1 citations · 1 across the 3 of their papers we have counts for
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Self-Distillation for Model Stacking Unlocks Cross-Lingual NLU in 200+ Languages
Fabian David Schmidt, Philipp Borchert, Ivan Vulić +1
LLMs have become a go-to solution not just for text generation, but also for natural language understanding (NLU) tasks. Acquiring extensive knowledge through language modeling on…
Efficient Information Extraction in Few-Shot Relation Classification through Contrastive Representation Learning
Philipp Borchert, Jochen De Weerdt, Marie-Francine Moens
Differentiating relationships between entity pairs with limited labeled instances poses a significant challenge in few-shot relation classification. Representations of textual data…
SEER : A Knapsack approach to Exemplar Selection for In-Context HybridQA
Jonathan Tonglet, Manon Reusens, Philipp Borchert +1
Question answering over hybrid contexts is a complex task, which requires the combination of information extracted from unstructured texts and structured tables in various ways. Re…
CORE: A Few-Shot Company Relation Classification Dataset for Robust Domain Adaptation
Philipp Borchert, Jochen De Weerdt, Kristof Coussement +2
We introduce CORE, a dataset for few-shot relation classification (RC) focused on company relations and business entities. CORE includes 4,708 instances of 12 relation types with c…
Investigating Bias in Multilingual Language Models: Cross-Lingual Transfer of Debiasing Techniques
Manon Reusens, Philipp Borchert, Margot Mieskes +2
This paper investigates the transferability of debiasing techniques across different languages within multilingual models. We examine the applicability of these techniques in Engli…