no code implementations • CRAC (ACL) 2021 • Semere Kiros Bitew, Johannes Deleu, Chris Develder, Thomas Demeester
Large annotated corpora for coreference resolution are available for few languages.
no code implementations • 11 Nov 2023 • Maarten De Raedt, Semere Kiros Bitew, Fréderic Godin, Thomas Demeester, Chris Develder
The brittleness of finetuned language model performance on out-of-distribution (OOD) test samples in unseen domains has been well-studied for English, yet is unexplored for multi-lingual models.
Cross-Lingual Sentiment Classification Sentiment Analysis +3
no code implementations • 7 Nov 2023 • Semere Kiros Bitew, Vincent Schelstraete, Klim Zaporojets, Kimberly Van Nieuwenhove, Reitske Meganck, Chris Develder
In disentangling the heterogeneity observed in psychopathology, personality of the patients is considered crucial.
1 code implementation • 9 Oct 2023 • Karel D'Oosterlinck, Semere Kiros Bitew, Brandon Papineau, Christopher Potts, Thomas Demeester, Chris Develder
State-of-the-art coreference resolutions systems depend on multiple LLM calls per document and are thus prohibitively expensive for many use cases (e. g., information extraction with large corpora).
Ranked #4 on Coreference Resolution on OntoNotes
2 code implementations • 30 Jul 2023 • Semere Kiros Bitew, Johannes Deleu, Chris Develder, Thomas Demeester
We also show the gains of our approach 1 in generating high-quality distractors by comparing it with a zero-shot ChatGPT and a few-shot ChatGPT prompted with static examples.
1 code implementation • 2 Jun 2023 • Semere Kiros Bitew, Johannes Deleu, A. Seza Doğruöz, Chris Develder, Thomas Demeester
Since performing exercises (including, e. g., practice tests) forms a crucial component of learning, and creating such exercises requires non-trivial effort from the teacher, there is a great value in automatic exercise generation in digital tools in education.
1 code implementation • 25 Oct 2022 • Semere Kiros Bitew, Amir Hadifar, Lucas Sterckx, Johannes Deleu, Chris Develder, Thomas Demeester
This paper studies how a large existing set of manually created answers and distractors for questions over a variety of domains, subjects, and languages can be leveraged to help teachers in creating new MCQs, by the smart reuse of existing distractors.
1 code implementation • 12 Oct 2022 • Amir Hadifar, Semere Kiros Bitew, Johannes Deleu, Chris Develder, Thomas Demeester
Thus, our versatile dataset can be used for both question and distractor generation, as well as to explore new challenges such as question format conversion.
no code implementations • WS 2019 • Semere Kiros Bitew, Giannis Bekoulis, Johannes Deleu, Lucas Sterckx, Klim Zaporojets, Thomas Demeester, Chris Develder
This paper describes IDLab{'}s text classification systems submitted to Task A as part of the CLPsych 2019 shared task.