activity
20182021
most citedImproving Multi-hop Knowledge Base Question Answering by Learning Intermediate Supervision Signals

204 citations · 250 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CL202113 cited

A Survey on Complex Knowledge Base Question Answering: Methods, Challenges and Solutions

Yunshi Lan, Gaole He, Jinhao Jiang +3

Knowledge base question answering (KBQA) aims to answer a question over a knowledge base (KB). Recently, a large number of studies focus on semantically or syntactically complicate…

cs.CL2021204 cited

Improving Multi-hop Knowledge Base Question Answering by Learning Intermediate Supervision Signals

Gaole He, Yunshi Lan, Jing Jiang +2

Multi-hop Knowledge Base Question Answering (KBQA) aims to find the answer entities that are multiple hops away in the Knowledge Base (KB) from the entities in the question. A majo…

cs.AI20214 cited

TextBox: A Unified, Modularized, and Extensible Framework for Text Generation

Junyi Li, Tianyi Tang, Gaole He +7

In this paper, we release an open-source library, called TextBox, to provide a unified, modularized, and extensible text generation framework. TextBox aims to support a broad set o…

cs.CL202029 cited

Knowledge-Enhanced Personalized Review Generation with Capsule Graph Neural Network

Junyi Li, Siqing Li, Wayne Xin Zhao +4

Personalized review generation (PRG) aims to automatically produce review text reflecting user preference, which is a challenging natural language generation task. Most of previous…

cs.AI2020

Mining Implicit Entity Preference from User-Item Interaction Data for Knowledge Graph Completion via Adversarial Learning

Gaole He, Junyi Li, Wayne Xin Zhao +2

The task of Knowledge Graph Completion (KGC) aims to automatically infer the missing fact information in Knowledge Graph (KG). In this paper, we take a new perspective that aims to…

cs.IR2018

KB4Rec: A Dataset for Linking Knowledge Bases with Recommender Systems

Wayne Xin Zhao, Gaole He, Hongjian Dou +3

To develop a knowledge-aware recommender system, a key data problem is how we can obtain rich and structured knowledge information for recommender system (RS) items. Existing datas…