Search Results for author: Kai Xiong

Found 6 papers, 1 papers with code

A Graph Enhanced BERT Model for Event Prediction

no code implementations Findings (ACL) 2022 Li Du, Xiao Ding, Yue Zhang, Kai Xiong, Ting Liu, Bing Qin

To this end, we incorporate an additional structured variable into BERT to learn to predict the event connections in the training process.

e-CARE: a New Dataset for Exploring Explainable Causal Reasoning

1 code implementation ACL 2022 Li Du, Xiao Ding, Kai Xiong, Ting Liu, Bing Qin

Understanding causality has vital importance for various Natural Language Processing (NLP) applications.

ExCAR: Event Graph Knowledge Enhanced Explainable Causal Reasoning

no code implementations ACL 2021 Li Du, Xiao Ding, Kai Xiong, Ting Liu, Bing Qin

ExCAR first acquires additional evidence information from a large-scale causal event graph as logical rules for causal reasoning.

Representation Learning

Multi-hop RIS-Empowered Terahertz Communications: A DRL-based Hybrid Beamforming Design

no code implementations22 Jan 2021 Chongwen Huang, Zhaohui Yang, George C. Alexandropoulos, Kai Xiong, Li Wei, Chau Yuen, Zhaoyang Zhang, Merouane Debbah

We investigate the joint design of digital beamforming matrix at the BS and analog beamforming matrices at the RISs, by leveraging the recent advances in deep reinforcement learning (DRL) to combat the propagation loss.

Hybrid Beamforming for RIS-Empowered Multi-hop Terahertz Communications: A DRL-based Method

no code implementations20 Sep 2020 Chongwen Huang, Zhaohui Yang, George C. Alexandropoulos, Kai Xiong, Li Wei, Chau Yuen, Zhaoyang Zhang

Wireless communication in the TeraHertz band (0. 1--10 THz) is envisioned as one of the key enabling technologies for the future six generation (6G) wireless communication systems.

Quda: Natural Language Queries for Visual Data Analytics

no code implementations7 May 2020 Siwei Fu, Kai Xiong, Xiaodong Ge, Siliang Tang, Wei Chen, Yingcai Wu

To address this challenge, we present a new dataset, called Quda, that aims to help V-NLIs recognize analytic tasks from free-form natural language by training and evaluating cutting-edge multi-label classification models.

Multi-Label Classification Paraphrase Generation

Cannot find the paper you are looking for? You can Submit a new open access paper.