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Found 5 papers, 3 papers with code
CoT-MAE v2: Contextual Masked Auto-Encoder with Multi-view Modeling for Passage Retrieval
As an effective representation bottleneck pretraining technique, the contextual masked auto-encoder utilizes contextual embedding to assist in the reconstruction of passages.
Good Is Bad: Causality Inspired Cloth-Debiasing for Cloth-Changing Person Re-Identification
Entangled representation of clothing and identity (ID)-intrinsic clues are potentially concomitant in conventional person Re-IDentification (ReID).
ConTextual Masked Auto-Encoder for Dense Passage Retrieval
Dense passage retrieval aims to retrieve the relevant passages of a query from a large corpus based on dense representations (i. e., vectors) of the query and the passages.
Text Smoothing: Enhance Various Data Augmentation Methods on Text Classification Tasks
Before entering the neural network, a token is generally converted to the corresponding one-hot representation, which is a discrete distribution of the vocabulary.
Imbalanced Sentiment Classification Enhanced with Discourse Marker
Imbalanced data commonly exists in real world, espacially in sentiment-related corpus, making it difficult to train a classifier to distinguish latent sentiment in text data.
