Baijiong Lin - RankMe

31 papers A* 5A 1B 1Journal 23Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Dual-balancing for multi-task learning. Neural Networks Baijiong Lin, Weisen Jiang, Feiyang Ye, Yu Zhang, Pengguang Chen, Ying-Cong Chen, Shu Liu, Ivor W. Tsang, James T. Kwok
2026	A*	`conf`	Efficient Reasoning for Large Reasoning Language Models via Certainty-Guided Reflection Suppression. AAAI Jiameng Huang, Baijiong Lin, Guhao Feng, Jierun Chen, Di He, Lu Hou
2026	J	`jnl`	RAIN-Merging: A Gradient-Free Method to Enhance Instruction Following in Large Reasoning Models with Preserved Thinking Format. CoRR Zhehao Huang, Yuhang Liu, Baijiong Lin, Yixin Lou, Zhengbao He, Hanling Tian, Tao Li, Xiaolin Huang
2025	J	`jnl`	Efficient Reasoning for Large Reasoning Language Models via Certainty-Guided Reflection Suppression. CoRR Jiameng Huang, Baijiong Lin, Guhao Feng, Jierun Chen, Di He, Lu Hou
2025	J	`jnl`	Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond. CoRR Weiyu Chen, Xiaoyuan Zhang, Baijiong Lin, Xi Lin, Han Zhao, Qingfu Zhang, James T. Kwok
2025	J	`jnl`	MTMamba++: Enhancing Multi-Task Dense Scene Understanding via Mamba-Based Decoders. IEEE Trans. Pattern Anal. Mach. Intell. Baijiong Lin, Weisen Jiang, Pengguang Chen, Shu Liu, Ying-Cong Chen
2025	A*	`conf`	PARM: Multi-Objective Test-Time Alignment via Preference-Aware Autoregressive Reward Model. ICML Baijiong Lin, Weisen Jiang, Yuancheng Xu, Hao Chen, Ying-Cong Chen
2025	J	`jnl`	PARM: Multi-Objective Test-Time Alignment via Preference-Aware Autoregressive Reward Model. CoRR Baijiong Lin, Weisen Jiang, Yuancheng Xu, Hao Chen, Ying-Cong Chen
2025	J	`jnl`	V-ReasonBench: Toward Unified Reasoning Benchmark Suite for Video Generation Models. CoRR Yang Luo, Xuanlei Zhao, Baijiong Lin, Lingting Zhu, Liyao Tang, Yuqi Liu, Ying-Cong Chen, Shengju Qian, Xin Wang, Yang You
2025	J	`jnl`	VL-RouterBench: A Benchmark for Vision-Language Model Routing. CoRR Zhehao Huang, Baijiong Lin, Jingyuan Zhang, Jingying Wang, Yuhang Liu, Ning Lu, Tao Li, Xiaolin Huang
2024	A	`conf`	A First-Order Multi-Gradient Algorithm for Multi-Objective Bi-Level Optimization. ECAI Feiyang Ye, Baijiong Lin, Xiaofeng Cao, Yu Zhang, Ivor W. Tsang
2024	J	`jnl`	A First-Order Multi-Gradient Algorithm for Multi-Objective Bi-Level Optimization. CoRR Feiyang Ye, Baijiong Lin, Xiaofeng Cao, Yu Zhang, Ivor W. Tsang
2024	A*	`conf`	Bridging Data Gaps in Diffusion Models with Adversarial Noise-Based Transfer Learning. ICML Xiyu Wang, Baijiong Lin, Daochang Liu, Ying-Cong Chen, Chang Xu
2024	J	`jnl`	MTMamba++: Enhancing Multi-Task Dense Scene Understanding via Mamba-Based Decoders. CoRR Baijiong Lin, Weisen Jiang, Pengguang Chen, Shu Liu, Ying-Cong Chen
2024	J	`jnl`	MTMamba: Enhancing Multi-Task Dense Scene Understanding by Mamba-Based Decoders. CoRR Baijiong Lin, Weisen Jiang, Pengguang Chen, Yu Zhang, Shu Liu, Ying-Cong Chen
2024	—	`conf`	MTMamba: Enhancing Multi-task Dense Scene Understanding by Mamba-Based Decoders. ECCV (70) Baijiong Lin, Weisen Jiang, Pengguang Chen, Yu Zhang, Shu Liu, Ying-Cong Chen
2024	J	`jnl`	Multi-objective meta-learning. Artif. Intell. Feiyang Ye, Baijiong Lin, Zhixiong Yue, Yu Zhang, Ivor W. Tsang
2024	A*	`conf`	RouterDC: Query-Based Router by Dual Contrastive Learning for Assembling Large Language Models. NeurIPS Shuhao Chen, Weisen Jiang, Baijiong Lin, James T. Kwok, Yu Zhang
2024	J	`jnl`	RouterDC: Query-Based Router by Dual Contrastive Learning for Assembling Large Language Models. CoRR Shuhao Chen, Weisen Jiang, Baijiong Lin, James T. Kwok, Yu Zhang
2023	J	`jnl`	A Scale-Invariant Task Balancing Approach for Multi-Task Learning. CoRR Baijiong Lin, Weisen Jiang, Feiyang Ye, Yu Zhang, Pengguang Chen, Ying-Cong Chen, Shu Liu
2023	J	`jnl`	Effective and Parameter-Efficient Reusing Fine-Tuned Models. CoRR Weisen Jiang, Baijiong Lin, Han Shi, Yu Zhang, Zhenguo Li, James T. Kwok
2023	J	`jnl`	Efficient Transfer Learning in Diffusion Models via Adversarial Noise. CoRR Xiyu Wang, Baijiong Lin, Daochang Liu, Chang Xu
2023	J	`jnl`	LibMTL: A Python Library for Deep Multi-Task Learning. J. Mach. Learn. Res. Baijiong Lin, Yu Zhang
2022	B	`conf`	Effective, Efficient and Robust Neural Architecture Search. IJCNN Zhixiong Yue, Baijiong Lin, Yu Zhang, Christy Jie Liang
2022	J	`jnl`	LibMTL: A Python Library for Multi-Task Learning. CoRR Baijiong Lin, Yu Zhang
2022	J	`jnl`	Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning. Trans. Mach. Learn. Res. Baijiong Lin, Feiyang Ye, Yu Zhang, Ivor W. Tsang
2021	J	`jnl`	A Closer Look at Loss Weighting in Multi-Task Learning. CoRR Baijiong Lin, Feiyang Ye, Yu Zhang
2021	A*	`conf`	Multi-Objective Meta Learning. NeurIPS Feiyang Ye, Baijiong Lin, Zhixiong Yue, Pengxin Guo, Qiao Xiao, Yu Zhang
2021	J	`jnl`	Multi-Objective Meta Learning. CoRR Feiyang Ye, Baijiong Lin, Zhixiong Yue, Pengxin Guo, Qiao Xiao, Yu Zhang
2020	J	`jnl`	Effective, Efficient and Robust Neural Architecture Search. CoRR Zhixiong Yue, Baijiong Lin, Xiaonan Huang, Yu Zhang
2020	J	`jnl`	Multi-Task Adversarial Attack. CoRR Pengxin Guo, Yuancheng Xu, Baijiong Lin, Yu Zhang