activity
20142021
most citedDecoupling Long- and Short-Term Patterns in Spatiotemporal Inference

17 citations · 45 across the 8 of their papers we have counts for

collaborators

8 papers

cs.LG2021★ 17 cited

Decoupling Long- and Short-Term Patterns in Spatiotemporal Inference

Junfeng Hu, Yuxuan Liang, Zhencheng Fan +3

Sensors are the key to environmental monitoring, which impart benefits to smart cities in many aspects, such as providing real-time air quality information to assist human decision…

cs.CL2020★ 3 cited

Incorporate Semantic Structures into Machine Translation Evaluation via UCCA

Jin Xu, Yinuo Guo, Junfeng Hu

Copying mechanism has been commonly used in neural paraphrasing networks and other text generation tasks, in which some important words in the input sequence are preserved in the o…

cs.CV2019★ 8 cited

Predicting Long-Term Skeletal Motions by a Spatio-Temporal Hierarchical Recurrent Network

Junfeng Hu, Zhencheng Fan, Jun Liao +1

The primary goal of skeletal motion prediction is to generate future motion by observing a sequence of 3D skeletons. A key challenge in motion prediction is the fact that a motion…

cs.CL2018

Understanding and Improving Multi-Sense Word Embeddings via Extended Robust Principal Component Analysis

Haoyue Shi, Yuqi Sun, Junfeng Hu

Unsupervised learned representations of polysemous words generate a large of pseudo multi senses since unsupervised methods are overly sensitive to contextual variations. In this p…

cs.CL2017★ 7 cited

Context Aware Document Embedding

Zhaocheng Zhu, Junfeng Hu

Recently, doc2vec has achieved excellent results in different tasks. In this paper, we present a context aware variant of doc2vec. We introduce a novel weight estimating mechanism…

cs.CL2017

Max-Cosine Matching Based Neural Models for Recognizing Textual Entailment

Zhipeng Xie, Junfeng Hu

Recognizing textual entailment is a fundamental task in a variety of text mining or natural language processing applications. This paper proposes a simple neural model for RTE prob…