Papers by Huasha Zhao
Graph Convolution for Multimodal Information Extraction from Visually Rich Documents (N19-2)
Copied to clipboard
| Challenge: | Visually rich documents (VRDs) present information in the form of both text and vision. |
| Approach: | They propose a graph convolution based model to combine textual and visual information presented in VRDs. |
| Outcome: | The proposed model outperforms existing models on two real-world datasets. |
Improve Neural Entity Recognition via Multi-Task Data Selection and Constrained Decoding (N18-2)
Copied to clipboard
| Challenge: | Entity recognition is a widely benchmarked task in natural language processing . a neural architecture called BiLSTM-CRF is used to model the language sequences . |
| Approach: | They propose a neural architecture called BiLSTM-CRF to model the language sequences. |
| Outcome: | The proposed system achieves state-of-the-art on English entity recognition task and also in other languages. |