Effective, Efficient and Robust Neural Architecture Search. - Zhixiong Yue; Baijiong Lin; Xiaonan Huang; Yu Zhang 006 (CoRR, 2020)

Multi-Task Adversarial Attack. - Pengxin Guo; Yuancheng Xu; Baijiong Lin; Yu Zhang 006 (CoRR, 2020)

Multi-Objective Meta Learning. - Feiyang Ye 001; Baijiong Lin; Zhixiong Yue; Pengxin Guo; Qiao Xiao; Yu Zhang 006 (NeurIPS, 2021)

A Closer Look at Loss Weighting in Multi-Task Learning. - Baijiong Lin; Feiyang Ye 001; Yu Zhang 006 (CoRR, 2021)

Effective, Efficient and Robust Neural Architecture Search. - Zhixiong Yue; Baijiong Lin; Yu Zhang 006; Christy Jie Liang (IJCNN, 2022)

LibMTL: A Python Library for Multi-Task Learning. - Baijiong Lin; Yu Zhang 006 (CoRR, 2022)

Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning. - Baijiong Lin; Feiyang Ye 001; Yu Zhang 006; Ivor W. Tsang (Trans. Mach. Learn. Res., 2022)

Efficient Transfer Learning in Diffusion Models via Adversarial Noise. - Xiyu Wang; Baijiong Lin; Daochang Liu; Chang Xu 002 (CoRR, 2023)

A Scale-Invariant Task Balancing Approach for Multi-Task Learning. - Baijiong Lin; Weisen Jiang; Feiyang Ye 001; Yu Zhang 006; Pengguang Chen; Ying-Cong Chen; Shu Liu 005 (CoRR, 2023)

Effective and Parameter-Efficient Reusing Fine-Tuned Models. - Weisen Jiang; Baijiong Lin; Han Shi; Yu Zhang 006; Zhenguo Li; James T. Kwok (CoRR, 2023)

LibMTL: A Python Library for Deep Multi-Task Learning. - Baijiong Lin; Yu Zhang 006 (J. Mach. Learn. Res., 2023)

A First-Order Multi-Gradient Algorithm for Multi-Objective Bi-Level Optimization. - Feiyang Ye 001; Baijiong Lin; Xiaofeng Cao 002; Yu Zhang 006; Ivor W. Tsang (ECAI, 2024)

MTMamba: Enhancing Multi-task Dense Scene Understanding by Mamba-Based Decoders. - Baijiong Lin; Weisen Jiang; Pengguang Chen; Yu Zhang 006; Shu Liu 005; Ying-Cong Chen (ECCV (70), 2024)

Bridging Data Gaps in Diffusion Models with Adversarial Noise-Based Transfer Learning. - Xiyu Wang; Baijiong Lin; Daochang Liu; Ying-Cong Chen; Chang Xu 002 (ICML, 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 006 (NeurIPS, 2024)

Multi-objective meta-learning. - Feiyang Ye 001; Baijiong Lin; Zhixiong Yue; Yu Zhang 006; Ivor W. Tsang (Artif. Intell., 2024)

MTMamba++: Enhancing Multi-Task Dense Scene Understanding via Mamba-Based Decoders. - Baijiong Lin; Weisen Jiang; Pengguang Chen; Shu Liu 005; Ying-Cong Chen (CoRR, 2024)

Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond. - Weiyu Chen; Xiaoyuan Zhang; Baijiong Lin; Xi Lin 001; Han Zhao 002; Qingfu Zhang 001; James T. Kwok (CoRR, 2025)

PARM: Multi-Objective Test-Time Alignment via Preference-Aware Autoregressive Reward Model. - Baijiong Lin; Weisen Jiang; Yuancheng Xu; Hao Chen; Ying-Cong Chen (CoRR, 2025)

Efficient Reasoning for Large Reasoning Language Models via Certainty-Guided Reflection Suppression. - Jiameng Huang; Baijiong Lin; Guhao Feng; Jierun Chen; Di He; Lu Hou (CoRR, 2025)