Kangshuo Li

According to our database, Kangshuo Li authored at least 11 papers between 2023 and 2026.

Collaborative distances:

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

2026

Survey of uncertainty estimation in LLMs - Sources, methods, applications, and challenges.

Jianfeng He, Linlin Yu, Changbin Li, Runing Yang, Fanglan Chen, Kangshuo Li, Min Zhang, Shuo Lei, Xuchao Zhang, Mohammad Beigi, Kaize Ding, Bei Xiao, Lifu Huang, Feng Chen, Ming Jin, Chang-Tien Lu

Inf. Fusion, 2026

Conditional Contrastive Confidence-Based Uncertainty Quantification for LLMs.

Yifan Zhang, Yuzhe Ou, Kangshuo Li, Feng Chen

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2026

2025

Measuring Aleatoric and Epistemic Uncertainty in LLMs: Empirical Evaluation on ID and OOD QA Tasks.

Kevin Wang, Subre Abdoul Moktar, Jia Li, Kangshuo Li, Feng Chen

CoRR, November, 2025

Predictive Uncertainty Quantification for Bird's Eye View Segmentation: A Benchmark and Novel Loss Function.

Linlin Yu, Bowen Yang, Tianhao Wang, Kangshuo Li, Feng Chen

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Large Language Models with Reinforcement Learning from Human Feedback Approach for Enhancing Explainable Sexism Detection.

Ali Riahi Samani, Tianhao Wang, Kangshuo Li, Feng Chen

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

Evidential Uncertainty Probes for Graph Neural Networks.

Linlin Yu, Kangshuo Li, Pritom Kumar Saha, Yifei Lou, Feng Chen

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

FedFMSL: Federated Learning of Foundation Models With Sparsely Activated LoRA.

Panlong Wu, Kangshuo Li, Ting Wang, Yanjie Dong, Victor C. M. Leung, Fangxin Wang

IEEE Trans. Mob. Comput., December, 2024

Federated In-Context LLM Agent Learning.

Panlong Wu, Kangshuo Li, Junbao Nan, Fangxin Wang

CoRR, 2024

Uncertainty Quantification for Bird's Eye View Semantic Segmentation: Methods and Benchmarks.

Linlin Yu, Bowen Yang, Tianhao Wang, Kangshuo Li, Feng Chen

CoRR, 2024

Hyper Evidential Deep Learning to Quantify Composite Classification Uncertainty.

Changbin Li, Kangshuo Li, Yuzhe Ou, Lance M. Kaplan, Audun Jøsang, Jin-Hee Cho, Dong Hyun Jeong, Feng Chen

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

FedMS: Federated Learning with Mixture of Sparsely Activated Foundations Models.

Panlong Wu, Kangshuo Li, Ting Wang, Fangxin Wang

CoRR, 2023