41 citations · 52 across the 18 of their papers we have counts for
7 papers · 1 filter
Domain Adaptation of LLMs for Process Data
Rafael Seidi Oyamada, Jari Peeperkorn, Jochen De Weerdt +1
In recent years, Large Language Models (LLMs) have emerged as a prominent area of interest across various research domains, including Process Mining (PM). Current applications in P…
Bridging Language Gaps: Enhancing Few-Shot Language Adaptation
Philipp Borchert, Jochen De Weerdt, Marie-Francine Moens
The disparity in language resources poses a challenge in multilingual NLP, with high-resource languages benefiting from extensive data, while low-resource languages lack sufficient…
Language Fusion for Parameter-Efficient Cross-lingual Transfer
Philipp Borchert, Ivan Vulić, Marie-Francine Moens +1
Limited availability of multilingual text corpora for training language models often leads to poor performance on downstream tasks due to undertrained representation spaces for lan…
Native Design Bias: Studying the Impact of English Nativeness on Language Model Performance
Manon Reusens, Philipp Borchert, Jochen De Weerdt +1
Large Language Models (LLMs) excel at providing information acquired during pretraining on large-scale corpora and following instructions through user prompts. This study investiga…
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…
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…