Papers by Manon Reusens

3 papers
SEER : A Knapsack approach to Exemplar Selection for In-Context HybridQA (2023.emnlp-main)

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Challenge: In-Context Learning with Large Language Models (LLMs) has shown great performance on reasoning tasks.
Approach: They propose a method for selecting a set of exemplars that is representative and diverse.
Outcome: The proposed method outperforms existing methods on FinQA and TAT-QA on hybrid questions.
Are Economists Always More Introverted? Analyzing Consistency in Persona-Assigned LLMs (2025.findings-emnlp)

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Challenge: Personalized Large Language Models are increasingly used in diverse applications . prior research examined how well LLMs adhere to predefined personas in writing style . inconsistent responses are influenced by multiple factors, including the assigned persona, stereotypes, and model design choices.
Approach: They propose a standardized framework to analyze consistency in persona-assigned LLMs.
Outcome: The proposed framework evaluates personas across multiple tasks and runs.
Investigating Bias in Multilingual Language Models: Cross-Lingual Transfer of Debiasing Techniques (2023.emnlp-main)

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Challenge: Debiasing techniques that target sentence representations are being investigated in multilingual models . a growing interest in addressing bias detection and mitigation in NLP due to their societal implications.
Approach: They examine the transferability of debiasing techniques across different languages within multilingual models by using a dataset from CrowS-Pairs.
Outcome: The proposed techniques reduce bias in English, French, German, and Dutch by 13% . the authors also show that the techniques with additional pretraining exhibit enhanced cross-lingual effectiveness for the languages included in the analyses .

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