Jinzhi Liao

Orcid: 0000-0002-2898-6559

Affiliations:
  • National University of Defense Technology, Changsha, Hunan, China


According to our database1, Jinzhi Liao authored at least 13 papers between 2017 and 2023.

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Bibliography

2023
A Unified Recombination and Adversarial Framework for Machine Reading Comprehension.
Proceedings of the Data Mining and Big Data - 8th International Conference, 2023

Multi-granularity Temporal Question Answering over Knowledge Graphs.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022
Contrastive heterogeneous graphs learning for multi-hop machine reading comprehension.
World Wide Web, 2022

Temporal knowledge graph question answering via subgraph reasoning.
Knowl. Based Syst., 2022

Complex Question Answering Over Temporal Knowledge Graphs.
Proceedings of the Web Information Systems Engineering - WISE 2022, 2022

PTAU: Prompt Tuning for Attributing Unanswerable Questions.
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

2021
To hop or not, that is the question: Towards effective multi-hop reasoning over knowledge graphs.
World Wide Web, 2021

Learning Discriminative Neural Representations for Event Detection.
Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

MOOPer: A Large-Scale Dataset of Practice-Oriented Online Learning.
Proceedings of the Knowledge Graph and Semantic Computing: Knowledge Graph Empowers New Infrastructure Construction, 2021

2019
Relevance-Based Entity Embedding.
Proceedings of the Database Systems for Advanced Applications, 2019

2018
Improving POI Recommendation via Dynamic Tensor Completion.
Sci. Program., 2018

Efficient and Accurate Traffic Flow Prediction via Incremental Tensor Completion.
IEEE Access, 2018

2017
Efficient and Accurate Traffic Flow Prediction via Fast Dynamic Tensor Completion.
Proceedings of the Traffic Mining Applied to Police Activities, 2017


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