5 papers
Advancing Sentiment Analysis: A Novel LSTM Framework with Multi-head Attention
Jingyuan Yi, Peiyang Yu, Tianyi Huang +1
This work proposes an LSTM-based sentiment classification model with multi-head attention mechanism and TF-IDF optimization. Through the integration of TF-IDF feature extraction an…
Unmasking Digital Falsehoods: A Comparative Analysis of LLM-Based Misinformation Detection Strategies
Tianyi Huang, Jingyuan Yi, Peiyang Yu +1
The proliferation of misinformation on social media has raised significant societal concerns, necessitating robust detection mechanisms. Large Language Models such as GPT-4 and LLa…
A Hybrid Transformer Model for Fake News Detection: Leveraging Bayesian Optimization and Bidirectional Recurrent Unit
Tianyi Huang, Zeqiu Xu, Peiyang Yu +2
In this paper, we propose an optimized Transformer model that integrates Bayesian algorithms with a Bidirectional Gated Recurrent Unit (BiGRU), and apply it to fake news classifica…
Challenges and Innovations in LLM-Powered Fake News Detection: A Synthesis of Approaches and Future Directions
Jingyuan Yi, Zeqiu Xu, Tianyi Huang +1
The pervasiveness of the dissemination of fake news through social media platforms poses critical risks to the trust of the general public, societal stability, and democratic insti…
Optimization of Transformer heart disease prediction model based on particle swarm optimization algorithm
Jingyuan Yi, Peiyang Yu, Tianyi Huang +1
Aiming at the latest particle swarm optimization algorithm, this paper proposes an improved Transformer model to improve the accuracy of heart disease prediction and provide a new…