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20232026
most citedNative Design Bias: Studying the Impact of English Nativeness on Language Model Performance

3 citations · 4 across the 10 of their papers we have counts for

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9 papers · 1 filter

cs.CL2025

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…

cs.CL2025

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…

cs.CL2024

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…

cs.CL2024★ 3 cited

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…

cs.CL2024

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…

cs.CL2023

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…

cs.CL2023★ 1 cited

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…

cs.CL2023

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…

cs.CL2023

Taught by the Internet, Exploring Bias in OpenAIs GPT3

Ali Ayaz, Aditya Nawalgaria, Ruilian Yin

This research delves into the current literature on bias in Natural Language Processing Models and the techniques proposed to mitigate the problem of bias, including why it is impo…