Natural Language Processing - Methods and Applications

People in organizations, society and institutions communicate via natural language. Typically, large amounts of unstructured information are stored in text documents. However, it is very challenging for machines to query relevant content fast and extract structured information.

Machine-based solutions for text analysis, indexing and generation are often summarized under the terms natural language processing, text mining or natural language generation. In the past decades, many different methods and solutions have been developed. The diversity of the different problems and the fast development of new technologies, e.g. machine learning, underline the large potential of these methods. 

The seminar aims to give an overview over the technological building blocks and their applications. The participants independently work on a scientific topic, based on existing literature and present and discuss their findings in a presentation and a seminar paper.

Proposed Seminar Topics:

Basics

1. Information Extraction 

2.Information Retrieval 

3. Topic Modelling 

4. Word Embedding 

5. seq2seq models 

Large Language Models

6. Transformer: Architecture 

7. Transformer: Applications 

8. Large Language Models: Architecture, Pre-training and Fine-tuning 

9. Efficient Transformers

10. Ethnical & Social concerns, Privacy, and Limitations of Large Language Models 

Natural Language Generation and Evaluation

11. Machine Translation ( Multilingual NLP) 

12. Text Summarization 

13. Model Hallucination  

14. Corpus-based Question Answering 

Conversational AI / Conversational Interfaces

15. Task-based & Social Conversational Agents 

16. Dialogue Management (Dialogue State Tracking & Policy) 

17. Conversational Search Systems 

Knowledge Graph in NLP

18. Graph Representations for NLP 

19. Knowledge Graph-based Question Answering

Natural Language Inference

20. Natural Language Inference 

LegalTech

21. Semantic Analysis of Legal Documents

22. LegalTech: Applications of Information Retrieval, Summarization and Simplification

Differential Privacy in NLP

23. Metric Differential Privacy in NLP

24. Privacy in Deep NLP

Explainability in NLP

25. Explainability in NLP

Weekly Sessions

Deliverables

Submissions