Search Results for author: Xinyu Ma

Found 9 papers, 4 papers with code

Pre-train a Discriminative Text Encoder for Dense Retrieval via Contrastive Span Prediction

no code implementations22 Apr 2022 Xinyu Ma, Jiafeng Guo, Ruqing Zhang, Yixing Fan, Xueqi Cheng

% Therefore, in this work, we propose to drop out the decoder and introduce a novel contrastive span prediction task to pre-train the encoder alone.

Contrastive Learning Information Retrieval +1

MedFACT: Modeling Medical Feature Correlations in Patient Health Representation Learning via Feature Clustering

no code implementations21 Apr 2022 Xinyu Ma, Xu Chu, Yasha Wang, Hailong Yu, Liantao Ma, Wen Tang, Junfeng Zhao

Thus, to address the issues, we expect to group up strongly correlated features and learn feature correlations in a group-wise manner to reduce the learning complexity without losing generality.

Representation Learning

Pre-training Methods in Information Retrieval

no code implementations27 Nov 2021 Yixing Fan, Xiaohui Xie, Yinqiong Cai, Jia Chen, Xinyu Ma, Xiangsheng Li, Ruqing Zhang, Jiafeng Guo

The core of information retrieval (IR) is to identify relevant information from large-scale resources and return it as a ranked list to respond to the user's information need.

Information Retrieval Re-Ranking

B-PROP: Bootstrapped Pre-training with Representative Words Prediction for Ad-hoc Retrieval

1 code implementation20 Apr 2021 Xinyu Ma, Jiafeng Guo, Ruqing Zhang, Yixing Fan, Yingyan Li, Xueqi Cheng

The basic idea of PROP is to construct the \textit{representative words prediction} (ROP) task for pre-training inspired by the query likelihood model.

Information Retrieval Language Modelling

A Linguistic Study on Relevance Modeling in Information Retrieval

no code implementations1 Mar 2021 Yixing Fan, Jiafeng Guo, Xinyu Ma, Ruqing Zhang, Yanyan Lan, Xueqi Cheng

We employ 16 linguistic tasks to probe a unified retrieval model over these three retrieval tasks to answer this question.

Information Retrieval Natural Language Understanding +1

PROP: Pre-training with Representative Words Prediction for Ad-hoc Retrieval

1 code implementation20 Oct 2020 Xinyu Ma, Jiafeng Guo, Ruqing Zhang, Yixing Fan, Xiang Ji, Xueqi Cheng

Recently pre-trained language representation models such as BERT have shown great success when fine-tuned on downstream tasks including information retrieval (IR).

Information Retrieval Language Modelling

ConCare: Personalized Clinical Feature Embedding via Capturing the Healthcare Context

1 code implementation27 Nov 2019 Liantao Ma, Chaohe Zhang, Yasha Wang, Wenjie Ruan, Jiantao Wang, Wen Tang, Xinyu Ma, Xin Gao, Junyi Gao

Predicting the patient's clinical outcome from the historical electronic medical records (EMR) is a fundamental research problem in medical informatics.

AdaCare: Explainable Clinical Health Status Representation Learning via Scale-Adaptive Feature Extraction and Recalibration

1 code implementation27 Nov 2019 Liantao Ma, Junyi Gao, Yasha Wang, Chaohe Zhang, Jiangtao Wang, Wenjie Ruan, Wen Tang, Xin Gao, Xinyu Ma

It also models the correlation between clinical features to enhance the ones which strongly indicate the health status and thus can maintain a state-of-the-art performance in terms of prediction accuracy while providing qualitative interpretability.

Representation Learning

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