Author

Haeun Yu

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#natural language process... Preprint Oct 2026

A Reality Check of Inference-Time Context Augmentation Methods

Large language models (LLMs) often fail to utilise the context given in the input, resulting in hallucinations or a fallback to parametric knowledge. Context augmentation methods aim to improve model performance by modifying the input, from inserting filler tokens that add computational time to adding relevant content...

Haeun Yu, Geert Heyman, Pepa Atanasova et al. · 0 citations

#artificial intelligence Preprint Aug 2025

BiasGym: A Simple and Generalizable Framework for Analyzing and Removing Biases through Injection

The proposed framework enables consistent bias elicitation for better localization of bias conceptual association in the model space, supports targeted debiasing without degrading performance on downstream tasks, and generalizes to biases unseen during fine-tuning.

Sekh Mainul Islam, Nadav Borenstein, Siddhesh Pawar et al. · 1 citation