Search Results for author: Degen Huang

Found 16 papers, 6 papers with code

Lexicon-Based Graph Convolutional Network for Chinese Word Segmentation

no code implementations Findings (EMNLP) 2021 Kaiyu Huang, Hao Yu, Junpeng Liu, Wei Liu, Jingxiang Cao, Degen Huang

Experimental results on five benchmarks and four cross-domain datasets show the lexicon-based graph convolutional network successfully captures the information of candidate words and helps to improve performance on the benchmarks (Bakeoff-2005 and CTB6) and the cross-domain datasets (SIGHAN-2010).

Chinese Word Segmentation

Exploring Better Text Image Translation with Multimodal Codebook

1 code implementation27 May 2023 Zhibin Lan, Jiawei Yu, Xiang Li, Wen Zhang, Jian Luan, Bin Wang, Degen Huang, Jinsong Su

Text image translation (TIT) aims to translate the source texts embedded in the image to target translations, which has a wide range of applications and thus has important research value.

Machine Translation Optical Character Recognition +2

BigVideo: A Large-scale Video Subtitle Translation Dataset for Multimodal Machine Translation

1 code implementation23 May 2023 Liyan Kang, Luyang Huang, Ningxin Peng, Peihao Zhu, Zewei Sun, Shanbo Cheng, Mingxuan Wang, Degen Huang, Jinsong Su

We also introduce two deliberately designed test sets to verify the necessity of visual information: Ambiguous with the presence of ambiguous words, and Unambiguous in which the text context is self-contained for translation.

Contrastive Learning Multimodal Machine Translation +3

Towards Robust k-Nearest-Neighbor Machine Translation

3 code implementations17 Oct 2022 Hui Jiang, Ziyao Lu, Fandong Meng, Chulun Zhou, Jie zhou, Degen Huang, Jinsong Su

Meanwhile we inject two types of perturbations into the retrieved pairs for robust training.

Machine Translation NMT +1

Exploring Dynamic Selection of Branch Expansion Orders for Code Generation

1 code implementation ACL 2021 Hui Jiang, Chulun Zhou, Fandong Meng, Biao Zhang, Jie zhou, Degen Huang, Qingqiang Wu, Jinsong Su

Due to the great potential in facilitating software development, code generation has attracted increasing attention recently.

Code Generation

Combining Context and Knowledge Representations for Chemical-Disease Relation Extraction

no code implementations23 Dec 2019 Huiwei Zhou, Yunlong Yang, Shixian Ning, Zhuang Liu, Chengkun Lang, Yingyu Lin, Degen Huang

KBs contain huge amounts of structured information about entities and relationships, therefore plays a pivotal role in chemical-disease relation (CDR) extraction.

Relation Relation Extraction

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