Hui Wang


CLLE: A Benchmark for Continual Language Learning Evaluation in Multilingual Machine Translation
Han Zhang | Sheng Zhang | Yang Xiang | Bin Liang | Jinsong Su | Zhongjian Miao | Hui Wang | Ruifeng Xu
Findings of the Association for Computational Linguistics: EMNLP 2022

Continual Language Learning (CLL) in multilingual translation is inevitable when new languages are required to be translated. Due to the lack of unified and generalized benchmarks, the evaluation of existing methods is greatly influenced by experimental design which usually has a big gap from the industrial demands. In this work, we propose the first Continual Language Learning Evaluation benchmark CLLE in multilingual translation. CLLE consists of a Chinese-centric corpus — CN-25 and two CLL tasks — the close-distance language continual learning task and the language family continual learning task designed for real and disparate demands. Different from existing translation benchmarks, CLLE considers several restrictions for CLL, including domain distribution alignment, content overlap, language diversity, and the balance of corpus. Furthermore, we propose a novel framework COMETA based on Constrained Optimization and META-learning to alleviate catastrophic forgetting and dependency on history training data by using a meta-model to retain the important parameters for old languages. Our experiments prove that CLLE is a challenging CLL benchmark and that our proposed method is effective when compared with other strong baselines. Due to the construction of the corpus, the task designing and the evaluation method are independent of the centric language, we also construct and release the English-centric corpus EN-25 to facilitate academic research.


FuRongWang at SemEval-2017 Task 3: Deep Neural Networks for Selecting Relevant Answers in Community Question Answering
Sheng Zhang | Jiajun Cheng | Hui Wang | Xin Zhang | Pei Li | Zhaoyun Ding
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)

We describes deep neural networks frameworks in this paper to address the community question answering (cQA) ranking task (SemEval-2017 task 3). Convolutional neural networks and bi-directional long-short term memory networks are applied in our methods to extract semantic information from questions and answers (comments). In addition, in order to take the full advantage of question-comment semantic relevance, we deploy interaction layer and augmented features before calculating the similarity. The results show that our methods have the great effectiveness for both subtask A and subtask C.


Identification of Social Acts in Dialogue
David Bracewell | Marc Tomlinson | Hui Wang
Proceedings of COLING 2012


An Exploration into the Use of Contextual Document Clustering for Cluster Sentiment Analysis
Niall Rooney | Hui Wang | Fiona Browne | Fergal Monaghan | Jann Müller | Alan Sergeant | Zhiwei Lin | Philip Taylor | Vladimir Dobrynin
Proceedings of the International Conference Recent Advances in Natural Language Processing 2011


Lexical Semantics-Syntactic Model for Defining and Subcategorizing Attribute Noun Class
Xiaopeng Bai | Hui Wang
Proceedings of the 24th Pacific Asia Conference on Language, Information and Computation


從構式語法理論看漢語詞義研究 (A Construction-Bsed Approach to Chinese Lexical Semantics) [In Chinese]
Hui Wang
International Journal of Computational Linguistics & Chinese Language Processing, Volume 10, Number 4, December 2005: Special Issue on Selected Papers from CLSW-5


A Large-scale Lexical Semantic Knowledge-base of Chinese
Hui Wang | Shiwen Yu
Proceedings of the 17th Pacific Asia Conference on Language, Information and Computation

The semantic Knowledge-base of Contemporary Chinese and Its Applications in WSD
Hui Wang | Shiwen Yu
Proceedings of the Second SIGHAN Workshop on Chinese Language Processing


基於組合特徵的漢語名詞詞義消歧 (A Study on Noun Sense Disambiguation Based on Syntagmatic Features) [In Chinese]
Hui Wang
International Journal of Computational Linguistics & Chinese Language Processing, Volume 7, Number 2, August 2002: Special Issue on Computational Chinese Lexical Semantics