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Luna De Bruyne

2 accepted papers

2025

In Benchmarks We Trust ... Or Not?

EMNLP 2025

Standardized benchmarks are central to evaluating and comparing model performance in Natural Language Processing (NLP). However, Large Language Models (LLMs) have exposed shortcomings in existing benchmarks, and so far there is no clear solution. In this paper, we survey a wide scope of benchmarking

Cited by 1SourcePDFScholar
2023

Misery Loves Complexity: Exploring Linguistic Complexity in the Context of Emotion Detection

EMNLP 2023long findings

Given the omnipresence of social media in our society, thoughts and opinions are being shared online in an unprecedented manner. This means that both positive and negative emotions can be equally and freely expressed. However, the negativity bias posits that human beings are inherently drawn to and…

Cited by 0SourceScholar