activity
20202023
most citedSequence Level Contrastive Learning for Text Summarization

23 citations · 36 across the 6 of their papers we have counts for

collaborators

6 papers

cs.RO2023★ 3 cited

LAGOON: Language-Guided Motion Control

Shusheng Xu, Huaijie Wang, Jiaxuan Gao +3

We aim to control a robot to physically behave in the real world following any high-level language command like "cartwheel" or "kick". Although human motion datasets exist, this ta…

cs.CL2021★ 2 cited

Native Chinese Reader: A Dataset Towards Native-Level Chinese Machine Reading Comprehension

Shusheng Xu, Yichen Liu, Xiaoyu Yi +3

We present Native Chinese Reader (NCR), a new machine reading comprehension (MRC) dataset with particularly long articles in both modern and classical Chinese. NCR is collected fro…

cs.LG2021

A Benchmark for Low-Switching-Cost Reinforcement Learning

Shusheng Xu, Yancheng Liang, Yunfei Li +2

A ubiquitous requirement in many practical reinforcement learning (RL) applications, including medical treatment, recommendation system, education and robotics, is that the deploye…

q-bio.QM2021★ 3 cited

PhyloTransformer: A Discriminative Model for Mutation Prediction Based on a Multi-head Self-attention Mechanism

Yingying Wu, Shusheng Xu, Shing-Tung Yau +1

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused an ongoing pandemic infecting 219 million people as of 10/19/21, with a 3.6% mortality rate. Natural selecti…

cs.CL2021★ 23 cited

Sequence Level Contrastive Learning for Text Summarization

Shusheng Xu, Xingxing Zhang, Yi Wu +1

Contrastive learning models have achieved great success in unsupervised visual representation learning, which maximize the similarities between feature representations of different…

cs.CL2020★ 5 cited

Unsupervised Extractive Summarization by Pre-training Hierarchical Transformers

Shusheng Xu, Xingxing Zhang, Yi Wu +2

Unsupervised extractive document summarization aims to select important sentences from a document without using labeled summaries during training. Existing methods are mostly graph…