Deep learning is the predominant machine learning paradigm in natural language processing (NLP). This approach not only gave huge performance improvements across a large variety of natural language processing tasks. However, large languages models struggle with rules, logic, reasoning and facts. Therefore this semesters seminar will focus on neuro-explicit models that is neural networks that also incorporate explicit knowledge like logic, math or laws of nature.
Lecturer: Dietrich Klakow, Vagrant Gautam
Time: block course in the fall break 2023 however preparations start earlier. Here the specific time line
Closing topic doodle: May 1st
Kick-Off: some time May 8-May 12 (doodle)
One page outline: due June 19
Draft presentation: due July 16
Practice talks and final talks will be during the summer break. Time/date will be decided during the kick-off.
HISPOS registration deadline: July 16
- 5% one page talk outline
- 10% draft presentation
- 10% practice talk
- 35% final talk
- 5% contributions to discussion during final talk of fellow participants
- 35% report
List of Topics (tentative):