Text Classification Models

ALDEN, or Active Learning with DivErse iNterpretations, is an active learning approach for text classification. With local interpretations in DNNs, ALDEN identifies linearly separable regions of samples. Then, it selects samples according to their diversity of local interpretations and queries their labels.

Specifically, we first calculate the local interpretations in DNN for each sample as the gradient backpropagated from the final predictions to the input features. Then, we use the most diverse interpretation of words in a sample to measure its diverseness. Accordingly, we select unlabeled samples with the maximally diverse interpretations for labeling and retrain the model with these labeled samples.

Source: Deep Active Learning for Text Classification with Diverse Interpretations

Papers


Paper Code Results Date Stars

Tasks


Task Papers Share
Active Learning 1 25.00%
Classification 1 25.00%
Sentence 1 25.00%
Text Classification 1 25.00%

Components


Component Type
🤖 No Components Found You can add them if they exist; e.g. Mask R-CNN uses RoIAlign

Categories