Songlin Zhai

Orcid: 0000-0003-2666-9952

According to our database1, Songlin Zhai authored at least 13 papers between 2018 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2026
IGen: Redefining long-term event prediction with iterative generation and dynamic balancing.
Inf. Process. Manag., 2026

2025
KG-Attention: Knowledge Graph-Guided Attention at Test-Time via Bidirectional Information Aggregation.
CoRR, July, 2025

Harnessing Diverse Perspectives: A Multi-Agent Framework for Enhanced Error Detection in Knowledge Graphs.
CoRR, January, 2025

DST: Continual event prediction by decomposing and synergizing the task commonality and specificity.
Inf. Process. Manag., 2025

TEF: Causality-Aware Taxonomy Expansion via Front-Door Criterion.
Proceedings of the 31st International Conference on Computational Linguistics, 2025

Parameter-Aware Contrastive Knowledge Editing: Tracing and Rectifying based on Critical Transmission Paths.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024
Which is better? Taxonomy induction with learning the optimal structure via contrastive learning.
Knowl. Based Syst., 2024

Event is more valuable than you think: Improving the Similar Legal Case Retrieval via event knowledge.
Inf. Process. Manag., 2024

Can Large Language Models Understand DL-Lite Ontologies? An Empirical Study.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Attributed Triple Extraction by Combination Under Contrastive Learning.
Proceedings of the Database Systems for Advanced Applications, 2024

2023
DNG: Taxonomy Expansion by Exploring the Intrinsic Directed Structure on Non-gaussian Space.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2021
VSE-fs: Fast Full-Sample Visual Semantic Embedding.
IEEE Intell. Syst., 2021

2018
VSE-ens: Visual-Semantic Embeddings with Efficient Negative Sampling.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018


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