Search Results for author: Yuzhong Qu

Found 22 papers, 13 papers with code

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

1 code implementation23 Nov 2022 Xiao Li, Yin Zhu, Sichen Liu, Jiangzhou Ju, Yuzhong Qu, Gong Cheng

Numerical reasoning over hybrid data containing tables and long texts has recently received research attention from the AI community.

Retrieval

Semantic Framework based Query Generation for Temporal Question Answering over Knowledge Graphs

no code implementations10 Oct 2022 Weantao Ding, Hao Chen, Huayu Li, Yuzhong Qu

Answering factual questions with temporal intent over knowledge graphs (temporal KGQA) attracts rising attention in recent years.

Knowledge Graphs Question Answering

Automatic Rule Generation for Time Expression Normalization

1 code implementation Findings (EMNLP) 2021 Wentao Ding, Jianhao Chen, Jinmao Li, Yuzhong Qu

The understanding of time expressions includes two sub-tasks: recognition and normalization.

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

1 code implementation Findings (EMNLP) 2021 Zixian Huang, Ao Wu, Yulin Shen, Gong Cheng, Yuzhong Qu

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.

Multiple-choice Question Answering +1

TransEdge: Translating Relation-contextualized Embeddings for Knowledge Graphs

1 code implementation22 Apr 2020 Zequn Sun, Jiacheng Huang, Wei Hu, Muchao Chen, Lingbing Guo, Yuzhong Qu

We refer to such contextualized representations of a relation as edge embeddings and interpret them as translations between entity embeddings.

Entity Alignment Entity Embeddings +2

SPARQA: Skeleton-based Semantic Parsing for Complex Questions over Knowledge Bases

1 code implementation31 Mar 2020 Yawei Sun, Lingling Zhang, Gong Cheng, Yuzhong Qu

This dedicated coarse-grained formalism with a BERT-based parsing algorithm helps to improve the accuracy of the downstream fine-grained semantic parsing.

Semantic Parsing

DeepLENS: Deep Learning for Entity Summarization

1 code implementation8 Mar 2020 Qingxia Liu, Gong Cheng, Yuzhong Qu

Entity summarization has been a prominent task over knowledge graphs.

Knowledge Graphs

ESBM: An Entity Summarization BenchMark

no code implementations8 Mar 2020 Qingxia Liu, Gong Cheng, Kalpa Gunaratna, Yuzhong Qu

In this paper, we create an Entity Summarization BenchMark (ESBM) which overcomes the limitations of existing benchmarks and meets standard desiderata for a benchmark.

Knowledge Graph Alignment Network with Gated Multi-hop Neighborhood Aggregation

1 code implementation20 Nov 2019 Zequn Sun, Chengming Wang, Wei Hu, Muhao Chen, Jian Dai, Wei zhang, Yuzhong Qu

As the direct neighbors of counterpart entities are usually dissimilar due to the schema heterogeneity, AliNet introduces distant neighbors to expand the overlap between their neighborhood structures.

Entity Alignment Knowledge Graphs

Entity Summarization: State of the Art and Future Challenges

no code implementations18 Oct 2019 Qingxia Liu, Gong Cheng, Kalpa Gunaratna, Yuzhong Qu

This has motivated fruitful research on automated generation of summaries for entity descriptions to satisfy users' information needs efficiently and effectively.

Combinatorial Optimization Information Retrieval +2

Leveraging Frequent Query Substructures to Generate Formal Queries for Complex Question Answering

no code implementations IJCNLP 2019 Jiwei Ding, Wei Hu, Qixin Xu, Yuzhong Qu

Formal query generation aims to generate correct executable queries for question answering over knowledge bases (KBs), given entity and relation linking results.

Question Answering Relation Linking

A Framework for Evaluating Snippet Generation for Dataset Search

no code implementations2 Jul 2019 Xiaxia Wang, Jinchi Chen, Shuxin Li, Gong Cheng, Jeff Z. Pan, Evgeny Kharlamov, Yuzhong Qu

Reusing existing datasets is of considerable significance to researchers and developers.

DSKG: A Deep Sequential Model for Knowledge Graph Completion

1 code implementation30 Oct 2018 Lingbing Guo, Qingheng Zhang, Weiyi Ge, Wei Hu, Yuzhong Qu

Knowledge graph (KG) completion aims to fill the missing facts in a KG, where a fact is represented as a triple in the form of $(subject, relation, object)$.

Knowledge Graph Completion

Graph-based Ontology Summarization: A Survey

no code implementations15 May 2018 Seyedamin Pouriyeh, Mehdi Allahyari, Qingxia Liu, Gong Cheng, Hamid Reza Arabnia, Yuzhong Qu, Krys Kochut

Ontologies have been widely used in numerous and varied applications, e. g., to support data modeling, information integration, and knowledge management.

Information Retrieval

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