| Challenge: | Technical logbooks are a challenging and under-explored text type in automated event identification. |
| Approach: | They propose a feedback strategy that resamples the training data based on its error in the prediction process. |
| Outcome: | The proposed approach provides the best results for four different neural network models trained across a suite of technical logbook datasets from distinct technical domains. |
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| Challenge: | Developing methods to improve model performance in imbalanced data settings has been an active area for decades . |
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| Challenge: | Existing methods to synthesize training labels with labeling rules ignore data imbalance issue . weak supervision paradigm is often used to reduce human efforts to produce training labels inexpensively. |
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Guilherme Fonseca, Washington Cunha, Gabriel Prenassi, Marcos André Gonçalves, Leonardo Chaves Dutra Da Rocha
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On the Limitations of Dataset Balancing: The Lost Battle Against Spurious Correlations (2022.findings-naacl)
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| Challenge: | Recent work shows that deep learning models are sensitive to low-level correlations between simple features and specific output labels, leading to over-fitting and lack of generalization. |
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