768 citations · 1k across the 18 of their papers we have counts for
19 papers
GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot Learning
Haiteng Zhao, Shengchao Liu, Chang Ma +5
Molecule property prediction has gained significant attention in recent years. The main bottleneck is the label insufficiency caused by expensive lab experiments. In order to allev…
Cross-Domain Few-Shot Classification via Adversarial Task Augmentation
Haoqing Wang, Zhi-Hong Deng
Few-shot classification aims to recognize unseen classes with few labeled samples from each class. Many meta-learning models for few-shot classification elaborately design various…
Few-shot Learning with LSSVM Base Learner and Transductive Modules
Haoqing Wang, Zhi-Hong Deng
The performance of meta-learning approaches for few-shot learning generally depends on three aspects: features suitable for comparison, the classifier ( base learner ) suitable for…
Self-Supervised Learning Aided Class-Incremental Lifelong Learning
Song Zhang, Gehui Shen, Jinsong Huang +1
Lifelong or continual learning remains to be a challenge for artificial neural network, as it is required to be both stable for preservation of old knowledge and plastic for acquis…
Generative Feature Replay with Orthogonal Weight Modification for Continual Learning
Gehui Shen, Song Zhang, Xiang Chen +1
The ability of intelligent agents to learn and remember multiple tasks sequentially is crucial to achieving artificial general intelligence. Many continual learning (CL) methods ha…
Fast Structured Decoding for Sequence Models
Zhiqing Sun, Zhuohan Li, Haoqing Wang +3
Autoregressive sequence models achieve state-of-the-art performance in domains like machine translation. However, due to the autoregressive factorization nature, these models suffe…
Dynamically Pruned Message Passing Networks for Large-Scale Knowledge Graph Reasoning
Xiaoran Xu, Wei Feng, Yunsheng Jiang +3
We propose Dynamically Pruned Message Passing Networks (DPMPN) for large-scale knowledge graph reasoning. In contrast to existing models, embedding-based or path-based, we learn an…
Beyond the Inverted Index
Zhi-Hong Deng
In this paper, a new data structure named group-list is proposed. The group-list is as simple as the inverted index. However, the group-list divides document identifiers in an inve…
Neural Consciousness Flow
Xiaoran Xu, Wei Feng, Zhiqing Sun +1
The ability of reasoning beyond data fitting is substantial to deep learning systems in order to make a leap forward towards artificial general intelligence. A lot of efforts have…
Leap-LSTM: Enhancing Long Short-Term Memory for Text Categorization
Ting Huang, Gehui Shen, Zhi-Hong Deng
Recurrent Neural Networks (RNNs) are widely used in the field of natural language processing (NLP), ranging from text categorization to question answering and machine translation.…
DivGraphPointer: A Graph Pointer Network for Extracting Diverse Keyphrases
Zhiqing Sun, Jian Tang, Pan Du +2
Keyphrase extraction from documents is useful to a variety of applications such as information retrieval and document summarization. This paper presents an end-to-end method called…
RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space
Zhiqing Sun, Zhi-Hong Deng, Jian-Yun Nie +1
We study the problem of learning representations of entities and relations in knowledge graphs for predicting missing links. The success of such a task heavily relies on the abilit…
Unsupervised Neural Word Segmentation for Chinese via Segmental Language Modeling
Zhiqing Sun, Zhi-Hong Deng
Previous traditional approaches to unsupervised Chinese word segmentation (CWS) can be roughly classified into discriminative and generative models. The former uses the carefully d…
Learning to Compose over Tree Structures via POS Tags
Gehui Shen, Zhi-Hong Deng, Ting Huang +1
Recursive Neural Network (RecNN), a type of models which compose words or phrases recursively over syntactic tree structures, has been proven to have superior ability to obtain sen…
A Novel Framework for Recurrent Neural Networks with Enhancing Information Processing and Transmission between Units
Xi Chen, Zhihong Deng, Gehui Shen +1
This paper proposes a novel framework for recurrent neural networks (RNNs) inspired by the human memory models in the field of cognitive neuroscience to enhance information process…
A Gap-Based Framework for Chinese Word Segmentation via Very Deep Convolutional Networks
Zhiqing Sun, Gehui Shen, Zhihong Deng
Most previous approaches to Chinese word segmentation can be roughly classified into character-based and word-based methods. The former regards this task as a sequence-labeling pro…
Mining Top-K Co-Occurrence Items
Zhi-Hong Deng
Frequent itemset mining has emerged as a fundamental problem in data mining and plays an important role in many data mining tasks, such as association analysis, classification, etc…
An Efficient Data Structure for Fast Mining High Utility Itemsets
Zhi-Hong Deng, Shulei Ma, He Liu
In this paper, we propose a novel data structure called PUN-list, which maintains both the utility information about an itemset and utility upper bound for facilitating the process…
DiffNodesets: An Efficient Structure for Fast Mining Frequent Itemsets
Zhi-Hong Deng
Mining frequent itemsets is an essential problem in data mining and plays an important role in many data mining applications. In recent years, some itemset representations based on…