Baijiong Lin

According to our database, Baijiong Lin authored at least 24 papers between 2020 and 2026.

Collaborative distances:

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

2026

RAIN-Merging: A Gradient-Free Method to Enhance Instruction Following in Large Reasoning Models with Preserved Thinking Format.

Zhehao Huang, Yuhang Liu, Baijiong Lin, Yixin Lou, Zhengbao He, Hanling Tian, Tao Li, Xiaolin Huang

CoRR, February, 2026

Dual-balancing for multi-task learning.

Baijiong Lin, Weisen Jiang, Feiyang Ye, Yu Zhang, Pengguang Chen, Ying-Cong Chen, Shu Liu, Ivor W. Tsang, James T. Kwok

Neural Networks, 2026

Efficient Reasoning for Large Reasoning Language Models via Certainty-Guided Reflection Suppression.

Jiameng Huang, Baijiong Lin, Guhao Feng, Jierun Chen, Di He, Lu Hou

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

VL-RouterBench: A Benchmark for Vision-Language Model Routing.

Zhehao Huang, Baijiong Lin, Jingyuan Zhang, Jingying Wang, Yuhang Liu, Ning Lu, Tao Li, Xiaolin Huang

CoRR, December, 2025

MTMamba++: Enhancing Multi-Task Dense Scene Understanding via Mamba-Based Decoders.

Baijiong Lin, Weisen Jiang, Pengguang Chen, Shu Liu, Ying-Cong Chen

IEEE Trans. Pattern Anal. Mach. Intell., November, 2025

V-ReasonBench: Toward Unified Reasoning Benchmark Suite for Video Generation Models.

Yang Luo, Xuanlei Zhao, Baijiong Lin, Lingting Zhu, Liyao Tang, Yuqi Liu, Ying-Cong Chen, Shengju Qian, Xin Wang, Yang You

CoRR, November, 2025

Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond.

Weiyu Chen, Xiaoyuan Zhang, Baijiong Lin, Xi Lin, Han Zhao, Qingfu Zhang, James T. Kwok

CoRR, January, 2025

PARM: Multi-Objective Test-Time Alignment via Preference-Aware Autoregressive Reward Model.

Baijiong Lin, Weisen Jiang, Yuancheng Xu, Hao Chen, Ying-Cong Chen

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Multi-objective meta-learning.

Feiyang Ye, Baijiong Lin, Zhixiong Yue, Yu Zhang, Ivor W. Tsang

Artif. Intell., 2024

RouterDC: Query-Based Router by Dual Contrastive Learning for Assembling Large Language Models.

Shuhao Chen, Weisen Jiang, Baijiong Lin, James T. Kwok, Yu Zhang

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Bridging Data Gaps in Diffusion Models with Adversarial Noise-Based Transfer Learning.

Xiyu Wang, Baijiong Lin, Daochang Liu, Ying-Cong Chen, Chang Xu

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

MTMamba: Enhancing Multi-task Dense Scene Understanding by Mamba-Based Decoders.

Baijiong Lin, Weisen Jiang, Pengguang Chen, Yu Zhang, Shu Liu, Ying-Cong Chen

Proceedings of the Computer Vision - ECCV 2024, 2024

A First-Order Multi-Gradient Algorithm for Multi-Objective Bi-Level Optimization.

Feiyang Ye, Baijiong Lin, Xiaofeng Cao, Yu Zhang, Ivor W. Tsang

Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

2023

LibMTL: A Python Library for Deep Multi-Task Learning.

Baijiong Lin, Yu Zhang

J. Mach. Learn. Res., 2023

Effective and Parameter-Efficient Reusing Fine-Tuned Models.

Weisen Jiang, Baijiong Lin, Han Shi, Yu Zhang, Zhenguo Li, James T. Kwok

CoRR, 2023

A Scale-Invariant Task Balancing Approach for Multi-Task Learning.

Baijiong Lin, Weisen Jiang, Feiyang Ye, Yu Zhang, Pengguang Chen, Ying-Cong Chen, Shu Liu

CoRR, 2023

Efficient Transfer Learning in Diffusion Models via Adversarial Noise.

Xiyu Wang, Baijiong Lin, Daochang Liu, Chang Xu

CoRR, 2023

2022

Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning.

Baijiong Lin, Feiyang Ye, Yu Zhang, Ivor W. Tsang

Trans. Mach. Learn. Res., 2022

LibMTL: A Python Library for Multi-Task Learning.

Baijiong Lin, Yu Zhang

CoRR, 2022

Effective, Efficient and Robust Neural Architecture Search.

Zhixiong Yue, Baijiong Lin, Yu Zhang, Christy Jie Liang

Proceedings of the International Joint Conference on Neural Networks, 2022

2021

A Closer Look at Loss Weighting in Multi-Task Learning.

Baijiong Lin, Feiyang Ye, Yu Zhang

CoRR, 2021

Multi-Objective Meta Learning.

Feiyang Ye, Baijiong Lin, Zhixiong Yue, Pengxin Guo, Qiao Xiao, Yu Zhang

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

2020

Multi-Task Adversarial Attack.

Pengxin Guo, Yuancheng Xu, Baijiong Lin, Yu Zhang

CoRR, 2020

Effective, Efficient and Robust Neural Architecture Search.

Zhixiong Yue, Baijiong Lin, Xiaonan Huang, Yu Zhang

CoRR, 2020