Search Results for author: Zhisong Zhang

Found 22 papers, 13 papers with code

On the Benefit of Syntactic Supervision for Cross-lingual Transfer in Semantic Role Labeling

1 code implementation EMNLP 2021 Zhisong Zhang, Emma Strubell, Eduard Hovy

Although recent developments in neural architectures and pre-trained representations have greatly increased state-of-the-art model performance on fully-supervised semantic role labeling (SRL), the task remains challenging for languages where supervised SRL training data are not abundant.

Cross-Lingual Transfer Semantic Role Labeling

Comparing Span Extraction Methods for Semantic Role Labeling

1 code implementation ACL (spnlp) 2021 Zhisong Zhang, Emma Strubell, Eduard Hovy

In this work, we empirically compare span extraction methods for the task of semantic role labeling (SRL).

Semantic Role Labeling

Towards More Efficient Insertion Transformer with Fractional Positional Encoding

no code implementations12 Dec 2021 Zhisong Zhang, Yizhe Zhang, Bill Dolan

Nevertheless, due to the incompatibility of absolute positional encoding and insertion-based generation schemes, it needs to refresh the encoding of every token in the generated partial hypotheses at each step, which could be costly.

Text Generation

Incorporating a Local Translation Mechanism into Non-autoregressive Translation

1 code implementation EMNLP 2020 Xiang Kong, Zhisong Zhang, Eduard Hovy

In this work, we introduce a novel local autoregressive translation (LAT) mechanism into non-autoregressive translation (NAT) models so as to capture local dependencies among tar-get outputs.

Machine Translation Translation

A Two-Step Approach for Implicit Event Argument Detection

no code implementations ACL 2020 Zhisong Zhang, Xiang Kong, Zhengzhong Liu, Xuezhe Ma, Eduard Hovy

It remains a challenge to detect implicit arguments, calling for more future work of document-level modeling for this task.

Cross-lingual Dependency Parsing with Unlabeled Auxiliary Languages

1 code implementation CONLL 2019 Wasi Uddin Ahmad, Zhisong Zhang, Xuezhe Ma, Kai-Wei Chang, Nanyun Peng

We conduct experiments on cross-lingual dependency parsing where we train a dependency parser on a source language and transfer it to a wide range of target languages.

Cross-Lingual Transfer Dependency Parsing +2

An Empirical Investigation of Structured Output Modeling for Graph-based Neural Dependency Parsing

1 code implementation ACL 2019 Zhisong Zhang, Xuezhe Ma, Eduard Hovy

In this paper, we investigate the aspect of structured output modeling for the state-of-the-art graph-based neural dependency parser (Dozat and Manning, 2017).

14 Dependency Parsing

Choosing Transfer Languages for Cross-Lingual Learning

1 code implementation ACL 2019 Yu-Hsiang Lin, Chian-Yu Chen, Jean Lee, Zirui Li, Yuyan Zhang, Mengzhou Xia, Shruti Rijhwani, Junxian He, Zhisong Zhang, Xuezhe Ma, Antonios Anastasopoulos, Patrick Littell, Graham Neubig

Cross-lingual transfer, where a high-resource transfer language is used to improve the accuracy of a low-resource task language, is now an invaluable tool for improving performance of natural language processing (NLP) on low-resource languages.

Cross-Lingual Transfer

Exploring Recombination for Efficient Decoding of Neural Machine Translation

1 code implementation EMNLP 2018 Zhisong Zhang, Rui Wang, Masao Utiyama, Eiichiro Sumita, Hai Zhao

In Neural Machine Translation (NMT), the decoder can capture the features of the entire prediction history with neural connections and representations.

Machine Translation Translation

A Transition-based System for Universal Dependency Parsing

no code implementations CONLL 2017 Hao Wang, Hai Zhao, Zhisong Zhang

This paper describes the system for our participation in the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies.

Transfer Learning Transition-Based Dependency Parsing

Fast and Accurate Neural Word Segmentation for Chinese

1 code implementation ACL 2017 Deng Cai, Hai Zhao, Zhisong Zhang, Yuan Xin, Yongjian Wu, Feiyue Huang

Neural models with minimal feature engineering have achieved competitive performance against traditional methods for the task of Chinese word segmentation.

Chinese Word Segmentation Feature Engineering

Adversarial Connective-exploiting Networks for Implicit Discourse Relation Classification

no code implementations ACL 2017 Lianhui Qin, Zhisong Zhang, Hai Zhao, Zhiting Hu, Eric P. Xing

Implicit discourse relation classification is of great challenge due to the lack of connectives as strong linguistic cues, which motivates the use of annotated implicit connectives to improve the recognition.

Classification General Classification +1

Implicit Discourse Relation Recognition with Context-aware Character-enhanced Embeddings

no code implementations COLING 2016 Lianhui Qin, Zhisong Zhang, Hai Zhao

For the task of implicit discourse relation recognition, traditional models utilizing manual features can suffer from data sparsity problem.

Machine Translation Question Answering +1

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