Yiming Ju

According to our database, Yiming Ju authored at least 15 papers between 2021 and 2024.

Collaborative distances:

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

2024

Explanation Guided Knowledge Distillation for Pre-trained Language Model Compression.

Zhao Yang, Yuanzhe Zhang, Dianbo Sui, Yiming Ju, Jun Zhao, Kang Liu

ACM Trans. Asian Low Resour. Lang. Inf. Process., February, 2024

Mitigating Training Imbalance in LLM Fine-Tuning via Selective Parameter Merging.

Yiming Ju, Ziyi Ni, Xingrun Xing, Zhixiong Zeng, Hanyu Zhao, Siqi Fan, Zheng Zhang

CoRR, 2024

Beyond IID: Optimizing Instruction Learning from the Perspective of Instruction Interaction and Dependency.

Hanyu Zhao, Li Du, Yiming Ju, Chengwei Wu, Tengfei Pan

CoRR, 2024

AquilaMoE: Efficient Training for MoE Models with Scale-Up and Scale-Out Strategies.

Bo-Wen Zhang, Liangdong Wang, Ye Yuan, Jijie Li, Shuhao Gu, Mengdi Zhao, Xinya Wu, Guang Liu, Chengwei Wu, Hanyu Zhao, Li Du, Yiming Ju, Quanyue Ma, Yulong Ao, Yingli Zhao, Songhe Zhu, Zhou Cao, Dong Liang, Yonghua Lin, Ming Zhang, Shunfei Wang, Yanxin Zhou, Min Ye, Xuekai Chen, Xinyang Yu, Xiangjun Huang, Jian Yang

CoRR, 2024

SpikeLM: Towards General Spike-Driven Language Modeling via Elastic Bi-Spiking Mechanisms.

Xingrun Xing, Zheng Zhang, Ziyi Ni, Shitao Xiao, Yiming Ju, Siqi Fan, Yequan Wang, Jiajun Zhang, Guoqi Li

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Mitigating Training Imbalance in LLM Fine-Tuning via Selective Parameter Merging.

Yiming Ju, Ziyi Ni, Xingrun Xing, Zhixiong Zeng, Hanyu Zhao, Siqi Fan, Zheng Zhang

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023

KLoB: a Benchmark for Assessing Knowledge Locating Methods in Language Models.

Yiming Ju, Zheng Zhang

CoRR, 2023

Unsupervised Text Style Transfer with Deep Generative Models.

Zhongtao Jiang, Yuanzhe Zhang, Yiming Ju, Kang Liu

CoRR, 2023

A Hierarchical Explanation Generation Method Based on Feature Interaction Detection.

Yiming Ju, Yuanzhe Zhang, Kang Liu, Jun Zhao

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

2022

Generating Hierarchical Explanations on Text Classification Without Connecting Rules.

Yiming Ju, Yuanzhe Zhang, Kang Liu, Jun Zhao

CoRR, 2022

CMQA: A Dataset of Conditional Question Answering with Multiple-Span Answers.

Yiming Ju, Weikang Wang, Yuanzhe Zhang, Suncong Zheng, Kang Liu, Jun Zhao

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

Can We Really Trust Explanations? Evaluating the Stability of Feature Attribution Explanation Methods via Adversarial Attack.

Zhao Yang, Yuanzhe Zhang, Zhongtao Jiang, Yiming Ju, Jun Zhao, Kang Liu

Proceedings of the Chinese Computational Linguistics - 21st China National Conference, 2022

Logic Traps in Evaluating Attribution Scores.

Yiming Ju, Yuanzhe Zhang, Zhao Yang, Zhongtao Jiang, Kang Liu, Jun Zhao

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021

The Logic Traps in Evaluating Post-hoc Interpretations.

Yiming Ju, Yuanzhe Zhang, Zhao Yang, Zhongtao Jiang, Kang Liu, Jun Zhao

CoRR, 2021

Enhancing Multiple-choice Machine Reading Comprehension by Punishing Illogical Interpretations.

Yiming Ju, Yuanzhe Zhang, Zhixing Tian, Kang Liu, Xiaohuan Cao, Wenting Zhao, Jinlong Li, Jun Zhao

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021