Chang Liu


2021

pdf bib
字里行间的道德:中文文本道德句识别研究(Morality Between the Lines: Research on Identification of Chinese Moral Sentence)
Shiya Peng (彭诗雅) | Chang Liu (刘畅) | Yayue Deng (邓雅月) | Dong Yu (于东)
Proceedings of the 20th Chinese National Conference on Computational Linguistics

“随着人工智能的发展,越来越多的研究开始关注人工智能伦理。在NLP领域,道德自动识别作为研究分析文本中的道德的一项重要任务,近年来开始受到研究者的关注。该任务旨在识别文本中的道德片段,其对自然语言处理的道德相关的下游任务如偏见识别消除、判定模型隐形歧视等具有重要意义。与英文相比,目前面向中文的道德识别研究开展缓慢,其主要原因是至今还没有较大型的道德中文数据集为研究提供数据。为解决上述问题,本文在中文语料上进行了中文道德句的标注工作,并初步对识别中文文本道德句进行探索。我们首先构建了国内首个10万级别的中文道德句数据集,然后本文提出了利用流行的几种机器学习方法探究识别中文道德句任务的效果。此外,我们还探索了利用额外知识辅助的方法,对中文道德句的识别任务进行了进一步的探究。”

pdf bib
BioGen: Generating Biography Summary under Table Guidance on Wikipedia
Shen Gao | Xiuying Chen | Chang Liu | Dongyan Zhao | Rui Yan
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021

2020

pdf bib
BLCU-NLP at SemEval-2020 Task 5: Data Augmentation for Efficient Counterfactual Detecting
Chang Liu | Dong Yu
Proceedings of the Fourteenth Workshop on Semantic Evaluation

Counterfactuals describe events counter to facts and hence naturally involve common sense, knowledge, and reasoning. SemEval 2020 task 5 is focusing on this field. We participate in the subtask 1 and we use BERT as our system. Our Innovations are feature extraction and data augmentation. We extract and summarize features of counterfactual statements, augment counterfactual examples in training set with the help of these features, and two general methods of data augmentation is experimented in our work. We demonstrate the effectiveness of our approaches, which achieves 0.95 of subtask 1 in F1 while using only a subset of giving training set to fine-tune the BERT model, and our official submission achieves F1 0.802, which ranks us 16th in the competition.

pdf bib
基于跨语言双语预训练及Bi-LSTM的汉-越平行句对抽取方法(Chinese-Vietnamese Parallel Sentence Pair Extraction Method Based on Cross-lingual Bilingual Pre-training and Bi-LSTM)
Chang Liu (刘畅) | Shengxiang Gao (高盛祥) | Zhengtao Yu (余正涛) | Yuxin Huang (黄于欣) | Congcong You (尤丛丛)
Proceedings of the 19th Chinese National Conference on Computational Linguistics

汉越平行句对抽取是缓解汉越平行语料库数据稀缺的重要方法。平行句对抽取可转换为同一语义空间下的句子相似性分类任务,其核心在于双语语义空间对齐。传统语义空间对齐方法依赖于大规模的双语平行语料,越南语作为低资源语言获取大规模平行语料相对困难。针对这个问题本文提出一种利用种子词典进行跨语言双语预训练及Bi-LSTM(Bi-directional Long Short-Term Memory)的汉-越平行句对抽取方法。预训练中仅需要大量的汉越单语和一个汉越种子词典,通过利用汉越种子词典将汉越双语映射到公共语义空间进行词对齐。再利用Bi-LSTM和CNN(Convolutional Neural Networks)分别提取句子的全局特征和局部特征从而最大化表示汉-越句对之间的语义相关性。实验结果表明,本文模型在F1得分上提升7.1%,优于基线模型。

pdf bib
面向人工智能伦理计算的中文道德词典构建方法研究(Construction of a Chinese Moral Dictionary for Artificial Intelligence Ethical Computing)
Hongrui Wang (王弘睿) | Chang Liu (刘畅) | Dong Yu (于东)
Proceedings of the 19th Chinese National Conference on Computational Linguistics

道德词典资源的建设是人工智能伦理计算的一个研究重点。由于道德行为复杂多样,现有的英文道德词典分类体系并不完善,而中文方面目前尚未有相关的词典资源,理论体系和构建方法仍待探究。针对以上问题,该文提出了面向人工智能伦理计算的中文道德词典构建任务,设计了四类标签和四种类型,得到包含25,012个词的中文道德词典资源。实验结果表明,该词典资源不仅能够使机器学会道德知识,判断词的道德标签和类型,而且能够为句子级别的道德文本分析提供数据支持。

2019

pdf bib
Kingsoft’s Neural Machine Translation System for WMT19
Xinze Guo | Chang Liu | Xiaolong Li | Yiran Wang | Guoliang Li | Feng Wang | Zhitao Xu | Liuyi Yang | Li Ma | Changliang Li
Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1)

This paper describes the Kingsoft AI Lab’s submission to the WMT2019 news translation shared task. We participated in two language directions: English-Chinese and Chinese-English. For both language directions, we trained several variants of Transformer models using the provided parallel data enlarged with a large quantity of back-translated monolingual data. The best translation result was obtained with ensemble and reranking techniques. According to automatic metrics (BLEU) our Chinese-English system reached the second highest score, and our English-Chinese system reached the second highest score for this subtask.

2012

pdf bib
Character-Level Machine Translation Evaluation for Languages with Ambiguous Word Boundaries
Chang Liu | Hwee Tou Ng
Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

pdf bib
Combining Coherence Models and Machine Translation Evaluation Metrics for Summarization Evaluation
Ziheng Lin | Chang Liu | Hwee Tou Ng | Min-Yen Kan
Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

2011

pdf bib
TESLA at WMT 2011: Translation Evaluation and Tunable Metric
Daniel Dahlmeier | Chang Liu | Hwee Tou Ng
Proceedings of the Sixth Workshop on Statistical Machine Translation

pdf bib
Better Evaluation Metrics Lead to Better Machine Translation
Chang Liu | Daniel Dahlmeier | Hwee Tou Ng
Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing

2010

pdf bib
TESLA: Translation Evaluation of Sentences with Linear-Programming-Based Analysis
Chang Liu | Daniel Dahlmeier | Hwee Tou Ng
Proceedings of the Joint Fifth Workshop on Statistical Machine Translation and MetricsMATR

pdf bib
PEM: A Paraphrase Evaluation Metric Exploiting Parallel Texts
Chang Liu | Daniel Dahlmeier | Hwee Tou Ng
Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing

2009

pdf bib
The NUS statistical machine translation system for IWSLT 2009
Preslav Nakov | Chang Liu | Wei Lu | Hwee Tou Ng
Proceedings of the 6th International Workshop on Spoken Language Translation: Evaluation Campaign

We describe the system developed by the team of the National University of Singapore for the Chinese-English BTEC task of the IWSLT 2009 evaluation campaign. We adopted a state-of-the-art phrase-based statistical machine translation approach and focused on experiments with different Chinese word segmentation standards. In our official submission, we trained a separate system for each segmenter and we combined the outputs in a subsequent re-ranking step. Given the small size of the training data, we further re-trained the system on the development data after tuning. The evaluation results show that both strategies yield sizeable and consistent improvements in translation quality.

2007

pdf bib
Learning Predictive Structures for Semantic Role Labeling of NomBank
Chang Liu | Hwee Tou Ng
Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics