activity
20192024
most citedCodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation

416 citations · 1k across the 55 of their papers we have counts for

collaborators
Showing 2022Show all

8 papers · 1 filter

cs.CL2022★ 1 cited

Mixed-modality Representation Learning and Pre-training for Joint Table-and-Text Retrieval in OpenQA

Junjie Huang, Wanjun Zhong, Qian Liu +3

Retrieving evidences from tabular and textual resources is essential for open-domain question answering (OpenQA), which provides more comprehensive information. However, training a…

cs.IR2022★ 3 cited

Unsupervised Context Aware Sentence Representation Pretraining for Multi-lingual Dense Retrieval

Ning Wu, Yaobo Liang, Houxing Ren +4

Recent research demonstrates the effectiveness of using pretrained language models (PLM) to improve dense retrieval and multilingual dense retrieval. In this work, we present a sim…

cs.IR2022★ 23 cited

Bridging the Gap Between Indexing and Retrieval for Differentiable Search Index with Query Generation

Shengyao Zhuang, Houxing Ren, Linjun Shou +4

The Differentiable Search Index (DSI) is an emerging paradigm for information retrieval. Unlike traditional retrieval architectures where index and retrieval are two different and…

cs.IR2022★ 20 cited

Negative Sampling for Contrastive Representation Learning: A Review

Lanling Xu, Jianxun Lian, Wayne Xin Zhao +5

The learn-to-compare paradigm of contrastive representation learning (CRL), which compares positive samples with negative ones for representation learning, has achieved great succe…

cs.CL2022

Label-aware Multi-level Contrastive Learning for Cross-lingual Spoken Language Understanding

Shining Liang, Linjun Shou, Jian Pei +4

Despite the great success of spoken language understanding (SLU) in high-resource languages, it remains challenging in low-resource languages mainly due to the lack of labeled trai…

cs.CL2022

Bridging the Gap between Language Models and Cross-Lingual Sequence Labeling

Nuo Chen, Linjun Shou, Ming Gong +2

Large-scale cross-lingual pre-trained language models (xPLMs) have shown effectiveness in cross-lingual sequence labeling tasks (xSL), such as cross-lingual machine reading compreh…

cs.IR2022★ 1 cited

Transformer-Empowered Content-Aware Collaborative Filtering

Weizhe Lin, Linjun Shou, Ming Gong +4

Knowledge graph (KG) based Collaborative Filtering is an effective approach to personalizing recommendation systems for relatively static domains such as movies and books, by lever…

cs.CL2022

Multi-View Document Representation Learning for Open-Domain Dense Retrieval

Shunyu Zhang, Yaobo Liang, Ming Gong +2

Dense retrieval has achieved impressive advances in first-stage retrieval from a large-scale document collection, which is built on bi-encoder architecture to produce single vector…