Peizhen Bai

According to our database, Peizhen Bai authored at least 13 papers between 2019 and 2026.

Collaborative distances:

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

2026

ESG-Bench: Benchmarking Long-Context ESG Reports for Hallucination Mitigation.

Siqi Sun, Ben Peng Wu, Mali Jin, Peizhen Bai, Hanpei Zhang, Xingyi Song

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Towards deployment-centric multimodal AI beyond vision and language.

Xianyuan Liu, Jiayang Zhang, Shuo Zhou, Thijs L. van der Plas, Avish Vijayaraghavan, Anastasiia Grishina, Mengdie Zhuang, Daniel Schofield, Christopher Tomlinson, Yuhan Wang, Ruizhe Li, Louisa van Zeeland, Sina Tabakhi, Cyndie Demeocq, Xiang Li, Arunav Das, Orlando Timmerman, Thomas Baldwin-McDonald, Jinge Wu, Peizhen Bai, Zahraa Al Sahili, Omnia Alwazzan, Thao N. Do, Mohammod Naimul Islam Suvon, Angeline Wang, Lucia Cipolina-Kun, Luigi A. Moretti, Lucas Farndale, Nitisha Jain, Natalia Efremova, Yan Ge, Marta Varela, Hak-Keung Lam, Oya Çeliktutan, Ben R. Evans, Alejandro Coca-Castro, Honghan Wu, Zahraa S. Abdallah, Chen Chen, Valentin Danchev, Nataliya Tkachenko, Lei Lu, Tingting Zhu, Gregory G. Slabaugh, Roger K. Moore, William K. Cheung, Peter H. Charlton, Haiping Lu

CoRR, April, 2025

2024

Mask prior-guided denoising diffusion improves inverse protein folding.

Peizhen Bai, Filip Miljkovic, Xianyuan Liu, Leonardo De Maria, Rebecca Croasdale-Wood, Owen J. L. Rackham, Haiping Lu

CoRR, 2024

Addressing Topic Granularity and Hallucination in Large Language Models for Topic Modelling.

Yida Mu, Peizhen Bai, Kalina Bontcheva, Xingyi Song

CoRR, 2024

2023

Interpretable bilinear attention network with domain adaptation improves drug-target prediction.

Peizhen Bai, Filip Miljkovic, Bino John, Haiping Lu

Nat. Mac. Intell., February, 2023

GripNet: Graph information propagation on supergraph for heterogeneous graphs.

Hao Xu, Shengqi Sang, Peizhen Bai, Ruike Li, Laurence Yang, Haiping Lu

Pattern Recognit., 2023

Geometry-aware Line Graph Transformer Pre-training for Molecular Property Prediction.

Peizhen Bai, Xianyuan Liu, Haiping Lu

CoRR, 2023

2022

PyKale: Knowledge-Aware Machine Learning from Multiple Sources in Python.

Haiping Lu, Xianyuan Liu, Shuo Zhou, Robert Turner, Peizhen Bai, Raivo E. Koot, Mustafa Chasmai, Lawrence Schobs, Hao Xu

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021

PyKale: Knowledge-Aware Machine Learning from Multiple Sources in Python.

Haiping Lu, Xianyuan Liu, Robert Turner, Peizhen Bai, Raivo E. Koot, Shuo Zhou, Mustafa Chasmai, Lawrence Schobs

CoRR, 2021

Hierarchical Clustering Split for Low-Bias Evaluation of Drug-Target Interaction Prediction.

Peizhen Bai, Filip Miljkovic, Yan Ge, Nigel Greene, Bino John, Haiping Lu

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

2020

GripNet: Graph Information Propagation on Supergraph for Heterogeneous Graphs.

Hao Xu, Shengqi Sang, Peizhen Bai, Laurence T. Yang, Haiping Lu

CoRR, 2020

2019

Corrigendum to "Joint interaction with context operation for collaborative filtering" [Pattern Recognition 88 (2019) 729-738].

Peizhen Bai, Yan Ge, Fangling Liu, Haiping Lu

Pattern Recognit., 2019

Joint interaction with context operation for collaborative filtering.

Peizhen Bai, Yan Ge, Fangling Liu, Haiping Lu

Pattern Recognit., 2019