Papers with EQA problem

1 papers
Towards Robust Extractive Question Answering Models: Rethinking the Training Methodology (2024.findings-emnlp)

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Challenge: Existing models lack robustness against distribution shifts and adversarial attacks when training on unanswerable questions in EQA datasets.
Approach: They propose a novel loss function for the EQA problem to improve the robustness of extractive question answering models by adding adversarial questions to a crowdsourcing process.
Outcome: The proposed method maintains in-domain performance while improving on out-of-domain datasets.

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