Annemarie Friedrich
@annefriedrich.bsky.social
130 followers 340 following 5 posts
Associate Professor and Computational Linguist @ University of Augsburg, Germany
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annefriedrich.bsky.social
Looking forward to #acl2025 in Vienna! Excited to catch up. I am also hiring, one fully paid (100% E13) position for either a PhD student or a PostDoc in computational linguistics / digital humanities / corpus linguistics (earliest start date: October 2025). Who is interested?
Reposted by Annemarie Friedrich
bamnlp.de
BamNLP @bamnlp.de · Jul 24
Last week, we've been on a retreat to talk about the big picture of our research, research ideas, and synergies between group members – and did some team building.
@annefriedrich.bsky.social
was our external guest and helped us out of a couple of local optima. Thank you for participating!
annefriedrich.bsky.social
Just came home from an awesome three-day retreat with the BamNLP group of @romanklinger.de. We talked about uncertainty in NLP, modeling emotions, and knowledge editing. Thank you for making me feel so welcome! I immensely enjoyed hanging out at a Bavarian Caribbean beach with you, BamNLP!
Caribbean corner beach in Lichtenfels
annefriedrich.bsky.social
Thanks for the nice feedback. :) My favorite in the subtitles was Chatchipiti. 😆
annefriedrich.bsky.social
This Wednesday, Christian Chiarcos and I finally gave our inaugural lectures at the University of Augsburg, hosted jointly by the Faculty of Applied Computer Science and the Faculty of Philology and History. Deeply grateful for working in this interdisciplinary context!
Picture from inaugural lecture of Prof. Friedrich and Prof. Chiarcos at Uni Augsburg, Germany.
annefriedrich.bsky.social
Ever wondered how effective LLMs are on detecting problems with formulating patents? Our paper on the new dataset PEDANTIC has just been accepted to PatentSemTech 2025 @ SIGIR 2025 in Padua, Italy. Really proud of Valentin Knappich. Find the prepint here: arxiv.org/abs/2505.21342
Illustration of the components of PEDANTIC: patent text, span annotations for writing issues such as Antecedent Basis or Undefined Term. Binary and Multi-Label Tasks, as well as applying an LLM for pair-wise reason judgments.