Oct 2, 2020 · In this paper, we proposed a novel model, which disguises the label prediction probability distribution as label embedding and incorporate each label embedding ...
The model disguises the label prediction prob- ability distribution as label embedding and incorporates each label embedding from previous step into the current ...
Label Embedding Enhanced Multi-label Sequence Generation Model. https://doi.org/10.1007/978-3-030-60457-8_18 ·. Видання: Natural Language Processing and ...
In addition, the SGM model is significantly improved by using global embedding. The SGM model with global embedding achieves a reduction of 7.41% hamming loss ...
Missing: Enhanced | Show results with:Enhanced
Dec 9, 2024 · In this paper, we implement a novel model for multi-label classification based on sequence-to-sequence learning, in which two different neural ...
Nov 21, 2022 · I am trying to create a multi-label model for sequence labeling (eg, multi-label NER) where each token in the input can have multiple labels.
Mar 21, 2020 · In this paper, we implement a novel model for multi-label classification based on sequence-to-sequence learning, in which two different neural network modules ...
This paper proposes to view the multi-label classification task as a sequence generation problem, and apply a sequencegeneration model with a novel decoder ...
We propose a label dependence-aware sequence genera- tion model. Both its encoder and decoder, combined with the mutual learning enhanced training method, can ...
Mar 4, 2024 · Label Embedding is to map each label to a high-dimensional space to capture the interactive information of sub-labels. Doc-know-label Attention ...