Papers › Rethinking the Objectives of Extractive Question Answering

Rethinking the Objectives of Extractive Question Answering

28 Aug 2020EMNLP (MRQA) 2021 11arXiv:2008.12804archive 2025-07-28

Martin Fajcik, Josef Jon, Pavel Smrz

This work demonstrates that using the objective with independence assumption for modelling the span probability P(aₛ,aₑ) = P(aₛ)P(aₑ) of span starting at position aₛ and ending at position aₑ has adverse effects. Therefore we propose multiple approaches to modelling joint probability P(aₛ,aₑ) directly. Among those, we propose a compound objective, composed from the joint probability while still keeping the objective with independence assumption as an auxiliary objective. We find that the compound objective is consistently superior or equal to other assumptions in exact match. Additionally, we identified common errors caused by the assumption of independence and manually checked the counterpart predictions, demonstrating the impact of the compound objective on the real examples. Our findings are supported via experiments with three extractive QA models (BIDAF, BERT, ALBERT) over six datasets and our code, individual results and manual analysis are available online.

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Extractive Question-AnsweringQuestion Answering

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AdamAttentionAttention DropoutBERTDense ConnectionsDropoutLayer NormalizationLinear LayerLinear Warmup With Linear DecayMulti-Head AttentionResidual ConnectionSoftmaxWeight DecayWordPiece

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