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Found 5 papers, 1 papers with code
Generative Zero-Shot Prompt Learning for Cross-Domain Slot Filling with Inverse Prompting
Zero-shot cross-domain slot filling aims to transfer knowledge from the labeled source domain to the unlabeled target domain.
PSSAT: A Perturbed Semantic Structure Awareness Transferring Method for Perturbation-Robust Slot Filling
Most existing slot filling models tend to memorize inherent patterns of entities and corresponding contexts from training data.
A Robust Contrastive Alignment Method For Multi-Domain Text Classification
In this paper, we propose a robust contrastive alignment method to align text classification features of various domains in the same feature space by supervised contrastive learning.
Concentrated Document Topic Model
We propose a Concentrated Document Topic Model(CDTM) for unsupervised text classification, which is able to produce a concentrated and sparse document topic distribution.
Exclusive Topic Modeling
We propose an Exclusive Topic Modeling (ETM) for unsupervised text classification, which is able to 1) identify the field-specific keywords though less frequently appeared and 2) deliver well-structured topics with exclusive words.
