activity
20182023
most citedMulti-view Knowledge Graph Embedding for Entity Alignment

21 citations · 54 across the 10 of their papers we have counts for

collaborators

18 papers

cs.CL2023

Question Decomposition Tree for Answering Complex Questions over Knowledge Bases

Xiang Huang, Sitao Cheng, Yiheng Shu +2

Knowledge base question answering (KBQA) has attracted a lot of interest in recent years, especially for complex questions which require multiple facts to answer. Question decompos…

cs.CL2022

DyRRen: A Dynamic Retriever-Reranker-Generator Model for Numerical Reasoning over Tabular and Textual Data

Xiao Li, Yin Zhu, Sichen Liu +3

Numerical reasoning over hybrid data containing tables and long texts has recently received research attention from the AI community. To generate an executable reasoning program co…

cs.CL20229 cited

TIARA: Multi-grained Retrieval for Robust Question Answering over Large Knowledge Bases

Yiheng Shu, Zhiwei Yu, Yuhan Li +4

Pre-trained language models (PLMs) have shown their effectiveness in multiple scenarios. However, KBQA remains challenging, especially regarding coverage and generalization setting…

cs.CL20221 cited

AdaLoGN: Adaptive Logic Graph Network for Reasoning-Based Machine Reading Comprehension

Xiao Li, Gong Cheng, Ziheng Chen +2

Recent machine reading comprehension datasets such as ReClor and LogiQA require performing logical reasoning over text. Conventional neural models are insufficient for logical reas…

cs.CL2021

When Retriever-Reader Meets Scenario-Based Multiple-Choice Questions

Zixian Huang, Ao Wu, Yulin Shen +2

Scenario-based question answering (SQA) requires retrieving and reading paragraphs from a large corpus to answer a question which is contextualized by a long scenario description.…

cs.AI20202 cited

TransEdge: Translating Relation-contextualized Embeddings for Knowledge Graphs

Zequn Sun, Jiacheng Huang, Wei Hu +3

Learning knowledge graph (KG) embeddings has received increasing attention in recent years. Most embedding models in literature interpret relations as linear or bilinear mapping fu…