applications within Natural …