Papers by Irtiza Chowdhury

2 papers
The Craft of Selective Prediction: Towards Reliable Case Outcome Classification - An Empirical Study on European Court of Human Rights Cases (2024.findings-emnlp)

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Challenge: Existing COC tasks prioritize high task performance over model reliability . however, large models exhibit overconfidence and Monte Carlo dropout methods produce reliable confidence estimates .
Approach: They conduct an empirical investigation into how various design choices affect the reliability of COC models within the framework of selective prediction.
Outcome: The proposed model is able to predict the outcome of a legal case based on the text of the case facts and is compared with other models using a pre-training corpus.
Fairness Beyond Performance: Revealing Reliability Disparities Across Groups in Legal NLP (2025.acl-long)

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Challenge: a recent study shows that models often make less reliable or overconfident predictions for marginalized groups.
Approach: They evaluate performance and reliability disparities across demographic, regional, and legal attributes across four jurisdictions using the FairLex benchmark.
Outcome: The FairLex benchmark shows that pre-training improves performance and reliability for underrepresented groups.

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