Qihuang Zhong
Orcid: 0009-0001-0118-5217
According to our database1,
Qihuang Zhong
authored at least 22 papers
between 2020 and 2024.
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Bibliography
2024
AdaSAM: Boosting sharpness-aware minimization with adaptive learning rate and momentum for training deep neural networks.
Neural Networks, January, 2024
ROSE Doesn't Do That: Boosting the Safety of Instruction-Tuned Large Language Models with Reverse Prompt Contrastive Decoding.
CoRR, 2024
2023
Knowledge Graph Augmented Network Towards Multiview Representation Learning for Aspect-Based Sentiment Analysis.
IEEE Trans. Knowl. Data Eng., October, 2023
Joint image and feature adaptative attention-aware networks for cross-modality semantic segmentation.
Neural Comput. Appl., February, 2023
Unified Instance and Knowledge Alignment Pretraining for Aspect-Based Sentiment Analysis.
IEEE ACM Trans. Audio Speech Lang. Process., 2023
Self-Evolution Learning for Mixup: Enhance Data Augmentation on Few-Shot Text Classification Tasks.
CoRR, 2023
AdaSAM: Boosting Sharpness-Aware Minimization with Adaptive Learning Rate and Momentum for Training Deep Neural Networks.
CoRR, 2023
CoRR, 2023
Bag of Tricks for Effective Language Model Pretraining and Downstream Adaptation: A Case Study on GLUE.
CoRR, 2023
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
Self-Evolution Learning for Mixup: Enhance Data Augmentation on Few-Shot Text Classification Tasks.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2023
2022
Toward Efficient Language Model Pretraining and Downstream Adaptation via Self-Evolution: A Case Study on SuperGLUE.
CoRR, 2022
CoRR, 2022
E2S2: Encoding-Enhanced Sequence-to-Sequence Pretraining for Language Understanding and Generation.
CoRR, 2022
Improving Sharpness-Aware Minimization with Fisher Mask for Better Generalization on Language Models.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022
A Contrastive Cross-Channel Data Augmentation Framework for Aspect-Based Sentiment Analysis.
Proceedings of the 29th International Conference on Computational Linguistics, 2022
2020