In an era where misinformation spreads faster than the truth, my research focuses on the crucial issue of fake news detection using the latest advancements in AI.
As an applied researcher in the field of AI, I’m currently focused on the critical issue of fake news detection. My work involves developing innovative approaches using advanced NLP and machine learning techniques. I’m keen on collaboration with like-minded professionals and academics who share a vision for leveraging Generative AI to ensure information integrity. Together, we can confront the challenges posed by digital misinformation and contribute to a more informed and truthful discourse in the digital age.
Researching fake news detection; interested in collaborations for cutting-edge research in this dynamic field.
My work in these areas includes both academic research and practical applications, as I strive to bridge the gap between theory and practice. I am constantly seeking out new challenges and opportunities to learn and grow, and I am passionate about sharing my insights and expertise with others.
If you are interested in learning more about my research work, I invite you to check out my Google Scholar profile and my ResearchGate profile, where you can find a list of my publications and citations. I also have a Microsoft Research profile, where you can learn more about my work in industry and academia. I also recommend visiting my ORCID record, which offers a detailed and verified list of my academic publications and activities across various platforms. Additionally, explore my GitHub repositories for access to my projects and code.
@misc{loth_blessing_2024,
title = {Blessing or curse? A survey on the Impact of Generative AI on Fake News},
author = {Alexander Loth and Martin Kappes and Marc-Oliver Pahl},
url = {http://arxiv.org/abs/2404.03021},
year = {2024},
date = {2024-04-03},
urldate = {2024-04-05},
number = {arXiv:2404.03021},
publisher = {arXiv},
abstract = {Fake news significantly influence our society. They impact consumers, voters, and many other societal groups. While Fake News exist for a centuries, Generative AI brings fake news on a new level. It is now possible to automate the creation of masses of high-quality individually targeted Fake News. On the other end, Generative AI can also help detecting Fake News. Both fields are young but developing fast. This survey provides a comprehensive examination of the research and practical use of Generative AI for Fake News detection and creation in 2024. Following the Structured Literature Survey approach, the paper synthesizes current results in the following topic clusters 1) enabling technologies, 2) creation of Fake News, 3) case study social media as most relevant distribution channel, 4) detection of Fake News, and 5) deepfakes as upcoming technology. The article also identifies current challenges and open issues.},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
Fake news significantly influence our society. They impact consumers, voters, and many other societal groups. While Fake News exist for a centuries, Generative AI brings fake news on a new level. It is now possible to automate the creation of masses of high-quality individually targeted Fake News. On the other end, Generative AI can also help detecting Fake News. Both fields are young but developing fast. This survey provides a comprehensive examination of the research and practical use of Generative AI for Fake News detection and creation in 2024. Following the Structured Literature Survey approach, the paper synthesizes current results in the following topic clusters 1) enabling technologies, 2) creation of Fake News, 3) case study social media as most relevant distribution channel, 4) detection of Fake News, and 5) deepfakes as upcoming technology. The article also identifies current challenges and open issues.
@article{loth2017necessity,
title = {The Necessity for a modern Data Strategy in the Course of Digital Transformation},
author = {Alexander Loth},
year = {2017},
date = {2017-01-01},
journal = {INFORMATION-WISSENSCHAFT UND PRAXIS},
volume = {68},
number = {1},
pages = {75–77},
publisher = {WALTER DE GRUYTER GMBH GENTHINER STRASSE 13, D-10785 BERLIN, GERMANY},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
@inproceedings{trentadue2012lcg,
title = {LCG persistency framework (CORAL, COOL, POOL): status and outlook in 2012},
author = {R Trentadue and M Clemencic and D Dykstra and M Frank and A Kalkhof and A Loth and M Nowak and A Salnikov and A Valassi and M Wache and others},
year = {2012},
date = {2012-01-01},
booktitle = {Journal of Physics: Conference Series},
volume = {396},
number = {5},
pages = {052067},
organization = {IOP Publishing},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@techreport{shiers2011sustainability,
title = {SUSTAINABILITY PLANS FOR THE ACTIVITIES OF THE HEAVY USER COMMUNITIES},
author = {J Shiers and M KENYON and R TRENTADUE and J MOSCICKI and M LITMAATH and D VAN DER STER and D SPIGA and F BARREIRO MEGINO and E LANCIOTTI and A VALASSI and others},
year = {2011},
date = {2011-01-01},
keywords = {},
pubstate = {published},
tppubtype = {techreport}
}
@inproceedings{valassi2011lcg,
title = {Lcg persistency framework (coral, cool, pool): Status and outlook},
author = {A Valassi and M Clemencic and D Dykstra and M Frank and G Govi and A Kalkhof and A Loth and M Nowak and W Pokorski and A Salnikov and others},
year = {2011},
date = {2011-01-01},
booktitle = {Journal of Physics: Conference Series},
volume = {331},
number = {4},
pages = {042043},
organization = {IOP Publishing},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
As I continue to work in the fields of machine learning, NLP, and large language models, I am excited to collaborate with others who share my passion and vision for the future of AI. Whether you are a researcher, student, or industry professional, I welcome the opportunity to connect via social media and work together to drive innovation and create new possibilities:
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