Guangxiang Zhao

Orcid: 0000-0002-3046-512X

According to our database1, Guangxiang Zhao authored at least 15 papers between 2018 and 2023.

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

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Links

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Bibliography

2023
When to Trust Aggregated Gradients: Addressing Negative Client Sampling in Federated Learning.
CoRR, 2023

Delving into the Openness of CLIP.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022
Rethinking the Openness of CLIP.
CoRR, 2022

From Mimicking to Integrating: Knowledge Integration for Pre-Trained Language Models.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Well-Classified Examples Are Underestimated in Classification with Deep Neural Networks.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Model Uncertainty-Aware Knowledge Amalgamation for Pre-Trained Language Models.
CoRR, 2021

Well-classified Examples are Underestimated in Classification with Deep Neural Networks.
CoRR, 2021

Topology-Imbalance Learning for Semi-Supervised Node Classification.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning Relation Alignment for Calibrated Cross-modal Retrieval.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020
Layer-Wise Cross-View Decoding for Sequence-to-Sequence Learning.
CoRR, 2020

2019
Explicit Sparse Transformer: Concentrated Attention Through Explicit Selection.
CoRR, 2019

MUSE: Parallel Multi-Scale Attention for Sequence to Sequence Learning.
CoRR, 2019

Understanding and Improving Layer Normalization.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Review-Driven Multi-Label Music Style Classification by Exploiting Style Correlations.
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

2018
Review-Driven Multi-Label Music Style Classification by Exploiting Style Correlations.
CoRR, 2018


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