Papers by Maarten De Raedt

2 papers
Robustifying Sentiment Classification by Maximally Exploiting Few Counterfactuals (2022.emnlp-main)

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Challenge: a recent study found that finetuned language models rely on spurious patterns in training data . this limitation limits their performance on out-of-distribution (OOD) test data.
Approach: They propose a method that only requires annotation of a small fraction of training data . they add 1% manual counterfactuals to training data and generate extra counterfacts in vector space .
Outcome: The proposed approach improves sentiment classification using IMDb data and other sets for OOD tests.
A Simple Geometric Method for Cross-Lingual Linguistic Transformations with Pre-trained Autoencoders (2021.emnlp-main)

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Challenge: Existing studies have used probing tasks to verify the presence of linguistic properties in vector representations, but it is unclear whether they can be manipulated to indirectly steer them.
Approach: They validate a geometric mapping technique to transform linguistic properties without tuning . they use a pre-trained multilingual autoencoder to transform three linguistic property .
Outcome: The proposed method can be used without tuning of the pre-trained autoencoder . the results are validated in monolingual and cross-lingual settings .

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