Papers with online application

2 papers
Towards Need-Based Spoken Language Understanding Model Updates: What Have We Learned? (2022.emnlp-industry)

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Challenge: In productionized machine learning systems, online model performance deteriorates when there is a distributional drift between offline training and online data.
Approach: They propose a need-based retraining strategy guided by an efficient drift detector . they propose overlapping model releases, observation limitation and lack of annotated resources at runtime .
Outcome: The proposed strategy reduces the cost of retraining models at fixed intervals . the proposed strategy can detect drifts when the model is applied on a new data set .
Improving Knowledge Production Efficiency With Question Answering on Conversation (2023.acl-industry)

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Challenge: Existing researches on conversation-based QA focus on document-based tasks . current researche focuses on document based tasks, but there is a lack of researche on conversation based qa .
Approach: They propose a multi-span extraction model on conversation-based QA and introduce continual pre-training and multi-task learning schemes to further improve model performance.
Outcome: The proposed model outperforms baseline on two Chinese datasets and will be released for research purposes.

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