Zhen Lin

According to our database, Zhen Lin authored at least 18 papers between 2018 and 2025.

Collaborative distances:

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

2025

Uncertainty Quantification and Confidence Calibration in Large Language Models: A Survey.

Xiaoou Liu, Tiejin Chen, Longchao Da, Chacha Chen, Zhen Lin, Hua Wei

CoRR, March, 2025

MCQA-Eval: Efficient Confidence Evaluation in NLG with Gold-Standard Correctness Labels.

Xiaoou Liu, Zhen Lin, Longchao Da, Chacha Chen, Shubhendu Trivedi, Hua Wei

CoRR, February, 2025

2024

Generating with Confidence: Uncertainty Quantification for Black-box Large Language Models.

Zhen Lin, Shubhendu Trivedi, Jimeng Sun

Trans. Mach. Learn. Res., 2024

Cross-Table Pretraining towards a Universal Function Space for Heterogeneous Tabular Data.

Jintai Chen, Zhen Lin, Qiyuan Chen, Jimeng Sun

CoRR, 2024

Certifiably Byzantine-Robust Federated Conformal Prediction.

Mintong Kang, Zhen Lin, Jimeng Sun, Cao Xiao, Bo Li

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

Contextualized Sequence Likelihood: Enhanced Confidence Scores for Natural Language Generation.

Zhen Lin, Shubhendu Trivedi, Jimeng Sun

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

2023

Conformal Drug Property Prediction with Density Estimation under Covariate Shift.

Siddhartha Laghuvarapu, Zhen Lin, Jimeng Sun

CoRR, 2023

CoDrug: Conformal Drug Property Prediction with Density Estimation under Covariate Shift.

Siddhartha Laghuvarapu, Zhen Lin, Jimeng Sun

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

PyHealth: A Deep Learning Toolkit for Healthcare Applications.

Chaoqi Yang, Zhenbang Wu, Patrick Jiang, Zhen Lin, Junyi Gao, Benjamin P. Danek, Jimeng Sun

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Fast Online Value-Maximizing Prediction Sets with Conformal Cost Control.

Zhen Lin, Shubhendu Trivedi, Cao Xiao, Jimeng Sun

Proceedings of the International Conference on Machine Learning, 2023

Taking a Step Back with KCal: Multi-Class Kernel-Based Calibration for Deep Neural Networks.

Zhen Lin, Shubhendu Trivedi, Jimeng Sun

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Conformal Prediction Intervals with Temporal Dependence.

Zhen Lin, Shubhendu Trivedi, Jimeng Sun

Trans. Mach. Learn. Res., 2022

Conformal Prediction with Temporal Quantile Adjustments.

Zhen Lin, Shubhendu Trivedi, Jimeng Sun

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

SCRIB: Set-Classifier with Class-Specific Risk Bounds for Blackbox Models.

Zhen Lin, Lucas Glass, M. Brandon Westover, Cao Xiao, Jimeng Sun

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Locally Valid and Discriminative Confidence Intervals for Deep Learning Models.

Zhen Lin, Shubhendu Trivedi, Jimeng Sun

CoRR, 2021

DeepSZ: Identification of Sunyaev-Zel'dovich Galaxy Clusters using Deep Learning.

Zhen Lin, Nicholas Huang, Camille Avestruz, W. L. Kimmy Wu, Shubhendu Trivedi, João Caldeira, Brian Nord

CoRR, 2021

Locally Valid and Discriminative Prediction Intervals for Deep Learning Models.

Zhen Lin, Shubhendu Trivedi, Jimeng Sun

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2018

Clebsch-Gordan Nets: a Fully Fourier Space Spherical Convolutional Neural Network.

Risi Kondor, Zhen Lin, Shubhendu Trivedi

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018