476 citations · 528 across the 12 of their papers we have counts for
12 papers
CLDG: Contrastive Learning on Dynamic Graphs
Yiming Xu, Bin Shi, Teng Ma +3
The graph with complex annotations is the most potent data type, whose constantly evolving motivates further exploration of the unsupervised dynamic graph representation. One of th…
From Text to Trajectory: Exploring Complex Constraint Representation and Decomposition in Safe Reinforcement Learning
Pusen Dong, Tianchen Zhu, Yue Qiu +2
Safe reinforcement learning (RL) requires the agent to finish a given task while obeying specific constraints. Giving constraints in natural language form has great potential for p…
PhoGAD: Graph-based Anomaly Behavior Detection with Persistent Homology Optimization
Ziqi Yuan, Haoyi Zhou, Tianyu Chen +1
A multitude of toxic online behaviors, ranging from network attacks to anonymous traffic and spam, have severely disrupted the smooth operation of networks. Due to the inherent sen…
Learning Music Sequence Representation from Text Supervision
Tianyu Chen, Yuan Xie, Shuai Zhang +3
Music representation learning is notoriously difficult for its complex human-related concepts contained in the sequence of numerical signals. To excavate better MUsic SEquence Repr…
BadRes: Reveal the Backdoors through Residual Connection
Mingrui He, Tianyu Chen, Haoyi Zhou +2
Generally, residual connections are indispensable network components in building CNNs and Transformers for various downstream tasks in CV and VL, which encourages skip shortcuts be…
Task-Specific Expert Pruning for Sparse Mixture-of-Experts
Tianyu Chen, Shaohan Huang, Yuan Xie +5
The sparse Mixture-of-Experts (MoE) model is powerful for large-scale pre-training and has achieved promising results due to its model capacity. However, with trillions of paramete…
THE-X: Privacy-Preserving Transformer Inference with Homomorphic Encryption
Tianyu Chen, Hangbo Bao, Shaohan Huang +6
As more and more pre-trained language models adopt on-cloud deployment, the privacy issues grow quickly, mainly for the exposure of plain-text user data (e.g., search history, medi…
MTTrans: Cross-Domain Object Detection with Mean-Teacher Transformer
Jinze Yu, Jiaming Liu, Xiaobao Wei +7
Recently, DEtection TRansformer (DETR), an end-to-end object detection pipeline, has achieved promising performance. However, it requires large-scale labeled data and suffers from…
RoSearch: Search for Robust Student Architectures When Distilling Pre-trained Language Models
Xin Guo, Jianlei Yang, Haoyi Zhou +2
Pre-trained language models achieve outstanding performance in NLP tasks. Various knowledge distillation methods have been proposed to reduce the heavy computation and storage requ…
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting
Haoyi Zhou, Shanghang Zhang, Jieqi Peng +4
Many real-world applications require the prediction of long sequence time-series, such as electricity consumption planning. Long sequence time-series forecasting (LSTF) demands a h…
Differentially-private Federated Neural Architecture Search
Ishika Singh, Haoyi Zhou, Kunlin Yang +3
Neural architecture search, which aims to automatically search for architectures (e.g., convolution, max pooling) of neural networks that maximize validation performance, has achie…
Stacked Kernel Network
Shuai Zhang, Jianxin Li, Pengtao Xie +4
Kernel methods are powerful tools to capture nonlinear patterns behind data. They implicitly learn high (even infinite) dimensional nonlinear features in the Reproducing Kernel Hil…