235 citations · 404 across the 20 of their papers we have counts for
20 papers
Learning Generalizable Models for Vehicle Routing Problems via Knowledge Distillation
Jieyi Bi, Yining Ma, Jiahai Wang +4
Recent neural methods for vehicle routing problems always train and test the deep models on the same instance distribution (i.e., uniform). To tackle the consequent cross-distribut…
ProQA: Structural Prompt-based Pre-training for Unified Question Answering
Wanjun Zhong, Yifan Gao, Ning Ding +6
Question Answering (QA) is a longstanding challenge in natural language processing. Existing QA works mostly focus on specific question types, knowledge domains, or reasoning skill…
Graph Neural Networks with Dynamic and Static Representations for Social Recommendation
Junfa Lin, Siyuan Chen, Jiahai Wang
Recommender systems based on graph neural networks receive increasing research interest due to their excellent ability to learn a variety of side information including social netwo…
MODRL/D-EL: Multiobjective Deep Reinforcement Learning with Evolutionary Learning for Multiobjective Optimization
Yongxin Zhang, Jiahai Wang, Zizhen Zhang +1
Learning-based heuristics for solving combinatorial optimization problems has recently attracted much academic attention. While most of the existing works only consider the single…
Topic-to-Essay Generation with Comprehensive Knowledge Enhancement
Zhiyue Liu, Jiahai Wang, Zhenghong Li
Generating high-quality and diverse essays with a set of topics is a challenging task in natural language generation. Since several given topics only provide limited source informa…
Meta-Learning-Based Deep Reinforcement Learning for Multiobjective Optimization Problems
Zizhen Zhang, Zhiyuan Wu, Hang Zhang +1
Deep reinforcement learning (DRL) has recently shown its success in tackling complex combinatorial optimization problems. When these problems are extended to multiobjective ones, i…
AR-LSAT: Investigating Analytical Reasoning of Text
Wanjun Zhong, Siyuan Wang, Duyu Tang +6
Analytical reasoning is an essential and challenging task that requires a system to analyze a scenario involving a set of particular circumstances and perform reasoning over it to…
ASBSO: An Improved Brain Storm Optimization With Flexible Search Length and Memory-Based Selection
Yang Yu, Shangce Gao, Yirui Wang +2
Brain storm optimization (BSO) is a newly proposed population-based optimization algorithm, which uses a logarithmic sigmoid transfer function to adjust its search range during the…
Neural Relational Inference with Efficient Message Passing Mechanisms
Siyuan Chen, Jiahai Wang, Guoqing Li
Many complex processes can be viewed as dynamical systems of interacting agents. In many cases, only the state sequences of individual agents are observed, while the interacting re…
Neural Deepfake Detection with Factual Structure of Text
Wanjun Zhong, Duyu Tang, Zenan Xu +5
Deepfake detection, the task of automatically discriminating machine-generated text, is increasingly critical with recent advances in natural language generative models. Existing a…
LogicalFactChecker: Leveraging Logical Operations for Fact Checking with Graph Module Network
Wanjun Zhong, Duyu Tang, Zhangyin Feng +7
Verifying the correctness of a textual statement requires not only semantic reasoning about the meaning of words, but also symbolic reasoning about logical operations like count, s…
A Heterogeneous Graph with Factual, Temporal and Logical Knowledge for Question Answering Over Dynamic Contexts
Wanjun Zhong, Duyu Tang, Nan Duan +3
We study question answering over a dynamic textual environment. Although neural network models achieve impressive accuracy via learning from input-output examples, they rarely leve…
A Novel Framework with Information Fusion and Neighborhood Enhancement for User Identity Linkage
Siyuan Chen, Jiahai Wang, Xin Du +1
User identity linkage across social networks is an essential problem for cross-network data mining. Since network structure, profile and content information describe different aspe…
MODRL/D-AM: Multiobjective Deep Reinforcement Learning Algorithm Using Decomposition and Attention Model for Multiobjective Optimization
Hong Wu, Jiahai Wang, Zizhen Zhang
Recently, a deep reinforcement learning method is proposed to solve multiobjective optimization problem. In this method, the multiobjective optimization problem is decomposed to a…
Utilizing BERT Intermediate Layers for Aspect Based Sentiment Analysis and Natural Language Inference
Youwei Song, Jiahai Wang, Zhiwei Liang +2
Aspect based sentiment analysis aims to identify the sentimental tendency towards a given aspect in text. Fine-tuning of pretrained BERT performs excellent on this task and achieve…
A Deep Reinforcement Learning Algorithm Using Dynamic Attention Model for Vehicle Routing Problems
Bo Peng, Jiahai Wang, Zizhen Zhang
Recent researches show that machine learning has the potential to learn better heuristics than the one designed by human for solving combinatorial optimization problems. The deep n…
CatGAN: Category-aware Generative Adversarial Networks with Hierarchical Evolutionary Learning for Category Text Generation
Zhiyue Liu, Jiahai Wang, Zhiwei Liang
Generating multiple categories of texts is a challenging task and draws more and more attention. Since generative adversarial nets (GANs) have shown competitive results on general…
Reasoning Over Semantic-Level Graph for Fact Checking
Wanjun Zhong, Jingjing Xu, Duyu Tang +5
Fact checking is a challenging task because verifying the truthfulness of a claim requires reasoning about multiple retrievable evidence. In this work, we present a method suitable…
Collective Mobile Sequential Recommendation: A Recommender System for Multiple Taxicabs
Tongwen Wu, Zizhen Zhang, Yanzhi Li +1
Mobile sequential recommendation was originally designed to find a promising route for a single taxicab. Directly applying it for multiple taxicabs may cause an excessive overlap o…
Attentional Encoder Network for Targeted Sentiment Classification
Youwei Song, Jiahai Wang, Tao Jiang +2
Targeted sentiment classification aims at determining the sentimental tendency towards specific targets. Most of the previous approaches model context and target words with RNN and…