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Found 5 papers, 3 papers with code
Semantic-Rearrangement-Based Multi-Level Alignment for Domain Generalized Segmentation
SRMA first incorporates a Semantic Rearrangement Module (SRM), which conducts semantic region randomization to enhance the diversity of the source domain sufficiently.
LafitE: Latent Diffusion Model with Feature Editing for Unsupervised Multi-class Anomaly Detection
Moreover, we are the first who pose the problem of hyperparameter selection in unsupervised anomaly detection, and propose a solution of synthesizing anomaly data for a pseudo validation set to address this problem.
UniTrans: Unifying Model Transfer and Data Transfer for Cross-Lingual Named Entity Recognition with Unlabeled Data
Prior works in cross-lingual named entity recognition (NER) with no/little labeled data fall into two primary categories: model transfer based and data transfer based methods.
Ranked #1 on
Cross-Lingual NER
on NoDaLiDa Norwegian Bokmål
Single-/Multi-Source Cross-Lingual NER via Teacher-Student Learning on Unlabeled Data in Target Language
However, such methods either are not applicable if the labeled data in the source languages is unavailable, or do not leverage information contained in unlabeled data in the target language.
Ranked #1 on
Cross-Lingual NER
on CoNLL German
Enhanced Meta-Learning for Cross-lingual Named Entity Recognition with Minimal Resources
For languages with no annotated resources, transferring knowledge from rich-resource languages is an effective solution for named entity recognition (NER).
Ranked #1 on
Cross-Lingual NER
on MSRA
