19 citations · 55 across the 8 of their papers we have counts for
12 papers
DialogConv: A Lightweight Fully Convolutional Network for Multi-view Response Selection
Yongkang Liu, Shi Feng, Wei Gao +2
Current end-to-end retrieval-based dialogue systems are mainly based on Recurrent Neural Networks or Transformers with attention mechanisms. Although promising results have been ac…
ERNIE-Layout: Layout Knowledge Enhanced Pre-training for Visually-rich Document Understanding
Qiming Peng, Yinxu Pan, Wenjin Wang +12
Recent years have witnessed the rise and success of pre-training techniques in visually-rich document understanding. However, most existing methods lack the systematic mining and u…
ERNIE-mmLayout: Multi-grained MultiModal Transformer for Document Understanding
Wenjin Wang, Zhengjie Huang, Bin Luo +8
Recent efforts of multimodal Transformers have improved Visually Rich Document Understanding (VrDU) tasks via incorporating visual and textual information. However, existing approa…
ERNIE-Search: Bridging Cross-Encoder with Dual-Encoder via Self On-the-fly Distillation for Dense Passage Retrieval
Yuxiang Lu, Yiding Liu, Jiaxiang Liu +8
Neural retrievers based on pre-trained language models (PLMs), such as dual-encoders, have achieved promising performance on the task of open-domain question answering (QA). Their…
Simple and Effective Relation-based Embedding Propagation for Knowledge Representation Learning
Huijuan Wang, Siming Dai, Weiyue Su +7
Relational graph neural networks have garnered particular attention to encode graph context in knowledge graphs (KGs). Although they achieved competitive performance on small KGs,…
ERNIE-SPARSE: Learning Hierarchical Efficient Transformer Through Regularized Self-Attention
Yang Liu, Jiaxiang Liu, Li Chen +7
Sparse Transformer has recently attracted a lot of attention since the ability for reducing the quadratic dependency on the sequence length. We argue that two factors, information…