189 citations · 346 across the 19 of their papers we have counts for
20 papers
Syntactic and Semantic-driven Learning for Open Information Extraction
Jialong Tang, Yaojie Lu, Hongyu Lin +4
One of the biggest bottlenecks in building accurate, high coverage neural open IE systems is the need for large labelled corpora. The diversity of open domain corpora and the varie…
Benchmarking Knowledge-Enhanced Commonsense Question Answering via Knowledge-to-Text Transformation
Ning Bian, Xianpei Han, Bo Chen +1
A fundamental ability of humans is to utilize commonsense knowledge in language understanding and question answering. In recent years, many knowledge-enhanced Commonsense Question…
From Bag of Sentences to Document: Distantly Supervised Relation Extraction via Machine Reading Comprehension
Lingyong Yan, Xianpei Han, Le Sun +2
Distant supervision (DS) is a promising approach for relation extraction but often suffers from the noisy label problem. Traditional DS methods usually represent an entity pair as…
ISCAS at SemEval-2020 Task 5: Pre-trained Transformers for Counterfactual Statement Modeling
Yaojie Lu, Annan Li, Hongyu Lin +2
ISCAS participated in two subtasks of SemEval 2020 Task 5: detecting counterfactual statements and detecting antecedent and consequence. This paper describes our system which is ba…
End-to-End Neural Event Coreference Resolution
Yaojie Lu, Hongyu Lin, Jialong Tang +2
Traditional event coreference systems usually rely on pipeline framework and hand-crafted features, which often face error propagation problem and have poor generalization ability.…
BERT-QE: Contextualized Query Expansion for Document Re-ranking
Zhi Zheng, Kai Hui, Ben He +3
Query expansion aims to mitigate the mismatch between the language used in a query and in a document. However, query expansion methods can suffer from introducing non-relevant info…
Modeling Voting for System Combination in Machine Translation
Xuancheng Huang, Jiacheng Zhang, Zhixing Tan +5
System combination is an important technique for combining the hypotheses of different machine translation systems to improve translation performance. Although early statistical ap…
A Rigorous Study on Named Entity Recognition: Can Fine-tuning Pretrained Model Lead to the Promised Land?
Hongyu Lin, Yaojie Lu, Jialong Tang +4
Fine-tuning pretrained model has achieved promising performance on standard NER benchmarks. Generally, these benchmarks are blessed with strong name regularity, high mention covera…
Neural Abstractive Summarization with Structural Attention
Tanya Chowdhury, Sachin Kumar, Tanmoy Chakraborty
Attentional, RNN-based encoder-decoder architectures have achieved impressive performance on abstractive summarization of news articles. However, these methods fail to account for…
Overview of the CCKS 2019 Knowledge Graph Evaluation Track: Entity, Relation, Event and QA
Xianpei Han, Zhichun Wang, Jiangtao Zhang +22
Knowledge graph models world knowledge as concepts, entities, and the relationships between them, which has been widely used in many real-world tasks. CCKS 2019 held an evaluation…
CAIL2019-SCM: A Dataset of Similar Case Matching in Legal Domain
Chaojun Xiao, Haoxi Zhong, Zhipeng Guo +8
In this paper, we introduce CAIL2019-SCM, Chinese AI and Law 2019 Similar Case Matching dataset. CAIL2019-SCM contains 8,964 triplets of cases published by the Supreme People's Cou…
Cost-sensitive Regularization for Label Confusion-aware Event Detection
Hongyu Lin, Yaojie Lu, Xianpei Han +1
In supervised event detection, most of the mislabeling occurs between a small number of confusing type pairs, including trigger-NIL pairs and sibling sub-types of the same coarse t…
Sequence-to-Nuggets: Nested Entity Mention Detection via Anchor-Region Networks
Hongyu Lin, Yaojie Lu, Xianpei Han +1
Sequential labeling-based NER approaches restrict each word belonging to at most one entity mention, which will face a serious problem when recognizing nested entity mentions. In t…
Sentence Rewriting for Semantic Parsing
Bo Chen, Le Sun, Xianpei Han +1
A major challenge of semantic parsing is the vocabulary mismatch problem between natural language and target ontology. In this paper, we propose a sentence rewriting based semantic…
Overview of CAIL2018: Legal Judgment Prediction Competition
Haoxi Zhong, Chaojun Xiao, Zhipeng Guo +8
In this paper, we give an overview of the Legal Judgment Prediction (LJP) competition at Chinese AI and Law challenge (CAIL2018). This competition focuses on LJP which aims to pred…
Sequence-to-Action: End-to-End Semantic Graph Generation for Semantic Parsing
Bo Chen, Le Sun, Xianpei Han
This paper proposes a neural semantic parsing approach -- Sequence-to-Action, which models semantic parsing as an end-to-end semantic graph generation process. Our method simultane…
CAIL2018: A Large-Scale Legal Dataset for Judgment Prediction
Chaojun Xiao, Haoxi Zhong, Zhipeng Guo +8
In this paper, we introduce the \textbf{C}hinese \textbf{AI} and \textbf{L}aw challenge dataset (CAIL2018), the first large-scale Chinese legal dataset for judgment prediction. \da…
Adaptive Scaling for Sparse Detection in Information Extraction
Hongyu Lin, Yaojie Lu, Xianpei Han +1
This paper focuses on detection tasks in information extraction, where positive instances are sparsely distributed and models are usually evaluated using F-measure on positive clas…
Nugget Proposal Networks for Chinese Event Detection
Hongyu Lin, Yaojie Lu, Xianpei Han +1
Neural network based models commonly regard event detection as a word-wise classification task, which suffer from the mismatch problem between words and event triggers, especially…
Variational Recurrent Neural Machine Translation
Jinsong Su, Shan Wu, Deyi Xiong +3
Partially inspired by successful applications of variational recurrent neural networks, we propose a novel variational recurrent neural machine translation (VRNMT) model in this pa…