435 citations · 572 across the 8 of their papers we have counts for
8 papers
MAF-GNN: Multi-adaptive Spatiotemporal-flow Graph Neural Network for Traffic Speed Forecasting
Yaobin Xu, Weitang Liu, Zhongyi Jiang +4
Traffic forecasting is a core element of intelligent traffic monitoring system. Approaches based on graph neural networks have been widely used in this task to effectively capture…
Energy-based Out-of-distribution Detection
Weitang Liu, Xiaoyun Wang, John D. Owens +1
Determining whether inputs are out-of-distribution (OOD) is an essential building block for safely deploying machine learning models in the open world. However, previous methods re…
CLUE: A Chinese Language Understanding Evaluation Benchmark
Liang Xu, Hai Hu, Xuanwei Zhang +29
The advent of natural language understanding (NLU) benchmarks for English, such as GLUE and SuperGLUE allows new NLU models to be evaluated across a diverse set of tasks. These com…
CLUENER2020: Fine-grained Named Entity Recognition Dataset and Benchmark for Chinese
Liang Xu, Yu tong, Qianqian Dong +7
In this paper, we introduce the NER dataset from CLUE organization (CLUENER2020), a well-defined fine-grained dataset for named entity recognition in Chinese. CLUENER2020 contains…
Unsupervised Object Segmentation with Explicit Localization Module
Weitang Liu, Lifeng Wei, James Sharpnack +1
In this paper, we propose a novel architecture that iteratively discovers and segments out the objects of a scene based on the image reconstruction quality. Different from other ap…
Multiple Generative Models Ensemble for Knowledge-Driven Proactive Human-Computer Dialogue Agent
Zelin Dai, Weitang Liu, Guanhua Zhan
Multiple sequence to sequence models were used to establish an end-to-end multi-turns proactive dialogue generation agent, with the aid of data augmentation techniques and variant…
Surprising Negative Results for Generative Adversarial Tree Search
Kamyar Azizzadenesheli, Brandon Yang, Weitang Liu +2
While many recent advances in deep reinforcement learning (RL) rely on model-free methods, model-based approaches remain an alluring prospect for their potential to exploit unsuper…
Object Localization with a Weakly Supervised CapsNet
Weitang Liu, Emad Barsoum, John D. Owens
Inspired by CapsNet's routing-by-agreement mechanism with its ability to learn object properties, we explore if those properties in turn can determine new properties of the objects…