246 citations · 1.2k across the 71 of their papers we have counts for
14 papers · 1 filter
DMRM: A Dual-channel Multi-hop Reasoning Model for Visual Dialog
Feilong Chen, Fandong Meng, Jiaming Xu +3
Visual Dialog is a vision-language task that requires an AI agent to engage in a conversation with humans grounded in an image. It remains a challenging task since it requires the…
Document Sub-structure in Neural Machine Translation
Radina Dobreva, Jie Zhou, Rachel Bawden
Current approaches to machine translation (MT) either translate sentences in isolation, disregarding the context they appear in, or model context at the level of the full document,…
Multi-Zone Unit for Recurrent Neural Networks
Fandong Meng, Jinchao Zhang, Yang Liu +1
Recurrent neural networks (RNNs) have been widely used to deal with sequence learning problems. The input-dependent transition function, which folds new observations into hidden st…
Guiding Non-Autoregressive Neural Machine Translation Decoding with Reordering Information
Qiu Ran, Yankai Lin, Peng Li +1
Non-autoregressive neural machine translation (NAT) generates each target word in parallel and has achieved promising inference acceleration. However, existing NAT models still hav…
Semantic Graph Convolutional Network for Implicit Discourse Relation Classification
Yingxue Zhang, Ping Jian, Fandong Meng +3
Implicit discourse relation classification is of great importance for discourse parsing, but remains a challenging problem due to the absence of explicit discourse connectives comm…
FewRel 2.0: Towards More Challenging Few-Shot Relation Classification
Tianyu Gao, Xu Han, Hao Zhu +4
We present FewRel 2.0, a more challenging task to investigate two aspects of few-shot relation classification models: (1) Can they adapt to a new domain with only a handful of inst…
NumNet: Machine Reading Comprehension with Numerical Reasoning
Qiu Ran, Yankai Lin, Peng Li +2
Numerical reasoning, such as addition, subtraction, sorting and counting is a critical skill in human's reading comprehension, which has not been well considered in existing machin…
CM-Net: A Novel Collaborative Memory Network for Spoken Language Understanding
Yijin Liu, Fandong Meng, Jinchao Zhang +3
Spoken Language Understanding (SLU) mainly involves two tasks, intent detection and slot filling, which are generally modeled jointly in existing works. However, most existing mode…
Unsupervised Paraphrasing by Simulated Annealing
Xianggen Liu, Lili Mou, Fandong Meng +3
Unsupervised paraphrase generation is a promising and important research topic in natural language processing. We propose UPSA, a novel approach that accomplishes Unsupervised Para…
Measuring and Relieving the Over-smoothing Problem for Graph Neural Networks from the Topological View
Deli Chen, Yankai Lin, Wei Li +3
Graph Neural Networks (GNNs) have achieved promising performance on a wide range of graph-based tasks. Despite their success, one severe limitation of GNNs is the over-smoothing is…
Enhancing Context Modeling with a Query-Guided Capsule Network for Document-level Translation
Zhengxin Yang, Jinchao Zhang, Fandong Meng +3
Context modeling is essential to generate coherent and consistent translation for Document-level Neural Machine Translations. The widely used method for document-level translation…
A Novel Aspect-Guided Deep Transition Model for Aspect Based Sentiment Analysis
Yunlong Liang, Fandong Meng, Jinchao Zhang +3
Aspect based sentiment analysis (ABSA) aims to identify the sentiment polarity towards the given aspect in a sentence, while previous models typically exploit an aspect-independent…
Retrieving Sequential Information for Non-Autoregressive Neural Machine Translation
Chenze Shao, Yang Feng, Jinchao Zhang +3
Non-Autoregressive Transformer (NAT) aims to accelerate the Transformer model through discarding the autoregressive mechanism and generating target words independently, which fails…
A Dual Reinforcement Learning Framework for Unsupervised Text Style Transfer
Fuli Luo, Peng Li, Jie Zhou +4
Unsupervised text style transfer aims to transfer the underlying style of text but keep its main content unchanged without parallel data. Most existing methods typically follow two…