Kun-Peng Ning

According to our database, Kun-Peng Ning authored at least 13 papers between 2020 and 2025.

Collaborative distances:

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

2025

GPT as a Monte Carlo Language Tree: A Probabilistic Perspective.

Kun-Peng Ning, Jia-Yu Yao, Yu-Yang Liu, Mu-Nan Ning, Li Yuan

CoRR, January, 2025

Is Parameter Collision Hindering Continual Learning in LLMs?

Shuo Yang, Kun-Peng Ning, Yu-Yang Liu, Jia-Yu Yao, Yong-Hong Tian, Yi-Bing Song, Li Yuan

Proceedings of the 31st International Conference on Computational Linguistics, 2025

2024

Sparse Orthogonal Parameters Tuning for Continual Learning.

Kun-Peng Ning, Hai-Jian Ke, Yu-Yang Liu, Jia-Yu Yao, Yonghong Tian, Li Yuan

CoRR, 2024

Peer-review-in-LLMs: Automatic Evaluation Method for LLMs in Open-environment.

Kun-Peng Ning, Shuo Yang, Yu-Yang Liu, Jia-Yu Yao, Zhen-Hui Liu, Yu Wang, Ming Pang, Li Yuan

CoRR, 2024

Bidirectional Uncertainty-Based Active Learning for Open-Set Annotation.

Chen-Chen Zong, Ye-Wen Wang, Kun-Peng Ning, Haibo Ye, Sheng-Jun Huang

Proceedings of the Computer Vision - ECCV 2024, 2024

Towards Better Seach Query Classification with Distribution-Diverse Multi-Expert Knowledge Distillation in JD Ads Search.

Kun-Peng Ning, Ming Pang, Zheng Fang, Xue Jiang, Xi-Wei Zhao, Changping Peng, Zhangang Lin, Jinghe Hu, Jingping Shao, Li Yuan

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023

LLM Lies: Hallucinations are not Bugs, but Features as Adversarial Examples.

Jia-Yu Yao, Kun-Peng Ning, Zhen-Hui Liu, Munan Ning, Li Yuan

CoRR, 2023

Towards Better Query Classification with Multi-Expert Knowledge Condensation in JD Ads Search.

Kun-Peng Ning, Ming Pang, Zheng Fang, Xue Jiang, Xi-Wei Zhao, Changping Peng, Zhangang Lin, Jinghe Hu, Jingping Shao

CoRR, 2023

2022

Active Learning for Open-set Annotation.

Kun-Peng Ning, Xun Zhao, Yu Li, Sheng-Jun Huang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Co-Imitation Learning without Expert Demonstration.

Kun-Peng Ning, Hu Xu, Kun Zhu, Sheng-Jun Huang

CoRR, 2021

Asynchronous Active Learning with Distributed Label Querying.

Sheng-Jun Huang, Chen-Chen Zong, Kun-Peng Ning, Haibo Ye

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Improving Model Robustness by Adaptively Correcting Perturbation Levels with Active Queries.

Kun-Peng Ning, Lue Tao, Songcan Chen, Sheng-Jun Huang

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Reinforcement Learning with Supervision from Noisy Demonstrations.

Kun-Peng Ning, Sheng-Jun Huang

CoRR, 2020