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20152023
most citedAccurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model

1k citations · 1.7k across the 19 of their papers we have counts for

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Showing 2020Show all

6 papers · 1 filter

cs.CL2020★ 1 cited

Cross-Thought for Sentence Encoder Pre-training

Shuohang Wang, Yuwei Fang, Siqi Sun +4

In this paper, we propose Cross-Thought, a novel approach to pre-training sequence encoder, which is instrumental in building reusable sequence embeddings for large-scale NLP tasks…

cs.CL2020★ 5 cited

Contrastive Distillation on Intermediate Representations for Language Model Compression

Siqi Sun, Zhe Gan, Yu Cheng +3

Existing language model compression methods mostly use a simple L2 loss to distill knowledge in the intermediate representations of a large BERT model to a smaller one. Although wi…

cs.CL2020★ 18 cited

Cluster-Former: Clustering-based Sparse Transformer for Long-Range Dependency Encoding

Shuohang Wang, Luowei Zhou, Zhe Gan +5

Transformer has become ubiquitous in the deep learning field. One of the key ingredients that destined its success is the self-attention mechanism, which allows fully-connected con…

cs.CL2020★ 10 cited

Accelerating Real-Time Question Answering via Question Generation

Yuwei Fang, Shuohang Wang, Zhe Gan +3

Although deep neural networks have achieved tremendous success for question answering (QA), they are still suffering from heavy computational and energy cost for real product deplo…

cs.CL2020★ 2 cited

FILTER: An Enhanced Fusion Method for Cross-lingual Language Understanding

Yuwei Fang, Shuohang Wang, Zhe Gan +2

Large-scale cross-lingual language models (LM), such as mBERT, Unicoder and XLM, have achieved great success in cross-lingual representation learning. However, when applied to zero…

q-bio.QM2020

Unsupervised and Supervised Structure Learning for Protein Contact Prediction

Siqi Sun

Protein contacts provide key information for the understanding of protein structure and function, and therefore contact prediction from sequences is an important problem. Recent re…