Active Label Correction (ALC) is an interactive method that cleans an established training set of mislabeled examples in conjunction with a domain expert.
Mar 16, 2024 · We hence propose an effective framework of active label correction (ALC) based on a design of correction query to rectify pseudo labels of ...
Active label correction addresses the problem of learning from input data for which noisy labels are available (e.g., from imprecise measurements or ...
We hence propose an effective framework of active label correction (ALC) based on a design of correction query to rectify pseudo labels of pixels, which in turn ...
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Active label correction. Typically, active label correction algorithms select examples to query by assessing the confidences of predictions made by the clas ...
Oct 3, 2024 · We hypothesize that Active Label Correction (ALC) can be use on the collected data to train smaller task-specific improved models that can ...
We hypothesize that Active Label Correction (ALC) can be use on the collected data to train smaller task-specific improved models that can replace LLM-based ...
Active Label Correction (ALC) is an interactive method that cleans an established training set of mislabeled examples in conjunction with a domain expert.
... active label correction can be used to improve the data quality by only examining a fraction of the dataset. In this paper, we analyze the noise in datasets ...
Active label correction addresses the problem of learning from input data for which noisy labels are available (e.g., from imprecise mea-.