27 citations · 82 across the 30 of their papers we have counts for
30 papers
Query Structure Modeling for Inductive Logical Reasoning Over Knowledge Graphs
Siyuan Wang, Zhongyu Wei, Meng Han +4
Logical reasoning over incomplete knowledge graphs to answer complex logical queries is a challenging task. With the emergence of new entities and relations in constantly evolving…
Locate Then Ask: Interpretable Stepwise Reasoning for Multi-hop Question Answering
Siyuan Wang, Zhongyu Wei, Zhihao Fan +2
Multi-hop reasoning requires aggregating multiple documents to answer a complex question. Existing methods usually decompose the multi-hop question into simpler single-hop question…
A Benchmark for Automatic Medical Consultation System: Frameworks, Tasks and Datasets
Wei Chen, Zhiwei Li, Hongyi Fang +7
In recent years, interest has arisen in using machine learning to improve the efficiency of automatic medical consultation and enhance patient experience. In this article, we propo…
Learning Implicit Sentiment in Aspect-based Sentiment Analysis with Supervised Contrastive Pre-Training
Zhengyan Li, Yicheng Zou, Chong Zhang +2
Aspect-based sentiment analysis aims to identify the sentiment polarity of a specific aspect in product reviews. We notice that about 30% of reviews do not contain obvious opinion…
Plug-Tagger: A Pluggable Sequence Labeling Framework Using Language Models
Xin Zhou, Ruotian Ma, Tao Gui +3
Plug-and-play functionality allows deep learning models to adapt well to different tasks without requiring any parameters modified. Recently, prefix-tuning was shown to be a plug-a…
SAM: A Self-adaptive Attention Module for Context-Aware Recommendation System
Jiabin Liu, Zheng Wei, Zhengpin Li +4
Recently, textual information has been proved to play a positive role in recommendation systems. However, most of the existing methods only focus on representation learning of text…
Low-Resource Dialogue Summarization with Domain-Agnostic Multi-Source Pretraining
Yicheng Zou, Bolin Zhu, Xingwu Hu +2
With the rapid increase in the volume of dialogue data from daily life, there is a growing demand for dialogue summarization. Unfortunately, training a large summarization model is…
A Partition Filter Network for Joint Entity and Relation Extraction
Zhiheng Yan, Chong Zhang, Jinlan Fu +2
In joint entity and relation extraction, existing work either sequentially encode task-specific features, leading to an imbalance in inter-task feature interaction where features e…
Heterogeneous Graph Neural Networks for Keyphrase Generation
Jiacheng Ye, Ruijian Cai, Tao Gui +1
The encoder-decoder framework achieves state-of-the-art results in keyphrase generation (KG) tasks by predicting both present keyphrases that appear in the source document and abse…
Thinking Clearly, Talking Fast: Concept-Guided Non-Autoregressive Generation for Open-Domain Dialogue Systems
Yicheng Zou, Zhihua Liu, Xingwu Hu +1
Human dialogue contains evolving concepts, and speakers naturally associate multiple concepts to compose a response. However, current dialogue models with the seq2seq framework lac…
Template-free Prompt Tuning for Few-shot NER
Ruotian Ma, Xin Zhou, Tao Gui +4
Prompt-based methods have been successfully applied in sentence-level few-shot learning tasks, mostly owing to the sophisticated design of templates and label words. However, when…
SENT: Sentence-level Distant Relation Extraction via Negative Training
Ruotian Ma, Tao Gui, Linyang Li +3
Distant supervision for relation extraction provides uniform bag labels for each sentence inside the bag, while accurate sentence labels are important for downstream applications t…
One2Set: Generating Diverse Keyphrases as a Set
Jiacheng Ye, Tao Gui, Yichao Luo +2
Recently, the sequence-to-sequence models have made remarkable progress on the task of keyphrase generation (KG) by concatenating multiple keyphrases in a predefined order as a tar…
Who Responded to Whom: The Joint Effects of Latent Topics and Discourse in Conversation Structure
Lu Ji, Jing Li, Zhongyu Wei +2
Numerous online conversations are produced on a daily basis, resulting in a pressing need to conversation understanding. As a basis to structure a discussion, we identify the respo…
Larger-Context Tagging: When and Why Does It Work?
Jinlan Fu, Liangjing Feng, Qi Zhang +2
The development of neural networks and pretraining techniques has spawned many sentence-level tagging systems that achieved superior performance on typical benchmarks. However, a r…
Keyphrase Generation with Fine-Grained Evaluation-Guided Reinforcement Learning
Yichao Luo, Yige Xu, Jiacheng Ye +2
Aiming to generate a set of keyphrases, Keyphrase Generation (KG) is a classical task for capturing the central idea from a given document. Based on Seq2Seq models, the previous re…
Uncertainty-Aware Label Refinement for Sequence Labeling
Tao Gui, Jiacheng Ye, Qi Zhang +4
Conditional random fields (CRF) for label decoding has become ubiquitous in sequence labeling tasks. However, the local label dependencies and inefficient Viterbi decoding have alw…
SenSeNet: Neural Keyphrase Generation with Document Structure
Yichao Luo, Zhengyan Li, Bingning Wang +3
Keyphrase Generation (KG) is the task of generating central topics from a given document or literary work, which captures the crucial information necessary to understand the conten…
RethinkCWS: Is Chinese Word Segmentation a Solved Task?
Jinlan Fu, Pengfei Liu, Qi Zhang +1
The performance of the Chinese Word Segmentation (CWS) systems has gradually reached a plateau with the rapid development of deep neural networks, especially the successful use of…
Topic-Oriented Spoken Dialogue Summarization for Customer Service with Saliency-Aware Topic Modeling
Yicheng Zou, Lujun Zhao, Yangyang Kang +7
In a customer service system, dialogue summarization can boost service efficiency by automatically creating summaries for long spoken dialogues in which customers and agents try to…
Unsupervised Summarization for Chat Logs with Topic-Oriented Ranking and Context-Aware Auto-Encoders
Yicheng Zou, Jun Lin, Lujun Zhao +6
Automatic chat summarization can help people quickly grasp important information from numerous chat messages. Unlike conventional documents, chat logs usually have fragmented and e…
Tasty Burgers, Soggy Fries: Probing Aspect Robustness in Aspect-Based Sentiment Analysis
Xiaoyu Xing, Zhijing Jin, Di Jin +3
Aspect-based sentiment analysis (ABSA) aims to predict the sentiment towards a specific aspect in the text. However, existing ABSA test sets cannot be used to probe whether a model…
Rethinking Generalization of Neural Models: A Named Entity Recognition Case Study
Jinlan Fu, Pengfei Liu, Qi Zhang +1
While neural network-based models have achieved impressive performance on a large body of NLP tasks, the generalization behavior of different models remains poorly understood: Does…
Constructing Multiple Tasks for Augmentation: Improving Neural Image Classification With K-means Features
Tao Gui, Lizhi Qing, Qi Zhang +4
Multi-task learning (MTL) has received considerable attention, and numerous deep learning applications benefit from MTL with multiple objectives. However, constructing multiple rel…