Search Results for author: Ying Shen

Found 32 papers, 11 papers with code

Wasserstein Selective Transfer Learning for Cross-domain Text Mining

no code implementations EMNLP 2021 Lingyun Feng, Minghui Qiu, Yaliang Li, Haitao Zheng, Ying Shen

However, the source and target domains usually have different data distributions, which may lead to negative transfer.

Transfer Learning

Amalgamating Knowledge from Two Teachers for Task-oriented Dialogue System with Adversarial Training

1 code implementation EMNLP 2020 Wanwei He, Min Yang, Rui Yan, Chengming Li, Ying Shen, Ruifeng Xu

Instead of adopting the classic student-teacher learning of forcing the output of a student network to exactly mimic the soft targets produced by the teacher networks, we introduce two discriminators as in generative adversarial network (GAN) to transfer knowledge from two teachers to the student.

Task-Oriented Dialogue Systems

Automatic Context Pattern Generation for Entity Set Expansion

no code implementations17 Jul 2022 Yinghui Li, Shulin Huang, Xinwei Zhang, Qingyu Zhou, Yangning Li, Ruiyang Liu, Yunbo Cao, Hai-Tao Zheng, Ying Shen

A non-negligible shortcoming of the pre-defined context patterns is that they cannot be flexibly generalized to all kinds of semantic classes, and we call this phenomenon as "semantic sensitivity".

Contrastive Learning with Hard Negative Entities for Entity Set Expansion

1 code implementation16 Apr 2022 Yinghui Li, Yangning Li, Yuxin He, Tianyu Yu, Ying Shen, Hai-Tao Zheng

In addition, we propose the ProbExpan, a novel probabilistic ESE framework utilizing the entity representation obtained by the aforementioned language model to expand entities.

Contrastive Learning Language Modelling

Automatic Depression Detection: An Emotional Audio-Textual Corpus and a GRU/BiLSTM-based Model

1 code implementation15 Feb 2022 Ying Shen, Huiyu Yang, Lin Lin

Depression is a global mental health problem, the worst case of which can lead to suicide.

Depression Detection

A Survey of Natural Language Generation

no code implementations22 Dec 2021 Chenhe Dong, Yinghui Li, Haifan Gong, Miaoxin Chen, Junxin Li, Ying Shen, Min Yang

This paper offers a comprehensive review of the research on Natural Language Generation (NLG) over the past two decades, especially in relation to data-to-text generation and text-to-text generation deep learning methods, as well as new applications of NLG technology.

Data-to-Text Generation

HRKD: Hierarchical Relational Knowledge Distillation for Cross-domain Language Model Compression

1 code implementation EMNLP 2021 Chenhe Dong, Yaliang Li, Ying Shen, Minghui Qiu

In this paper, we target to compress PLMs with knowledge distillation, and propose a hierarchical relational knowledge distillation (HRKD) method to capture both hierarchical and domain relational information.

Few-Shot Learning Knowledge Distillation +3

Continual Learning for Task-oriented Dialogue System with Iterative Network Pruning, Expanding and Masking

1 code implementation ACL 2021 Binzong Geng, Fajie Yuan, Qiancheng Xu, Ying Shen, Ruifeng Xu, Min Yang

This ability to learn consecutive tasks without forgetting how to perform previously trained problems is essential for developing an online dialogue system.

Continual Learning Network Pruning

Contextualized Knowledge-aware Attentive Neural Network: Enhancing Answer Selection with Knowledge

no code implementations12 Apr 2021 Yang Deng, Yuexiang Xie, Yaliang Li, Min Yang, Wai Lam, Ying Shen

Answer selection, which is involved in many natural language processing applications such as dialog systems and question answering (QA), is an important yet challenging task in practice, since conventional methods typically suffer from the issues of ignoring diverse real-world background knowledge.

Answer Selection Natural Language Processing +1

Learning Purified Feature Representations from Task-irrelevant Labels

no code implementations22 Feb 2021 Yinghui Li, Chen Wang, Yangning Li, Hai-Tao Zheng, Ying Shen

Learning an empirically effective model with generalization using limited data is a challenging task for deep neural networks.

Learning to Augment for Data-Scarce Domain BERT Knowledge Distillation

no code implementations20 Jan 2021 Lingyun Feng, Minghui Qiu, Yaliang Li, Hai-Tao Zheng, Ying Shen

Despite pre-trained language models such as BERT have achieved appealing performance in a wide range of natural language processing tasks, they are computationally expensive to be deployed in real-time applications.

Knowledge Distillation Natural Language Processing

Integrating User History into Heterogeneous Graph for Dialogue Act Recognition

no code implementations COLING 2020 Dong Wang, Ziran Li, Haitao Zheng, Ying Shen

Dialogue Act Recognition (DAR) is a challenging problem in Natural Language Understanding, which aims to attach Dialogue Act (DA) labels to each utterance in a conversation.

Dialogue Act Classification

Answer-driven Deep Question Generation based on Reinforcement Learning

no code implementations COLING 2020 Liuyin Wang, Zihan Xu, Zibo Lin, Haitao Zheng, Ying Shen

First, we propose an answer-aware initialization module with a gated connection layer which introduces both document and answer information to the decoder, thus helping to guide the choice of answer-focused question words.

Question Generation reinforcement-learning

Summarize before Aggregate: A Global-to-local Heterogeneous Graph Inference Network for Conversational Emotion Recognition

no code implementations COLING 2020 Dongming Sheng, Dong Wang, Ying Shen, Haitao Zheng, Haozhuang Liu

Local dependencies, which captures short-term emotional effects between neighbouring utterances, are further injected via an Aggregation Graph to distinguish the subtle differences between utterances containing emotional phrases.

Emotion Recognition in Conversation Natural Language Processing

Relabel the Noise: Joint Extraction of Entities and Relations via Cooperative Multiagents

no code implementations ACL 2020 Daoyuan Chen, Yaliang Li, Kai Lei, Ying Shen

Distant supervision based methods for entity and relation extraction have received increasing popularity due to the fact that these methods require light human annotation efforts.

Relation Extraction

A multi-agent ontologies-based clinical decision support system

no code implementations21 Jan 2020 Ying Shen, Jacquet-Andrieu Armelle, Joël Colloc

Our approach is based on the specialization of agents adapted to the knowledge models used during the clinical steps and ontologies.

Clinical Knowledge

Chinese Relation Extraction with Multi-Grained Information and External Linguistic Knowledge

1 code implementation ACL 2019 Ziran Li, Ning Ding, Zhiyuan Liu, Hai-Tao Zheng, Ying Shen

Chinese relation extraction is conducted using neural networks with either character-based or word-based inputs, and most existing methods typically suffer from segmentation errors and ambiguity of polysemy.

Relation Extraction

Multi-Task Learning with Multi-View Attention for Answer Selection and Knowledge Base Question Answering

2 code implementations6 Dec 2018 Yang Deng, Yuexiang Xie, Yaliang Li, Min Yang, Nan Du, Wei Fan, Kai Lei, Ying Shen

Second, these two tasks can benefit each other: answer selection can incorporate the external knowledge from knowledge base (KB), while KBQA can be improved by learning contextual information from answer selection.

Answer Selection Knowledge Base Question Answering +1

Improving Medical Short Text Classification with Semantic Expansion Using Word-Cluster Embedding

no code implementations5 Dec 2018 Ying Shen, Qiang Zhang, Jin Zhang, Jiyue Huang, Yuming Lu, Kai Lei

However, in electronic medical records (EMR), the texts containing sentences are shorter than that in general domain, which leads to the lack of semantic features and the ambiguity of semantic.

Classification General Classification +1

Constructing Ontology-Based Cancer Treatment Decision Support System with Case-Based Reasoning

no code implementations5 Dec 2018 Ying Shen, Joël Colloc, Armelle Jacquet-Andrieu, Ziyi Guo, Yong liu

Disease Ontology (DO) that pertains to cancer's clinical stages and their corresponding information components is utilized to improve the reasoning ability of a decision support system (DSS).

General Classification Natural Language Processing

A Knowledge Graph Based Solution for Entity Discovery and Linking in Open-Domain Questions

no code implementations5 Dec 2018 Kai Lei, Bing Zhang, Yong liu, Yang Deng, Dongyu Zhang, Ying Shen

In Question Entity Discovery and Linking (QEDL) problem, traditional methods are challenged because multiple entities in one short question are difficult to be discovered entirely and the incomplete information in short text makes entity linking hard to implement.

Entity Linking Learning-To-Rank +4

Approach for Semi-automatic Construction of Anti-infective Drug Ontology Based on Entity Linking

no code implementations5 Dec 2018 Ying Shen, Yang Deng, Kaiqi Yuan, Li Liu, Yong liu

Experiments show that our selected features have achieved a precision rate of 86. 77%, a recall rate of 89. 03% and an F1 score of 87. 89%.

Entity Linking Natural Language Processing

MedSim: A Novel Semantic Similarity Measure in Bio-medical Knowledge Graphs

no code implementations5 Dec 2018 Kai Lei, Kaiqi Yuan, Qiang Zhang, Ying Shen

We present MedSim, a novel semantic SIMilarity method based on public well-established bio-MEDical knowledge graphs (KGs) and large-scale corpus, to study the therapeutic substitution of antibiotics.

Knowledge Graphs Semantic Similarity +1

MedTruth: A Semi-supervised Approach to Discovering Knowledge Condition Information from Multi-Source Medical Data

no code implementations27 Sep 2018 Yang Deng, Yaliang Li, Ying Shen, Nan Du, Wei Fan, Min Yang, Kai Lei

In the light of these challenges, we propose a new truth discovery method, MedTruth, for medical knowledge condition discovery, which incorporates prior source quality information into the source reliability estimation procedure, and also utilizes the knowledge triple information for trustworthy information computation.

Databases

Cooperative Denoising for Distantly Supervised Relation Extraction

no code implementations COLING 2018 Kai Lei, Daoyuan Chen, Yaliang Li, Nan Du, Min Yang, Wei Fan, Ying Shen

Distantly supervised relation extraction greatly reduces human efforts in extracting relational facts from unstructured texts.

Denoising Information Retrieval +3

Knowledge as A Bridge: Improving Cross-domain Answer Selection with External Knowledge

no code implementations COLING 2018 Yang Deng, Ying Shen, Min Yang, Yaliang Li, Nan Du, Wei Fan, Kai Lei

In this paper, we propose Knowledge-aware Attentive Network (KAN), a transfer learning framework for cross-domain answer selection, which uses the knowledge base as a bridge to enable knowledge transfer from the source domain to the target domains.

Answer Selection Information Retrieval +2

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