Qihuang Zhong

According to our database, Qihuang Zhong authored at least 24 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

E2S2: Encoding-Enhanced Sequence-to-Sequence Pretraining for Language Understanding and Generation.

Qihuang Zhong, Liang Ding, Juhua Liu, Bo Du, Dacheng Tao

IEEE Trans. Knowl. Data Eng., December, 2024

PanDa: Prompt Transfer Meets Knowledge Distillation for Efficient Model Adaptation.

Qihuang Zhong, Liang Ding, Juhua Liu, Bo Du, Dacheng Tao

IEEE Trans. Knowl. Data Eng., September, 2024

AdaSAM: Boosting sharpness-aware minimization with adaptive learning rate and momentum for training deep neural networks.

Hao Sun, Li Shen, Qihuang Zhong, Liang Ding, Shixiang Chen, Jingwei Sun, Jing Li, Guangzhong Sun, Dacheng Tao

Neural Networks, January, 2024

Iterative Data Augmentation with Large Language Models for Aspect-based Sentiment Analysis.

Haiyun Li, Qihuang Zhong, Ke Zhu, Juhua Liu, Bo Du, Dacheng Tao

CoRR, 2024

Achieving >97% on GSM8K: Deeply Understanding the Problems Makes LLMs Better Reasoners.

Qihuang Zhong, Kang Wang, Ziyang Xu, Juhua Liu, Liang Ding, Bo Du, Dacheng Tao

CoRR, 2024

Learning from Imperfect Data: Towards Efficient Knowledge Distillation of Autoregressive Language Models for Text-to-SQL.

Qihuang Zhong, Kunfeng Chen, Liang Ding, Juhua Liu, Bo Du, Dacheng Tao

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

ROSE Doesn't Do That: Boosting the Safety of Instruction-Tuned Large Language Models with Reverse Prompt Contrastive Decoding.

Qihuang Zhong, Liang Ding, Juhua Liu, Bo Du, Dacheng Tao

Proceedings of the Findings of the Association for Computational Linguistics, 2024

Revisiting Knowledge Distillation for Autoregressive Language Models.

Qihuang Zhong, Liang Ding, Li Shen, Juhua Liu, Bo Du, Dacheng Tao

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

Knowledge Graph Augmented Network Towards Multiview Representation Learning for Aspect-Based Sentiment Analysis.

Qihuang Zhong, Liang Ding, Juhua Liu, Bo Du, Hua Jin, Dacheng Tao

IEEE Trans. Knowl. Data Eng., October, 2023

Joint image and feature adaptative attention-aware networks for cross-modality semantic segmentation.

Qihuang Zhong, Fanzhou Zeng, Fei Liao, Juhua Liu, Bo Du, Jedi S. Shang

Neural Comput. Appl., February, 2023

Unified Instance and Knowledge Alignment Pretraining for Aspect-Based Sentiment Analysis.

Juhua Liu, Qihuang Zhong, Liang Ding, Hua Jin, Bo Du, Dacheng Tao

IEEE ACM Trans. Audio Speech Lang. Process., 2023

Self-Evolution Learning for Mixup: Enhance Data Augmentation on Few-Shot Text Classification Tasks.

Haoqi Zheng, Qihuang Zhong, Liang Ding, Zhiliang Tian, Xin Niu, Dongsheng Li, Dacheng Tao

CoRR, 2023

Can ChatGPT Understand Too? A Comparative Study on ChatGPT and Fine-tuned BERT.

Qihuang Zhong, Liang Ding, Juhua Liu, Bo Du, Dacheng Tao

CoRR, 2023

Bag of Tricks for Effective Language Model Pretraining and Downstream Adaptation: A Case Study on GLUE.

Qihuang Zhong, Liang Ding, Keqin Peng, Juhua Liu, Bo Du, Li Shen, Yibing Zhan, Dacheng Tao

CoRR, 2023

Zero-shot Sharpness-Aware Quantization for Pre-trained Language Models.

Miaoxi Zhu, Qihuang Zhong, Li Shen, Liang Ding, Juhua Liu, Bo Du, Dacheng Tao

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.

Haoqi Zheng, Qihuang Zhong, Liang Ding, Zhiliang Tian, Xin Niu, Changjian Wang, Dongsheng Li, Dacheng Tao

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Towards Making the Most of ChatGPT for Machine Translation.

Keqin Peng, Liang Ding, Qihuang Zhong, Li Shen, Xuebo Liu, Min Zhang, Yuanxin Ouyang, Dacheng Tao

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Revisiting Token Dropping Strategy in Efficient BERT Pretraining.

Qihuang Zhong, Liang Ding, Juhua Liu, Xuebo Liu, Min Zhang, Bo Du, Dacheng Tao

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Self-Evolution Learning for Discriminative Language Model Pretraining.

Qihuang Zhong, Liang Ding, Juhua Liu, Bo Du, Dacheng Tao

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

Token-Level Self-Evolution Training for Sequence-to-Sequence Learning.

Keqin Peng, Liang Ding, Qihuang Zhong, Yuanxin Ouyang, Wenge Rong, Zhang Xiong, Dacheng Tao

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.

Qihuang Zhong, Liang Ding, Yibing Zhan, Yu Qiao, Yonggang Wen, Li Shen, Juhua Liu, Baosheng Yu, Bo Du, Yixin Chen, Xinbo Gao, Chunyan Miao, Xiaoou Tang, Dacheng Tao

CoRR, 2022

Improving Sharpness-Aware Minimization with Fisher Mask for Better Generalization on Language Models.

Qihuang Zhong, Liang Ding, Li Shen, Peng Mi, Juhua Liu, Bo Du, Dacheng Tao

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.

Bing Wang, Liang Ding, Qihuang Zhong, Ximing Li, Dacheng Tao

Proceedings of the 29th International Conference on Computational Linguistics, 2022

2020

SemiText: Scene text detection with semi-supervised learning.

Juhua Liu, Qihuang Zhong, Yuan Yuan, Hai Su, Bo Du

Neurocomputing, 2020