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2020 – today
- 2024
[c8]Weisen Jiang, Han Shi, Longhui Yu, Zhengying Liu, Yu Zhang, Zhenguo Li, James T. Kwok:
Forward-Backward Reasoning in Large Language Models for Mathematical Verification. ACL (Findings) 2024: 6647-6661- [c7]Longhui Yu, Weisen Jiang, Han Shi, Jincheng Yu, Zhengying Liu, Yu Zhang, James T. Kwok, Zhenguo Li, Adrian Weller, Weiyang Liu:
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models. ICLR 2024 - [c6]Xuehao Wang, Weisen Jiang, Shuai Fu, Yu Zhang:
Enhancing Sharpness-Aware Minimization by Learning Perturbation Radius. ECML/PKDD (2) 2024: 375-391 - [i14]Shuhao Chen, Yulong Zhang, Weisen Jiang, Jiangang Lu, Yu Zhang:
Large Language Models as Visual Cross-Domain Learners. CoRR abs/2401.03253 (2024) - [i13]Yanbin Wei
, Shuai Fu, Weisen Jiang, James T. Kwok, Yu Zhang:
Rendering Graphs for Graph Reasoning in Multimodal Large Language Models. CoRR abs/2402.02130 (2024) - [i12]Baijiong Lin, Weisen Jiang, Pengguang Chen, Yu Zhang, Shu Liu, Ying-Cong Chen:
MTMamba: Enhancing Multi-Task Dense Scene Understanding by Mamba-Based Decoders. CoRR abs/2407.02228 (2024) - [i11]Tao Li, Weisen Jiang, Fanghui Liu, Xiaolin Huang, James T. Kwok:
Learning Scalable Model Soup on a Single GPU: An Efficient Subspace Training Strategy. CoRR abs/2407.03641 (2024) - [i10]Xuehao Wang, Weisen Jiang, Shuai Fu, Yu Zhang:
Enhancing Sharpness-Aware Minimization by Learning Perturbation Radius. CoRR abs/2408.08222 (2024) - [i9]Baijiong Lin, Weisen Jiang, Pengguang Chen, Shu Liu, Ying-Cong Chen:
MTMamba++: Enhancing Multi-Task Dense Scene Understanding via Mamba-Based Decoders. CoRR abs/2408.15101 (2024) - [i8]Shuhao Chen, Weisen Jiang, Baijiong Lin, James T. Kwok, Yu Zhang:
RouterDC: Query-Based Router by Dual Contrastive Learning for Assembling Large Language Models. CoRR abs/2409.19886 (2024) - 2023
- [c5]Weisen Jiang, Hansi Yang, Yu Zhang, James T. Kwok:
An Adaptive Policy to Employ Sharpness-Aware Minimization. ICLR 2023 - [c4]Weisen Jiang, Yu Zhang, James T. Kwok:
Effective Structured Prompting by Meta-Learning and Representative Verbalizer. ICML 2023: 15186-15199 - [i7]Weisen Jiang, Hansi Yang, Yu Zhang, James T. Kwok:
An Adaptive Policy to Employ Sharpness-Aware Minimization. CoRR abs/2304.14647 (2023) - [i6]Weisen Jiang, Yu Zhang, James T. Kwok:
Effective Structured Prompting by Meta-Learning and Representative Verbalizer. CoRR abs/2306.00618 (2023) - [i5]Weisen Jiang, Han Shi, Longhui Yu, Zhengying Liu, Yu Zhang, Zhenguo Li, James T. Kwok:
Forward-Backward Reasoning in Large Language Models for Verification. CoRR abs/2308.07758 (2023) - [i4]Baijiong Lin, Weisen Jiang, Feiyang Ye, Yu Zhang, Pengguang Chen, Ying-Cong Chen, Shu Liu:
A Scale-Invariant Task Balancing Approach for Multi-Task Learning. CoRR abs/2308.12029 (2023) - [i3]Longhui Yu, Weisen Jiang, Han Shi, Jincheng Yu, Zhengying Liu, Yu Zhang, James T. Kwok, Zhenguo Li, Adrian Weller, Weiyang Liu:
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models. CoRR abs/2309.12284 (2023) - [i2]Yulong Zhang, Shuhao Chen, Weisen Jiang, Yu Zhang, Jiangang Lu, James T. Kwok:
Domain-Guided Conditional Diffusion Model for Unsupervised Domain Adaptation. CoRR abs/2309.14360 (2023) - [i1]Weisen Jiang, Baijiong Lin, Han Shi, Yu Zhang, Zhenguo Li, James T. Kwok:
Effective and Parameter-Efficient Reusing Fine-Tuned Models. CoRR abs/2310.01886 (2023) - 2022
- [c3]Weisen Jiang, James T. Kwok, Yu Zhang:
Subspace Learning for Effective Meta-Learning. ICML 2022: 10177-10194 - 2021
- [c2]Weisen Jiang, Yu Zhang, James T. Kwok:
SEEN: Few-Shot Classification with SElf-ENsemble. IJCNN 2021: 1-8 - [c1]Weisen Jiang, James T. Kwok, Yu Zhang:
Effective Meta-Regularization by Kernelized Proximal Regularization. NeurIPS 2021: 26212-26222
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