Search Results for author: Meng Lin

Found 5 papers, 3 papers with code

CoT-MAE v2: Contextual Masked Auto-Encoder with Multi-view Modeling for Passage Retrieval

no code implementations5 Apr 2023 Xing Wu, Guangyuan Ma, Peng Wang, Meng Lin, Zijia Lin, Fuzheng Zhang, Songlin Hu

As an effective representation bottleneck pretraining technique, the contextual masked auto-encoder utilizes contextual embedding to assist in the reconstruction of passages.

Passage Retrieval Retrieval +1

Good Is Bad: Causality Inspired Cloth-Debiasing for Cloth-Changing Person Re-Identification

1 code implementation CVPR 2023 Zhengwei Yang, Meng Lin, Xian Zhong, Yu Wu, Zheng Wang

Entangled representation of clothing and identity (ID)-intrinsic clues are potentially concomitant in conventional person Re-IDentification (ReID).

Cloth-Changing Person Re-Identification

ConTextual Masked Auto-Encoder for Dense Passage Retrieval

2 code implementations16 Aug 2022 Xing Wu, Guangyuan Ma, Meng Lin, Zijia Lin, Zhongyuan Wang, Songlin Hu

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.

Decoder Passage Retrieval +2

Text Smoothing: Enhance Various Data Augmentation Methods on Text Classification Tasks

1 code implementation ACL 2022 Xing Wu, Chaochen Gao, Meng Lin, Liangjun Zang, Zhongyuan Wang, Songlin Hu

Before entering the neural network, a token is generally converted to the corresponding one-hot representation, which is a discrete distribution of the vocabulary.

Data Augmentation Language Modelling +3

Imbalanced Sentiment Classification Enhanced with Discourse Marker

no code implementations28 Mar 2019 Tao Zhang, Xing Wu, Meng Lin, Jizhong Han, Songlin Hu

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.

Classification Data Augmentation +4

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