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Type
Conference paper
Journal article
Date
2024
2023
2022
2021
2020
2018
CS-Bench:A Comprehensive Benchmark for Large Language Models towards Computer Science Mastery
Computer Science (CS) stands as a testament to the intricacies of human intelligence, profoundly advancing the development of …
Xiaoshuai Song
,
Muxi Diao
,
Guanting Dong
,
Zhengyang Wang
,
Yujia Fu
,
RunqiQiao
,
Zhexu Wang
,
Dayuan Fu
,
Huangxuan Wu
,
Bin Liang
,
Weihao Zeng
,
Yejie Wang
,
Zhuoma GongQue
,
Jianing Yu
,
QiunaTan
,
Weiran Xu
PDF
Cite
Code
DOI
BootTOD:Bootstrap Task-oriented Dialogue Representations by Aligning Diverse Responses
Pre-trained language models have been successful in many scenarios. However, their usefulness in task-oriented dialogues is limited due …
Weihao Zeng
,
Keqing He
,
Yejie Wang
,
Dayuan Fu
,
Weiran Xu
PDF
Cite
DOI
COLING 2024
DivTOD:Unleashing the Power of LLMs for Diversifying Task-Oriented Dialogue Representations
Language models pre-trained on general text have achieved impressive results in diverse fields. Yet, the distinct linguistic …
Weihao Zeng
,
Dayuan Fu
,
Keqing He
,
Yejie Wang
,
Yukai Xu
,
Weiran Xu
PDF
Cite
DOI
NAACL 2024
Faceptor:A Generalist Model for Face Perception
With the comprehensive research conducted on various face analysis tasks, there is a growing interest among researchers to develop a …
Lixiong Qin
,
MeiWang
,
XuannanLiu
,
YuhangZhang
,
WeiDeng
,
Xiaoshuai Song
,
Weiran Xu
,
WeihongDeng
PDF
Cite
Code
DOI
ECCV 2024
PreAct:Predicting Future in ReAct Enhances Agent's Planning Ability
Addressing the discrepancies between predictions and actual outcomes often aids individuals in expanding their thought processes and …
Dayuan Fu
,
JianzhaoHuang
,
SiyuanLu
,
Guanting Dong
,
Yejie Wang
,
Keqing He
,
Weiran Xu
PDF
Cite
Code
DOI
Multi-Perspective Consistency Enhances Confidence Estimation in Large Language Models
In the deployment of large language models (LLMs), accurate confidence estimation is critical for assessing the credibility of model …
Pei Wang
,
Yejie Wang
,
Muxi Diao
,
Keqing He
,
Guanting Dong
,
Weiran Xu
PDF
Cite
DOI
DolphCoder:Echo-Locating Code Large Language Models with Diverse and Multi-Objective Instruction Tuning
Code Large Language Models (Code LLMs) have demonstrated outstanding performance in code-related tasks. Several instruction tuning …
Yejie Wang
,
Keqing He
,
Guanting Dong
,
Pei Wang
,
Weihao Zeng
,
Muxi Diao
,
Yutao Mu
,
MengdiZhang
,
JingangWang
,
XunliangCai
,
Weiran Xu
PDF
Cite
DOI
ACL 2024
Knowledge Editing on Black-box Large Language Models
Knowledge editing (KE) aims to efficiently and precisely modify the behavior of large language models (LLMs) to update specific …
Xiaoshuai Song
,
Zhengyang Wang
,
Keqing He
,
Guanting Dong
,
Yutao Mu
,
Jinxu Zhao
,
Weiran Xu
PDF
Cite
Code
DOI
Semantic Parsing by Large Language Models for Intricate Updating Strategies of Zero-Shot Dialogue State Tracking
Zero-shot Dialogue State Tracking (DST) addresses the challenge of acquiring and annotating task-oriented dialogues, which can be time …
YuxiangWu
,
Guanting Dong
,
Weiran Xu
PDF
Code
DOI
EMNLP 2023
Revisit input perturbation problems for llms: A unified robustness evaluation framework for noisy slot filling task
We utilize a multi-level data augmentation method (character, word, and sentence levels) to construct a candidate data pool, and …
Guanting Dong
,
Jinxu Zhao
,
Tingfeng Hui
,
Daichi Guo
,
WenlongWan
,
BoqiFeng
,
YueyanQiu
,
Zhuoma GongQue
,
Keqing He
,
Zechen Wang
,
Weiran Xu
PDF
Code
DOI
NLPCC 2023
Large Language Models Meet Open-World Intent Discovery and Recognition: An Evaluation of ChatGPT
The tasks of out-of-domain (OOD) intent discovery and generalized intent discovery (GID) aim to extend a closed intent classifier to …
Xiaoshuai Song
,
Keqing He
,
Pei Wang
,
Guanting Dong
,
Yutao Mu
,
JingangWang
,
YunsenXian
,
XunliangCai
,
Weiran Xu
PDF
Code
DOI
EMNLP 2023
DemoNSF: A Multi-task Demonstration-based Generative Framework for Noisy Slot Filling Task
Recently, prompt-based generative frameworks have shown impressive capabilities in sequence labeling tasks. However, in practical …
Guanting Dong
,
Tingfeng Hui
,
Zhuoma GongQue
,
Jinxu Zhao
,
Daichi Guo
,
GangZhao
,
Keqing He
,
Weiran Xu
PDF
Code
DOI
EMNLP 2023
Continual Generalized Intent Discovery: Marching Towards Dynamic and Open-world Intent Recognition
In a practical dialogue system, users may input out-of-domain (OOD) queries. The Generalized Intent Discovery (GID) task aims to …
Xiaoshuai Song
,
Yutao Mu
,
Keqing He
,
YueyanQiu
,
Pei Wang
,
Weiran Xu
PDF
Code
DOI
EMNLP 2023
Bridging the KB-Text Gap: Leveraging Structured Knowledge-aware Pre-training for KBQA
Knowledge Base Question Answering (KBQA) aims to answer natural language questions with factual information such as entities and …
Guanting Dong
,
Rumei Li
,
SiruiWang
,
YupengZhang
,
YunsenXian
,
Weiran Xu
PDF
Code
DOI
CIKM 2023
APP:Adaptive Prototypical Pseudo-Labeling for Few-shot OOD Detection
Detecting out-of-domain (OOD) intents from user queries is essential for a task-oriented dialogue system. Previous OOD detection …
Pei Wang
,
Keqing He
,
Yutao Mu
,
Xiaoshuai Song
,
Yanan Wu
,
JingangWang
,
YunsenXian
,
XunliangCai
,
Weiran Xu
PDF
DOI
EMNLP 2023
A multi-task semantic decomposition framework with task-specific pre-training for few-shot ner
The objective of few-shot named entity recognition is to identify named entities with limited labeled instances. Previous works have …
Guanting Dong
,
Zechen Wang
,
Jinxu Zhao
,
GangZhao
,
Daichi Guo
,
Dayuan Fu
,
Tingfeng Hui
,
Chen Zeng
,
Keqing He
,
Xuefeng Li
,
Liwen Wang
,
XinyueCui
,
Weiran Xu
PDF
Code
DOI
CIKM 2023
Value type-the bridge to a better DST model
Value type of the slots can provide lots of useful information for DST tasks. However, it has been ignored in most previous works. In …
Qixiang Gao
,
MingyangSun
,
Yutao Mu
,
Chen Zeng
,
Weiran Xu
PDF
DOI
ACL 2023
Seen to Unseen: Exploring Compositional Generalization of Multi-Attribute Controllable Dialogue Generation
Existing controllable dialogue generation work focuses on the single-attribute control and lacks generalization capability to …
Weihao Zeng
,
Lulu Zhao
,
Keqing He
,
Ruotong Geng
,
JingangWang
,
WeiWu
,
Weiran Xu
PDF
DOI
ACL 2023
Revisit Out-Of-Vocabulary Problem For Slot Filling: A Unified Contrastive Framework With Multi-Level Data Augmentations
In real dialogue scenarios, the existing slot filling model, which tends to memorize entity patterns, has a significantly reduced …
Daichi Guo
,
Guanting Dong
,
Dayuan Fu
,
YuxiangWu
,
Chen Zeng
,
Tingfeng Hui
,
Liwen Wang
,
Xuefeng Li
,
Zechen Wang
,
Keqing He
,
XinyueCui
,
Weiran Xu
PDF
DOI
ICASSP 2023
Generative zero-shot prompt learning for cross-domain slot filling with inverse prompting
Zero-shot cross-domain slot filling aims to transfer knowledge from the labeled source domain to the unlabeled target domain. Existing …
Xuefeng Li
,
Liwen Wang
,
Guanting Dong
,
Keqing He
,
JinzhengZhao
,
Hao Lei
,
JiachiLiu
,
Weiran Xu
PDF
Code
DOI
ACL 2023
FutureTOD: Teaching Future Knowledge to Pre-trained Language Model for Task-Oriented Dialogue
Pre-trained language models based on general text enable huge success in the NLP scenario. But the intrinsical difference of linguistic …
Weihao Zeng
,
Keqing He
,
Yejie Wang
,
Chen Zeng
,
JingangWang
,
YunsenXian
,
Weiran Xu
PDF
Code
DOI
ACL 2023
Decoupling Pseudo Label Disambiguation and Representation Learning for Generalized Intent Discovery
Generalized intent discovery aims to extend a closed-set in-domain intent classifier to an open-world intent set including in-domain …
Yutao Mu
,
Xiaoshuai Song
,
Keqing He
,
Chen Zeng
,
Pei Wang
,
JingangWang
,
YunsenXian
,
Weiran Xu
PDF
Code
DOI
ACL 2023
A Prototypical Semantic Decoupling Method via Joint Contrastive Learning for Few-Shot Named Entity Recognition
Few-shot named entity recognition (NER) aims at identifying named entities based on only few labeled instances. Most existing …
Guanting Dong
,
Zechen Wang
,
Liwen Wang
,
Daichi Guo
,
Dayuan Fu
,
YuxiangWu
,
Chen Zeng
,
Xuefeng Li
,
Tingfeng Hui
,
Keqing He
,
XinyueCui
,
Qixiang Gao
,
Weiran Xu
PDF
DOI
ICASSP 2023
Watch the Neighbors: A Unified K-Nearest Neighbor Contrastive Learning Framework for OOD Intent Discovery
Discovering out-of-domain (OOD) intent is important for developing new skills in task-oriented dialogue systems. The key challenges lie …
Yutao Mu
,
Keqing He
,
Pei Wang
,
Yanan Wu
,
JingangWang
,
WeiWu
,
Weiran Xu
EMNLP 2022
UniNL: Aligning Representation Learning with Scoring Function for OOD Detection via Unified Neighborhood Learning
Detecting out-of-domain (OOD) intents from user queries is essential for avoiding wrong operations in task-oriented dialogue systems. …
Yutao Mu
,
Pei Wang
,
Keqing He
,
Yanan Wu
,
JingangWang
,
WeiWu
,
Weiran Xu
EMNLP 2022
Exploiting domain-slot related keywords description for Few-Shot Cross-Domain Dialogue State Tracking
Collecting dialogue data with domain-slot-value labels for dialogue state tracking (DST) could be a costly process. In this paper, we …
Qixiang Gao
,
Guanting Dong
,
Yutao Mu
,
Liwen Wang
,
Chen Zeng
,
Daichi Guo
,
MingyangSun
,
Weiran Xu
EMNLP 2022
Entity-level Interaction via Heterogeneous Graph for Multimodal Named Entity Recognition
Multimodal Named Entity Recognition (MNER) faces two specific challenges: 1) How to capture useful entity-related visual information; …
GangZhao
,
Guanting Dong
,
YidongShi
,
HaolongYan
,
Weiran Xu
,
SiLi
EMNLP 2022 Findings
Disentangling Confidence Score Distribution for Out-of-Domain Intent Detection with Energy-Based Learning
Detecting Out-of-Domain (OOD) or unknown intents from user queries is essential in a task-oriented dialog system. Traditional …
Yanan Wu
,
Zhiyuan Zeng
,
Keqing He
,
Yutao Mu
,
Pei Wang
,
Yuanmeng Yan
,
Weiran Xu
EMNLP 2022 workshop
Semi-Supervised Knowledge-Grounded Pre-training for Task-Oriented Dialog Systems
Recent advances in neural approaches greatly improve task-oriented dialogue (TOD) systems which assist users to accomplish their goals. …
Weihao Zeng
,
Keqing He
,
Zechen Wang
,
Dayuan Fu
,
Guanting Dong
,
Ruotong Geng
,
Pei Wang
,
JingangWang
,
ChaoboSun
,
WeiWu
,
Weiran Xu
PDF
Cite
Code
EMNLP2022 workshop (SereTOD)
PSSAT: A Perturbed Semantic Structure Awareness Transferring Method for Perturbation-Robust Slot Filling
Most existing slot filling models tend to memorize inherent patterns of entities and corresponding contexts from training data. …
Guanting Dong
,
Daichi Guo
,
Liwen Wang
,
Xuefeng Li
,
Zechen Wang
,
Chen Zeng
,
Keqing He
,
JinzhengZhao
,
Hao Lei
,
XinyueCui
,
YiHuang
,
JunlanFeng
,
Weiran Xu
PDF
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COLING 2022
Generalized Intent Discovery: Learning from Open World Dialogue System
Traditional intent classification models are based on a pre-defined intent set and only recognize limited in-domain (IND) intent …
Yutao Mu
,
Keqing He
,
Yanan Wu
,
Pei Wang
,
JingangWang
,
WeiWu
,
YiHuang
,
JunlanFeng
,
Weiran Xu
PDF
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Code
COLING 2022
Distribution Calibration for Out-of-Domain Detection with Bayesian Approximation
Out-of-Domain (OOD) detection is a key component in a task-oriented dialog system, which aims to identify whether a query falls outside …
Yanan Wu
,
Zhiyuan Zeng
,
Keqing He
,
Yutao Mu
,
Pei Wang
,
Weiran Xu
PDF
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Code
COLING 2022
ADPL: Adversarial Prompt-based Domain Adaptation for Dialogue Summarization with Knowledge Disentanglement
Traditional dialogue summarization models rely on a large-scale manually-labeled corpus, lacking generalization ability to new domains, …
Lulu Zhao
,
Fujia Zheng
,
Weihao Zeng
,
Keqing He
,
Ruotong Geng
,
HuixingJiang
,
WeiWu
,
Weiran Xu
SIGIR 2022
Revisit Overconfidence for OOD Detection: Reassigned Contrastive Learning with Adaptive Class-dependent Threshold
Detecting Out-of-Domain (OOD) or unknown intents from user queries is essential in a task-oriented dialog system. A key challenge of …
Yanan Wu
,
Keqing He
,
Yuanmeng Yan
,
Qixiang Gao
,
Zhiyuan Zeng
,
Fujia Zheng
,
Lulu Zhao
,
HuixingJiang
,
WeiWu
,
Weiran Xu
NAACL 2022
Domain-Oriented Prefix-Tuning: Towards Efficient and Generalizable Fine-tuning for Zero-Shot Dialogue Summarization
The most advanced abstractive dialogue summarizers lack generalization ability on new domains and the existing researches for domain …
Lulu Zhao
,
Fujia Zheng
,
Weihao Zeng
,
Keqing He
,
Weiran Xu
,
HuixingJiang
,
WeiWu
,
Yanan Wu
NAACL 2022
Disentangled Knowledge Transfer for OOD Intent Discovery with Unified Contrastive Learning
Discovering Out-of-Domain(OOD) intents is essential for developing new skills in a task-oriented dialogue system. The key challenge is …
Yutao Mu
,
Keqing He
,
Yanan Wu
,
Zhiyuan Zeng
,
Hong Xu
,
HuixingJiang
,
WeiWu
,
Weiran Xu
ACL 2022
A Robust Contrastive Alignment Method For Multi-Domain Text Classification
Multi-domain text classification can automatically classify texts in various scenarios. Due to the diversity of human languages, texts …
Xuefeng Li
,
Hao Lei
,
Liwen Wang
,
Guanting Dong
,
JinzhengZhao
,
JiachiLiu
,
Weiran Xu
,
ChunyunZhang
ICASSP 2022
Large-Scale Relation Learning for Question Answering over Knowledge Bases with Pre-trained Language Models
The key challenge of question answering over knowledge bases (KBQA) is the inconsistency between the natural language questions and the …
Yuanmeng Yan
,
RumeiLi
,
SiruiWang
,
HongzhiZhang
,
ZanDaoguang
,
FuzhengZhang
,
WeiWu
,
Weiran Xu
PDF
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Code
EMNLP 2021
Gradient-Based Adversarial Factual Consistency Evaluation for Abstractive Summarization
Neural abstractive summarization systems have gained significant progress in recent years. However, excessive abstractiveness …
Zhiyuan Zeng
,
JiazeChen
,
Weiran Xu
,
LeiLi
PDF
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Code
EMNLP 2021
Give the Truth:Incorporate Semantic Slot into Abstractive Dialogue Summarization
Abstractive dialogue summarization suffers from a lots of factual errors, which are due to scattered salient elements in the …
Lulu Zhao
,
Weihao Zeng
,
Weiran Xu
,
郭军
PDF
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EMNLP 2021
Bridge to Target Domain by Prototypical Contrastive Learning and Label Confusion:Re-explore Zero-Shot Learning for Slot Filling
Zero-shot cross-domain slot filling alleviates the data dependence in the case of data scarcity in the target domain, which has aroused …
Liwen Wang
,
Xuefeng Li
,
JiachiLiu
,
Keqing He
,
Yuanmeng Yan
,
Weiran Xu
PDF
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Code
EMNLP 2021
A Finer-grain Universal Dialogue Semantic Structures based Model For Abstractive Dialogue Summarization
Although abstractive summarization models have achieved impressive results on document summarization tasks, their performance on …
Yuejie Lei
,
Fujia Zheng
,
Yuanmeng Yan
,
Keqing He
,
Weiran Xu
PDF
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Code
EMNLP 2021
Scheduled Dialog Policy Learning:An Automatic Curriculum Learning Framework for Task-oriented Dialog System
Sihong Liu
,
JinchaoZhang
,
KeqingHe,
,
Weiran Xu
,
JieZhou
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DOI
ACL 2021
Novel Slot Detection:A Benchmark for Discovering Unknown Slot Types in the Task-Oriented Dialogue System
Existing slot filling models can only recognize pre-defined in-domain slot types from a limited slot set. In the practical application, …
Yanan Wu
,
Zhiyuan Zeng
,
Keqing He
,
Hong Xu
,
Yuanmeng Yan
,
HuixingJiang
,
Weiran Xu
PDF
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Code
ACL 2021
Modeling Discriminative Representations for Out-of-Domain Detection with Supervised Contrastive Learning
Detecting Out-of-Domain (OOD) or unknown intents from user queries is essential in a task oriented dialog system. A key challenge of …
Zhiyuan Zeng
,
Keqing He
,
Yuanmeng Yan
,
Zijun Liu
,
Yanan Wu
,
Hong Xu
,
HuixingJiang
,
Weiran Xu
PDF
Cite
Code
ACL 2021
ConSERT:A Contrastive Framework for Self-Supervised Sentence Representation Transfer
Learning high-quality sentence representations benefits a wide range of natural language processing tasks. Though BERT-based …
Yuanmeng Yan
,
RumeiLi
,
SiruiWang
,
FuzhengZhang
,
WeiWu
,
Weiran Xu
PDF
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Code
ACL 2021
Hierarchical Speaker-aware Sequence-to-sequence Model for Dialogue Summarization
Yuejie Lei
,
Yuanmeng Yan
,
Zhiyuan Zeng
,
Keqing He
,
XimingZhang
,
Weiran Xu
PDF
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DOI
ICASSP 2021
Dynamically Disentangling Social Bias from Task-Oriented Representations with Adversarial Attack
Representation learning is widely used in NLP for a vast range of tasks. However, representations derived from text corpora often …
Liwen Wang
,
Yuanmeng Yan
,
Keqing He
,
Yanan Wu
,
Weiran Xu
PDF
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Code
DOI
NAACL 2021
Adversarial Self-Supervised Learning for Out-of-Domain Detection
Detecting out-of-domain (OOD) intents is crucial for the deployed task-oriented dialogue system. Previous unsupervised OOD detection …
Zhiyuan Zeng
,
Keqing He
,
Yuanmeng Yan
,
Hong Xu
,
Weiran Xu
PDF
Cite
Code
DOI
NAACL 2021
Adversarial Generative Distance-Based Classifier for Robust Out-of-Domain Detection
Detecting out-of-domain (OOD) intents is critical in a task-oriented dialog system. Existing methods rely heavily on extensive manually …
Zhiyuan Zeng
,
Hong Xu
,
Keqing He
,
Yuanmeng Yan
,
Sihong Liu
,
Zijun Liu
,
Weiran Xu
PDF
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DOI
ICASSP 2021
Utilizing Graph Neural Networks to Improving Dialogue-based Relation Extraction
Relation extraction has been an active research interest in the field of Natural Language Processing (NLP). The past works primarily …
Lulu Zhao
,
Weiran Xu
,
ShengGao
,
JunGuo
PDF
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DOI
Neurocomputing
From context-aware:to knowledge-aware Boosting OOV tokens recognition in slot tagging with background knowledge
Neural-based context-aware models for slot tagging tasks in language understanding have achieved state-of-the-art performance, …
Keqing He
,
Yuanmeng Yan
,
Weiran Xu
PDF
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DOI
Neurocomputing
Improving Abstractive Dialogue Summarization with Graph Structures and Topic Words
Recently, people have been beginning paying more attention to the abstractive dialogue summarization task. Since the information flows …
Lulu Zhao
,
Weiran Xu
,
JunGuo
PDF
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DOI
COLING 2020
Contrastive Zero-Shot Learning for Cross-Domain Slot Filling with Adversarial Attack
Zero-shot slot filling has widely arisen to cope with data scarcity in target domains. However, previous approaches often ignore …
Keqing He
,
JinchaoZhang
,
Yuanmeng Yan
,
Weiran Xu
,
ChengNiu
,
JieZhou
PDF
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DOI
COLING 2020
A Deep Generative Distance-Based Classifier for Out-of-Domain Detection with Mahalanobis Space
Detecting out-of-domain (OOD) input intents is critical in the task-oriented dialog system. Different from most existing methods that …
Hong Xu
,
Keqing He
,
Yuanmeng Yan
,
Sihong Liu
,
Zijun Liu
,
Weiran Xu
PDF
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Code
DOI
COLING 2020
Adversarial Semantic Decoupling for Recognizing Open-Vocabulary Slots
Open-vocabulary slots, such as file name, album name, or schedule title, significantly degrade the performance of neural-based slot …
Yuanmeng Yan
,
Keqing He
,
Hong Xu
,
Sihong Liu
,
FanyuMeng
,
MinHu
,
Weiran Xu
PDF
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Code
DOI
EMNLP 2020
CGTR:Convolution Graph Topology Representation for Document Ranking
Contextualized neural language models have gained much attention in Information Retrieval (IR) with its ability to achieve better text …
YuanyuanQi
,
JiayueZhang
,
YansongLiu
,
Weiran Xu
,
JunGuo
PDF
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Code
DOI
CIKM 2020
Learning Label-Relational Output Structure for Adaptive Sequence Labeling
Sequence labeling is a fundamental task of natural language understanding. Recent neural models for sequence labeling task achieve …
Keqing He
,
Yuanmeng Yan
,
Hong Xu
,
Sihong Liu
,
Zijun Liu
,
Weiran Xu
PDF
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DOI
IJCNN 2020
Adversarial Cross-Lingual Transfer Learning for Slot Tagging of Low-Resource Languages
Slot tagging is a key component in a task-oriented dialogue system. Conversational agents need to understand human input by training on …
Keqing He
,
Yuanmeng Yan
,
Weiran Xu
PDF
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DOI
IJCNN 2020
Learning to Tag OOV Tokens by Integrating Contextual Representation and Background Knowledge
Neural-based context-aware models for slot tagging have achieved state-of-the-art performance. However, the presence of …
Keqing He
,
Yuanmeng Yan
,
Weiran Xu
PDF
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DOI
ACL 2020
Generative Adversarial Zero-Shot Relation Learning for Knowledge Grapths
Large-scale knowledge graphs (KGs) are shown to become more important in current information systems. To expand the coverage of KGs, …
Pengda Qin
,
XinWang
,
WenhuChen
,
ChunyunZhang
,
Weiran Xu
,
WilliamYangWang
PDF
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DOI
AAAI 2020
Robust Distant Supervision Relation Extraction via Deep Reinforcement Learning
Distant supervision has become the standard method for relation extraction. However, even though it is an efficient method, it does not …
Pengda Qin
,
Weiran Xu
,
WilliamYangWang
PDF
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Code
DOI
ACL 2018
DSGAN: Generative Adversarial Training for Distant Supervision Relation Extraction
Distant supervision can effectively label data for relation extraction, but suffers from the noise labeling problem. Recent works …
Pengda Qin
,
Weiran Xu
,
WilliamYangWang
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DOI
ACL 2018
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