Before the presentation (by noon on Monday, 11/12/2023):

• Submit the following into the homework vault of your project
  • A file with your presentation (PDF is preferred, but PowerPoint is also OK)
  • Your project implementation (ideally, one self-contained Python notebook that loads necessary data from a URL, but an archive with your code and required data resources is also possible, if there is no other option).

Presentation format:

1. Project presentation
   • Presenting the results of reproducing your chosen piece of research, describing your extension or re-interpretation of the model, and, most importantly, a summary of lessons learned.
   • Duration max 10 minutes!!!
2. Discussion
1. General discussion
2. Duration max 5 minutes!!!

Presenting groups:

• Group 1
  • Members: Pavel Nedělník, Patrik Begáň, Samuel Gazda
  • Topic: Electra: Pre-training text encoders as discriminators rather than generators
• Group 2
  • Members: Marc Monfort Muñoz, Aigerim Bilyalova, Arman Sakibekov, Emre Karyagdi
  • Topic: Automatic Detection of Fake News
• Group 3
  • Members: Jakub Pekár, Jonáš Tichý, Kryštof Zamazal
  • Topic: Unsupervised Machine Translation Using Monolingual Corpora Only
• Group 4
  • Members: Samuel Šuľan, Heejoo Kim, Muhammad Jazim Ali
  • Topic: Optimization and improvement of fake news detection using deep learning approaches for societal benefit
• Group 5
  • Members: Nakul Gupta, Tanmay Rakhe, Himanshu Sharma, Himanshu Kasana
  • Topic: Support Vector Machines for Spam Categorization