351 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Zhejiang UniversityCN124 papers
- Fudan UniversityCN73 papers
- Tsinghua UniversityCN46 papers
- Chinese Academy of SciencesCN45 papers
- University of Chinese Academy of SciencesCN39 papers
- Nanjing UniversityCN31 papers
- Peking UniversityCN26 papers
- University of Science and Technology of ChinaCN26 papers
- Vladimir State UniversityRU26 papers
- St Petersburg UniversityRU25 papers
- Collaborative Innovation Center of Advanced MicrostructuresCN24 papers
- Beihang UniversityCN21 papers
30 papers · 1 filter
Constituency Parsing using LLMs
Xuefeng Bai, Jialong Wu, Yulong Chen +4
Constituency parsing is a fundamental yet unsolved challenge in natural language processing. In this paper, we examine the potential of recent large language models (LLMs) to addre…
SMILE: Single-turn to Multi-turn Inclusive Language Expansion via ChatGPT for Mental Health Support
Huachuan Qiu, Hongliang He, Shuai Zhang +2
Developing specialized dialogue systems for mental health support requires multi-turn conversation data, which has recently garnered increasing attention. However, gathering and re…
Unsupervised Key Event Detection from Massive Text Corpora
Yunyi Zhang, Fang Guo, Jiaming Shen +1
Automated event detection from news corpora is a crucial task towards mining fast-evolving structured knowledge. As real-world events have different granularities, from the top-lev…
Iterative Network Pruning with Uncertainty Regularization for Lifelong Sentiment Classification
Binzong Geng, Min Yang, Fajie Yuan +3
Lifelong learning capabilities are crucial for sentiment classifiers to process continuous streams of opinioned information on the Web. However, performing lifelong learning is non…
DialogSum: A Real-Life Scenario Dialogue Summarization Dataset
Yulong Chen, Yang Liu, Liang Chen +1
Proposal of large-scale datasets has facilitated research on deep neural models for news summarization. Deep learning can also be potentially useful for spoken dialogue summarizati…
Can Generative Pre-trained Language Models Serve as Knowledge Bases for Closed-book QA?
Cunxiang Wang, Pai Liu, Yue Zhang
Recent work has investigated the interesting question using pre-trained language models (PLMs) as knowledge bases for answering open questions. However, existing work is limited in…
Semantic Representation for Dialogue Modeling
Xuefeng Bai, Yulong Chen, Linfeng Song +1
Although neural models have achieved competitive results in dialogue systems, they have shown limited ability in representing core semantics, such as ignoring important entities. T…
On Compositional Generalization of Neural Machine Translation
Yafu Li, Yongjing Yin, Yulong Chen +1
Modern neural machine translation (NMT) models have achieved competitive performance in standard benchmarks such as WMT. However, there still exist significant issues such as robus…
G-Transformer for Document-level Machine Translation
Guangsheng Bao, Yue Zhang, Zhiyang Teng +2
Document-level MT models are still far from satisfactory. Existing work extend translation unit from single sentence to multiple sentences. However, study shows that when we furthe…
Natural Language Inference in Context -- Investigating Contextual Reasoning over Long Texts
Hanmeng Liu, Leyang Cui, Jian Liu +1
Natural language inference (NLI) is a fundamental NLP task, investigating the entailment relationship between two texts. Popular NLI datasets present the task at sentence-level. Wh…
Dialogue State Induction Using Neural Latent Variable Models
Qingkai Min, Libo Qin, Zhiyang Teng +2
Dialogue state modules are a useful component in a task-oriented dialogue system. Traditional methods find dialogue states by manually labeling training corpora, upon which neural…
On Commonsense Cues in BERT for Solving Commonsense Tasks
Leyang Cui, Sijie Cheng, Yu Wu +1
BERT has been used for solving commonsense tasks such as CommonsenseQA. While prior research has found that BERT does contain commonsense information to some extent, there has been…
LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning
Jian Liu, Leyang Cui, Hanmeng Liu +3
Machine reading is a fundamental task for testing the capability of natural language understanding, which is closely related to human cognition in many aspects. With the rising of…
CoSDA-ML: Multi-Lingual Code-Switching Data Augmentation for Zero-Shot Cross-Lingual NLP
Libo Qin, Minheng Ni, Yue Zhang +1
Multi-lingual contextualized embeddings, such as multilingual-BERT (mBERT), have shown success in a variety of zero-shot cross-lingual tasks. However, these models are limited by h…
DRTS Parsing with Structure-Aware Encoding and Decoding
Qiankun Fu, Yue Zhang, Jiangming Liu +1
Discourse representation tree structure (DRTS) parsing is a novel semantic parsing task which has been concerned most recently. State-of-the-art performance can be achieved by a ne…
Exploiting Syntactic Structure for Better Language Modeling: A Syntactic Distance Approach
Wenyu Du, Zhouhan Lin, Yikang Shen +3
It is commonly believed that knowledge of syntactic structure should improve language modeling. However, effectively and computationally efficiently incorporating syntactic structu…
MuTual: A Dataset for Multi-Turn Dialogue Reasoning
Leyang Cui, Yu Wu, Shujie Liu +2
Non-task oriented dialogue systems have achieved great success in recent years due to largely accessible conversation data and the development of deep learning techniques. Given a…
News-Driven Stock Prediction With Attention-Based Noisy Recurrent State Transition
Xiao Liu, Heyan Huang, Yue Zhang +1
We consider direct modeling of underlying stock value movement sequences over time in the news-driven stock movement prediction. A recurrent state transition model is constructed,…
Investigating Typed Syntactic Dependencies for Targeted Sentiment Classification Using Graph Attention Neural Network
Xuefeng Bai, Pengbo Liu, Yue Zhang
Targeted sentiment classification predicts the sentiment polarity on given target mentions in input texts. Dominant methods employ neural networks for encoding the input sentence a…
Modeling Global and Local Node Contexts for Text Generation from Knowledge Graphs
Leonardo F. R. Ribeiro, Yue Zhang, Claire Gardent +1
Recent graph-to-text models generate text from graph-based data using either global or local aggregation to learn node representations. Global node encoding allows explicit communi…
A Pilot Study for Chinese SQL Semantic Parsing
Qingkai Min, Yuefeng Shi, Yue Zhang
The task of semantic parsing is highly useful for dialogue and question answering systems. Many datasets have been proposed to map natural language text into SQL, among which the r…
Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning
Zhijiang Guo, Yan Zhang, Zhiyang Teng +1
We focus on graph-to-sequence learning, which can be framed as transducing graph structures to sequences for text generation. To capture structural information associated with grap…
Hierarchically-Refined Label Attention Network for Sequence Labeling
Leyang Cui, Yue Zhang
CRF has been used as a powerful model for statistical sequence labeling. For neural sequence labeling, however, BiLSTM-CRF does not always lead to better results compared with BiLS…
Investigating Self-Attention Network for Chinese Word Segmentation
Leilei Gan, Yue Zhang
Neural network has become the dominant method for Chinese word segmentation. Most existing models cast the task as sequence labeling, using BiLSTM-CRF for representing the input an…