Automatic News Generation and Fact-Checking System Based on Language Processing

Xirui Peng; Qiming Xu; Zheng Feng; Haopeng Zhao; Lianghao Tan; Yan Zhou; Zecheng Zhang; Chenwei Gong; Yingqiao Zheng

doi:10.5281/zenodo.11179548

Authors

Xirui Peng University of Texas at Austin
Qiming Xu Northeastern University
Zheng Feng Northeastern University
Haopeng Zhao New York University
Lianghao Tan Independent Researcher
Yan Zhou Northeastern University
Zecheng Zhang New York University
Chenwei Gong University of California
Yingqiao Zheng Carnegie Mellon University

DOI:

https://doi.org/10.5281/zenodo.11179548

Keywords:

Automatic News Generation, Fact-checking, Natural Language Processing, Deep Learning, Information Extraction, News Authenticity, Fake News, Language Models

Abstract

This paper explores an automatic news generation and fact-checking system based on language processing, aimed at enhancing the efficiency and quality of news production while ensuring the authenticity and reliability of the news content. With the rapid development of Natural Language Processing (NLP) and deep learning technologies, automatic news generation systems are capable of extracting key information from massive data and generating well-structured, fluent news articles. Meanwhile, by integrating fact-checking technology, the system can effectively prevent the spread of false news and improve the accuracy and credibility of news. This study details the key technologies involved in automatic news generation and fact-checking, including text generation, information extraction, and the application of knowledge graphs, and validates the effectiveness of these technologies through experiments. Additionally, the paper discusses the future development directions of automatic news generation and fact-checking systems, emphasizing the importance of further integration and innovation of technologies. The results show that with continuous technological optimization and practical application, these systems will play an increasingly important role in the future news industry, providing more efficient and reliable news services.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

Author Biographies

Xirui Peng, University of Texas at Austin

University of Texas at Austin, USA.

Qiming Xu, Northeastern University

Northeastern University, USA.

Zheng Feng, Northeastern University

Northeastern University, USA.

Haopeng Zhao, New York University

New York University, USA.

Lianghao Tan, Independent Researcher

Independent Researcher, USA.

Yan Zhou, Northeastern University

Northeastern University, USA.

Zecheng Zhang, New York University

New York University, USA.

Chenwei Gong, University of California

University of California, USA.

Yingqiao Zheng, Carnegie Mellon University

Carnegie Mellon University, USA.

References

Liu, Tianrui, et al. "Particle Filter SLAM for Vehicle Localization." Journal of Industrial Engineering and Applied Science 2.1 (2024): 27-31.

Liu, Tianrui, et al. "News Recommendation with Attention Mechanism." Journal of Industrial Engineering and Applied Science 2.1 (2024): 21-26.

Su, Jing, et al. "Large Language Models for Forecasting and Anomaly Detection: A Systematic Literature Review." arXiv preprint arXiv:2402.10350 (2024).

Liu, Tianrui, et al. "Image Captioning in News Report Scenario." Academic Journal of Science and Technology 10.1 (2024): 284-289.

Liu, Tianrui, et al. "Rumor Detection with A Novel Graph Neural Network Approach." Academic Journal of Science and Technology 10.1 (2024): 305-310.

Wang, Xiaosong, et al. "Advanced Network Intrusion Detection with TabTransformer." Journal of Theory and Practice of Engineering Science 4.03 (2024): 191-198.

Chen, Jie, et al. "Full-Stack Machine Learning Development Framework for Energy Industry Applications." Abu Dhabi International Petroleum Exhibition and Conference. SPE, 2022.

Nagao, Masahiro, et al. "An efficient deep learning-based workflow for CO2 plume imaging considering model uncertainties with distributed pressure and temperature measurements." International Journal of Greenhouse Gas Control 132 (2024): 104066.

Yao, Changqing, Masahiro Nagao, and Akhil Datta-Gupta. A Deep-Learning Based Accelerated Workflow for Robust CO2 Plume Imaging at the Illinois Basin-Decatur Carbon Sequestration Project. National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV, and Albany, OR (United States), 2023.

Fu, Jia, et al. "Field application of a novel multi-resolution multi-well unconventional reservoir simulation: History matching and parameter identification." Unconventional Resources Technology Conference, 13–15 June 2023. Unconventional Resources Technology Conference (URTeC), 2023.

Ren, Xiang, et al. "Data driven oil production prediction and uncertainty quantification for unconventional asset development planning through machine learning." Unconventional Resources Technology Conference, 13–15 June 2023. Unconventional Resources Technology Conference (URTeC), 2023.

Xin, Yi, et al. "VMT-Adapter: Parameter-Efficient Transfer Learning for Multi-Task Dense Scene Understanding." Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 38. No. 14. 2024.

Xin, Yi, et al. "Mmap: Multi-modal alignment prompt for cross-domain multi-task learning." Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 38. No. 14. 2024.

Xin, Yi, et al. "Self-Training with Label-Feature-Consistency for Domain Adaptation." International Conference on Database Systems for Advanced Applications. Cham: Springer Nature Switzerland, 2023.

Peng, Qucheng, Ce Zheng, and Chen Chen. "A Dual-Augmentor Framework for Domain Generalization in 3D Human Pose Estimation." arXiv preprint arXiv:2403.11310 (2024).

Peng, Qucheng, Ce Zheng, and Chen Chen. "Source-free domain adaptive human pose estimation." Proceedings of the IEEE/CVF International Conference on Computer Vision. 2023.

Peng, Qucheng, et al. "RAIN: regularization on input and network for black-box domain adaptation." arXiv preprint arXiv:2208.10531 (2022).

Pinyoanuntapong, Ekkasit, et al. "Gaitsada: Self-aligned domain adaptation for mmwave gait recognition." 2023 IEEE 20th International Conference on Mobile Ad Hoc and Smart Systems (MASS). IEEE, 2023.

Peng, Qucheng. Multi-source and Source-Private Cross-Domain Learning for Visual Recognition. Diss. Purdue University, 2022.

Zhu, Armando, et al. "Cross-Task Multi-Branch Vision Transformer for Facial Expression and Mask Wearing Classification." Journal of Computer Technology and Applied Mathematics 1.1 (2024): 46-53.

Li, Keqin, et al. "Utilizing Deep Learning to Optimize Software Development Processes." Journal of Computer Technology and Applied Mathematics 1.1 (2024): 70-76.

Wang, Jin, et al. "Research on Emotionally Intelligent Dialogue Generation based on Automatic Dialogue System." Journal of Computer Technology and Applied Mathematics 1.1 (2024): 1-5.

Li, Keqin, et al. "The Application of Augmented Reality (AR) in Remote Work and Education." Journal of Computer Technology and Applied Mathematics 1.1 (2024): 33-39.

Jin, Jiajun, et al. "Enhancing Federated Semi-Supervised Learning with Out-of-Distribution Filtering Amidst Class Mismatches." Journal of Computer Technology and Applied Mathematics 1.1 (2024): 100-108.

Song, Jintong, et al. "A Comprehensive Evaluation and Comparison of Enhanced Learning Methods." Academic Journal of Science and Technology 10.3 (2024): 167-171.

Zhou, Yucheng, et al. "Improving zero-shot cross-lingual transfer for multilingual question answering over knowledge graph." Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 2021.

Zhou, Yucheng, et al. "Modeling event-pair relations in external knowledge graphs for script reasoning." Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 (2021).

Zhou, Yucheng, et al. "Eventbert: A pre-trained model for event correlation reasoning." Proceedings of the ACM Web Conference 2022. 2022.

Zhou, Yucheng, et al. "Visual In-Context Learning for Large Vision-Language Models." arXiv preprint arXiv:2402.11574 (2024).

Zhou, Yucheng, et al. "Claret: Pre-training a correlation-aware context-to-event transformer for event-centric generation and classification." arXiv preprint arXiv:2203.02225 (2022).

Zhou, Yucheng, and Guodong Long. "Multimodal event transformer for image-guided story ending generation." arXiv preprint arXiv:2301.11357 (2023).

Yin, Zhengcong, Diya Li, and Daniel W. Goldberg. "Is ChatGPT a game changer for geocoding-a benchmark for geocoding address parsing techniques." Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Searching and Mining Large Collections of Geospatial Data. 2023.

Li, Diya, and Zhe Zhang. "MetaQA: Enhancing human-centered data search using Generative Pre-trained Transformer (GPT) language model and artificial intelligence." Plos one 18.11 (2023): e0293034.

Li, Diya, et al. "A reinforcement learning-based routing algorithm for large street networks." International Journal of Geographical Information Science 38.2 (2024): 183-215.

Wang, Han, et al. "Jointly Learning Selection Matrices For Transmitters, Receivers And Fourier Coefficients In Multichannel Imaging." arXiv preprint arXiv:2402.19023 (2024).

Zhou, Yiming, et al. "Semantic Wireframe Detection." (2023).

Li, Panfeng, Mohamed Abouelenien, and Rada Mihalcea. "Deception Detection from Linguistic and Physiological Data Streams Using Bimodal Convolutional Neural Networks." arXiv preprint arXiv:2311.10944 (2023).

Mingrui Li, et al. " DDN-SLAM: Real-time Dense Dynamic Neural Implicit SLAM" arXiv preprint arXiv: 2401.01545 (2024).

Yu, Zhou, Niloufar Dousti Mousavi, and Jie Yang. "A trigamma-free approach for computing information matrices related to trigamma function." Statistical Papers (2024): 1-21.

Yu, Zhou, Jie Yang, and Hsin-Hsiung Huang. "Smoothing regression and impact measures for accidents of traffic flows." Journal of Applied Statistics (2023): 1-16.

Smalheiser, Neil R., et al. "Effect size, sample size and power of forced swim test assays in mice: Guidelines for investigators to optimize reproducibility." PloS one 16.2 (2021): e0243668.

Cheng, Yi-Ling, et al. "Characterization of microplastics in sediment using stereomicroscopy and laser direct infrared (LDIR) spectroscopy." Gondwana Research 108 (2022): 22-30.

Yuan, Jiajie, et al. "Research on Intelligent Aided Diagnosis System of Medical Image Based on Computer Deep Learning." arXiv preprint arXiv:2404.18419 (2024).

Gong, Yulu, et al. "Innovative Deep Learning Methods for Precancerous Lesion Detection." International Journal of Innovative Research in Computer Science & Technology 12.2 (2024): 81-86.