Björn BebenseeEmail: bebensee [at] snu.ac.kr
Good day! I am currently a research engineer at Samsung Research where I work on pre-training large language models. I am broadly interested in how to train better LLMs faster. I also do research on dialogue understanding and published a paper introducing a novel span-based architecture for schema-guided dialogue state tracking
I completed my Master's degree at Seoul National University where I also worked as a Graduate Research Assistant in the Biointelligence Laboratory supervised by Byoung-Tak Zhang. There, I did research on machine learning at the intersection of language and vision. I wrote a paper proposing a co-attentional Transformer for video question answering that was accepted to ICASSP 2021.
Before getting into research I was an undergraduate student at RWTH Aachen where I studied computer science. I wrote my bachelor thesis on applying hidden Markov models to the problem space of Enterprise Architecture to automate the model creation process using network data. During my undergrad I also did a software project internship with ITERGO doing software development for ERGO Group. I also studied abroad at EWHA Womans Unversity in 2017.
Some things about me:
- Grew up near the town of Bremen, Germany
- Currently live in Seoul, Korea
- Moved to Korea for my Master's degree after initially coming as an exchange student
Span-Selective Linear Attention Transformers for Effective and Robust Schema-Guided Dialogue State Tracking,
Björn Bebensee, Haejun Lee.
Co-Attentional Transformers for Story-Based Video Understanding,
Björn Bebensee, Byoung-Tak Zhang.
Applying Dynamic Bayesian Networks for Automated Modeling in ArchiMate: A Realization Study,
Björn Bebensee, Simon Hacks.
Local Differential Privacy: a tutorial,
Large language models, i.e. how to train better models faster, and their applications to dialogue and natural language understanding.
Feel free to ping me on Twitter, or send me an email!