Ying Wei

According to our database, Ying Wei authored at least 81 papers between 2014 and 2025.

Collaborative distances:

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

2025

Quantization Meets dLLMs: A Systematic Study of Post-training Quantization for Diffusion LLMs.

Haokun Lin, Haobo Xu, Yichen Wu, Ziyu Guo, Renrui Zhang, Zhichao Lu, Ying Wei, Qingfu Zhang, Zhenan Sun

CoRR, August, 2025

Come Together, But Not Right Now: A Progressive Strategy to Boost Low-Rank Adaptation.

Zhan Zhuang, Xiequn Wang, Wei Li, Yulong Zhang, Qiushi Huang, Shuhao Chen, Xuehao Wang, Yanbin Wei, Yuhe Nie, Kede Ma, Yu Zhang, Ying Wei

CoRR, June, 2025

What Makes a Good Reasoning Chain? Uncovering Structural Patterns in Long Chain-of-Thought Reasoning.

Gangwei Jiang, Yahui Liu, Zhaoyi Li, Qi Wang, Fuzheng Zhang, Linqi Song, Ying Wei, Defu Lian

CoRR, May, 2025

TokLIP: Marry Visual Tokens to CLIP for Multimodal Comprehension and Generation.

Haokun Lin, Teng Wang, Yixiao Ge, Yuying Ge, Zhichao Lu, Ying Wei, Qingfu Zhang, Zhenan Sun, Ying Shan

CoRR, May, 2025

Learning to Substitute Components for Compositional Generalization.

Zhaoyi Li, Gangwei Jiang, Chenwang Wu, Ying Wei, Defu Lian, Enhong Chen

CoRR, February, 2025

S-LoRA: Scalable Low-Rank Adaptation for Class Incremental Learning.

Yichen Wu, Hongming Piao, Long-Kai Huang, Renzhen Wang, Wanhua Li, Hanspeter Pfister, Deyu Meng, Kede Ma, Ying Wei

CoRR, January, 2025

SD-LoRA: Scalable Decoupled Low-Rank Adaptation for Class Incremental Learning.

Yichen Wu, Hongming Piao, Long-Kai Huang, Renzhen Wang, Wanhua Li, Hanspeter Pfister, Deyu Meng, Kede Ma, Ying Wei

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Unlocking the Power of Function Vectors for Characterizing and Mitigating Catastrophic Forgetting in Continual Instruction Tuning.

Gangwei Jiang, Caigao Jiang, Zhaoyi Li, Siqiao Xue, Jun Zhou, Linqi Song, Defu Lian, Ying Wei

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

CLDyB: Towards Dynamic Benchmarking for Continual Learning with Pre-trained Models.

Shengzhuang Chen, Yikai Liao, Xiaoxiao Sun, Kede Ma, Ying Wei

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Automatic Expert Discovery in LLM Upcycling via Sparse Interpolated Mixture-of-Experts.

Shengzhuang Chen, Ying Wei, Jonathan Richard Schwarz

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

Interpretable Catastrophic Forgetting of Large Language Model Fine-tuning via Instruction Vector.

Gangwei Jiang, Caigao Jiang, Zhaoyi Li, Siqiao Xue, Jun Zhou, Linqi Song, Defu Lian, Ying Wei

CoRR, 2024

Rotation and Permutation for Advanced Outlier Management and Efficient Quantization of LLMs.

Haokun Lin, Haobo Xu, Yichen Wu, Jingzhi Cui, Yingtao Zhang, Linzhan Mou, Linqi Song, Zhenan Sun, Ying Wei

CoRR, 2024

From Words to Molecules: A Survey of Large Language Models in Chemistry.

Chang Liao, Yemin Yu, Yu Mei, Ying Wei

CoRR, 2024

Global-local aware Heterogeneous Graph Contrastive Learning for multifaceted association prediction in miRNA-gene-disease networks.

Yuxuan Si, Zihan Huang, Zhengqing Fang, Zhouhang Yuan, Zhengxing Huang, Yingming Li, Ying Wei, Fei Wu, Yu-Feng Yao

Briefings Bioinform., 2024

Learning Where to Edit Vision Transformers.

Yunqiao Yang, Long-Kai Huang, Shengzhuang Chen, Kede Ma, Ying Wei

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

DuQuant: Distributing Outliers via Dual Transformation Makes Stronger Quantized LLMs.

Haokun Lin, Haobo Xu, Yichen Wu, Jingzhi Cui, Yingtao Zhang, Linzhan Mou, Linqi Song, Zhenan Sun, Ying Wei

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

A Multi-objective Perspective Towards Improving Meta-Generalization.

Weiduo Liao, Ying Wei, Qirui Sun, Qingfu Zhang, Hisao Ishibuchi

Proceedings of the International Joint Conference on Neural Networks, 2024

Mitigating Catastrophic Forgetting in Online Continual Learning by Modeling Previous Task Interrelations via Pareto Optimization.

Yichen Wu, Hong Wang, Peilin Zhao, Yefeng Zheng, Ying Wei, Long-Kai Huang

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

Federated Continual Learning via Prompt-based Dual Knowledge Transfer.

Hongming Piao, Yichen Wu, Dapeng Wu, Ying Wei

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

Unleashing the Power of Meta-tuning for Few-shot Generalization Through Sparse Interpolated Experts.

Shengzhuang Chen, Jihoon Tack, Yunqiao Yang, Yee Whye Teh, Jonathan Richard Schwarz, Ying Wei

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

Active Retrosynthetic Planning Aware of Route Quality.

Luotian Yuan, Yemin Yu, Ying Wei, Yongwei Wang, Zhihua Wang, Fei Wu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Meta Continual Learning Revisited: Implicitly Enhancing Online Hessian Approximation via Variance Reduction.

Yichen Wu, Long-Kai Huang, Renzhen Wang, Deyu Meng, Ying Wei

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Mitigating the Language Mismatch and Repetition Issues in LLM-based Machine Translation via Model Editing.

Weichuan Wang, Zhaoyi Li, Defu Lian, Chen Ma, Linqi Song, Ying Wei

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

MoPE-CLIP: Structured Pruning for Efficient Vision-Language Models with Module-Wise Pruning Error Metric.

Haokun Lin, Haoli Bai, Zhili Liu, Lu Hou, Muyi Sun, Linqi Song, Ying Wei, Zhenan Sun

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Benchmarking and Improving Compositional Generalization of Multi-aspect Controllable Text Generation.

Tianqi Zhong, Zhaoyi Li, Quan Wang, Linqi Song, Ying Wei, Defu Lian, Zhendong Mao

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

Understanding and Patching Compositional Reasoning in LLMs.

Zhaoyi Li, Gangwei Jiang, Hong Xie, Linqi Song, Defu Lian, Ying Wei

Proceedings of the Findings of the Association for Computational Linguistics, 2024

RetroOOD: Understanding Out-of-Distribution Generalization in Retrosynthesis Prediction.

Yemin Yu, Luotian Yuan, Ying Wei, Hanyu Gao, Fei Wu, Zhihua Wang, Xinhai Ye

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

DeepAlgPro: an interpretable deep neural network model for predicting allergenic proteins.

Chun He, Xinhai Ye, Yi Yang, Liya Hu, Yuxuan Si, Xianxin Zhao, Longfei Chen, Qi Fang, Ying Wei, Fei Wu, Gongyin Ye

Briefings Bioinform., July, 2023

On the Opportunities of Green Computing: A Survey.

You Zhou, Xiujing Lin, Xiang Zhang, Maolin Wang, Gangwei Jiang, Huakang Lu, Yupeng Wu, Kai Zhang, Zhe Yang, Kehang Wang, Yongduo Sui, Fengwei Jia, Zuoli Tang, Yao Zhao, Hongxuan Zhang, Tiannuo Yang, Weibo Chen, Yunong Mao, Yi Li, De Bao, Yu Li, Hongrui Liao, Ting Liu, Jingwen Liu, Jinchi Guo, Xiangyu Zhao, Ying Wei, Hong Qian, Qi Liu, Xiang Wang, Wai Kin Chan, Chenliang Li, Yusen Li, Shiyu Yang, Jining Yan, Chao Mou, Shuai Han, Wuxia Jin, Guannan Zhang, Xiaodong Zeng

CoRR, 2023

Towards Anytime Fine-tuning: Continually Pre-trained Language Models with Hypernetwork Prompt.

Gangwei Jiang, Caigao Jiang, Siqiao Xue, James Y. Zhang, Jun Zhou, Defu Lian, Ying Wei

CoRR, 2023

Does Continual Learning Meet Compositionality? New Benchmarks and An Evaluation Framework.

Weiduo Liao, Ying Wei, Mingchen Jiang, Qingfu Zhang, Hisao Ishibuchi

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Secure Out-of-Distribution Task Generalization with Energy-Based Models.

Shengzhuang Chen, Long-Kai Huang, Jonathan Richard Schwarz, Yilun Du, Ying Wei

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Concept-wise Fine-tuning Matters in Preventing Negative Transfer.

Yunqiao Yang, Long-Kai Huang, Ying Wei

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Towards Anytime Fine-tuning: Continually Pre-trained Language Models with Hypernetwork Prompts.

Gangwei Jiang, Caigao Jiang, Siqiao Xue, James Zhang, Jun Zhou, Defu Lian, Ying Wei

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Blind Image Quality Assessment via Vision-Language Correspondence: A Multitask Learning Perspective.

Weixia Zhang, Guangtao Zhai, Ying Wei, Xiaokang Yang, Kede Ma

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

A Joint Attention Module and Deformable Transformer Network for Hyperparathyroidism Detection.

Qing Guo, Jie Yang, Yufeng Xiao, Huaqing Wang, Mingan Yu, Ying Wei, Zhenlong Zhao

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

Learning to Substitute Spans towards Improving Compositional Generalization.

Zhaoyi Li, Ying Wei, Defu Lian

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Learning Chemical Rules of Retrosynthesis with Pre-training.

Yinjie Jiang, Ying Wei, Fei Wu, Zhengxing Huang, Kun Kuang, Zhihua Wang

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Learning to generate imaginary tasks for improving generalization in meta-learning.

Yichen Wu, Long-Kai Huang, Ying Wei

CoRR, 2022

A Benchmark and Transformer-based Approach for Automated Hyperparathyroidism Detection.

Qing Guo, Yufeng Xiao, Huaqing Wang, Mingan Yu, Ying Wei, Zhenlong Zhao

Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2022

GRASP: Navigating Retrosynthetic Planning with Goal-driven Policy.

Yemin Yu, Ying Wei, Kun Kuang, Zhengxing Huang, Huaxiu Yao, Fei Wu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Adversarial Task Up-sampling for Meta-learning.

Yichen Wu, Long-Kai Huang, Ying Wei

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Improving Task-Specific Generalization in Few-Shot Learning via Adaptive Vicinal Risk Minimization.

Long-Kai Huang, Ying Wei

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Self-Supervised Text Erasing with Controllable Image Synthesis.

Gangwei Jiang, Shiyao Wang, Tiezheng Ge, Yuning Jiang, Ying Wei, Defu Lian

Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

The Role of Deconfounding in Meta-learning.

Yinjie Jiang, Zhengyu Chen, Kun Kuang, Luotian Yuan, Xinhai Ye, Zhihua Wang, Fei Wu, Ying Wei

Proceedings of the International Conference on Machine Learning, 2022

Frustratingly Easy Transferability Estimation.

Long-Kai Huang, Junzhou Huang, Yu Rong, Qiang Yang, Ying Wei

Proceedings of the International Conference on Machine Learning, 2022

Disentangling Task Relations for Few-shot Text Classification via Self-Supervised Hierarchical Task Clustering.

Juan Zha, Zheng Li, Ying Wei, Yu Zhang

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

2021

Meta-learning with an Adaptive Task Scheduler.

Huaxiu Yao, Yu Wang, Ying Wei, Peilin Zhao, Mehrdad Mahdavi, Defu Lian, Chelsea Finn

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

Functionally Regionalized Knowledge Transfer for Low-resource Drug Discovery.

Huaxiu Yao, Ying Wei, Long-Kai Huang, Ding Xue, Junzhou Huang, Zhenhui Li

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

Improving Generalization in Meta-learning via Task Augmentation.

Huaxiu Yao, Long-Kai Huang, Linjun Zhang, Ying Wei, Li Tian, James Zou, Junzhou Huang, Zhenhui Li

Proceedings of the 38th International Conference on Machine Learning, 2021

Meta-learning Hyperparameter Performance Prediction with Neural Processes.

Ying Wei, Peilin Zhao, Junzhou Huang

Proceedings of the 38th International Conference on Machine Learning, 2021

MetaTS: Meta Teacher-Student Network for Multilingual Sequence Labeling with Minimal Supervision.

Zheng Li, Danqing Zhang, Tianyu Cao, Ying Wei, Yiwei Song, Bing Yin

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2020

Collaborative Unsupervised Domain Adaptation for Medical Image Diagnosis.

Yifan Zhang, Ying Wei, Qingyao Wu, Peilin Zhao, Shuaicheng Niu, Junzhou Huang, Mingkui Tan

IEEE Trans. Image Process., 2020

Don't Overlook the Support Set: Towards Improving Generalization in Meta-learning.

Huaxiu Yao, Longkai Huang, Ying Wei, Li Tian, Junzhou Huang, Zhenhui Li

CoRR, 2020

GROVER: Self-supervised Message Passing Transformer on Large-scale Molecular Data.

Yu Rong, Yatao Bian, Tingyang Xu, Weiyang Xie, Ying Wei, Wenbing Huang, Junzhou Huang

CoRR, 2020

COVID-DA: Deep Domain Adaptation from Typical Pneumonia to COVID-19.

Yifan Zhang, Shuaicheng Niu, Zhen Qiu, Ying Wei, Peilin Zhao, Jianhua Yao, Junzhou Huang, Qingyao Wu, Mingkui Tan

CoRR, 2020

Fisher Deep Domain Adaptation.

Yinghua Zhang, Yu Zhang, Ying Wei, Kun Bai, Yangqiu Song, Qiang Yang

Proceedings of the 2020 SIAM International Conference on Data Mining, 2020

Adversarial Sparse Transformer for Time Series Forecasting.

Sifan Wu, Xi Xiao, Qianggang Ding, Peilin Zhao, Ying Wei, Junzhou Huang

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Self-Supervised Graph Transformer on Large-Scale Molecular Data.

Yu Rong, Yatao Bian, Tingyang Xu, Weiyang Xie, Ying Wei, Wenbing Huang, Junzhou Huang

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

TranSlider: Transfer Ensemble Learning from Exploitation to Exploration.

Kuo Zhong, Ying Wei, Chun Yuan, Haoli Bai, Junzhou Huang

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Learn to Cross-lingual Transfer with Meta Graph Learning Across Heterogeneous Languages.

Zheng Li, Mukul Kumar, William Headden, Bing Yin, Ying Wei, Yu Zhang, Qiang Yang

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Recognition of Hyperparathyroidism based on Transfer Learning.

Jiabo Chen, Qing Guo, Zixun Jiang, Huaqing Wang, Mingan Yu, Ying Wei

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020

Graph Few-Shot Learning via Knowledge Transfer.

Huaxiu Yao, Chuxu Zhang, Ying Wei, Meng Jiang, Suhang Wang, Junzhou Huang, Nitesh V. Chawla, Zhenhui Li

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Transferable Neural Processes for Hyperparameter Optimization.

Ying Wei, Peilin Zhao, Huaxiu Yao, Junzhou Huang

CoRR, 2019

Learning from Multiple Cities: A Meta-Learning Approach for Spatial-Temporal Prediction.

Huaxiu Yao, Yiding Liu, Ying Wei, Xianfeng Tang, Zhenhui Li

Proceedings of the World Wide Web Conference, 2019

From Whole Slide Imaging to Microscopy: Deep Microscopy Adaptation Network for Histopathology Cancer Image Classification.

Yifan Zhang, Hanbo Chen, Ying Wei, Peilin Zhao, Jiezhang Cao, Xinjuan Fan, Xiaoying Lou, Hailing Liu, Jinlong Hou, Xiao Han, Jianhua Yao, Qingyao Wu, Mingkui Tan, Junzhou Huang

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Hierarchically Structured Meta-learning.

Huaxiu Yao, Ying Wei, Junzhou Huang, Zhenhui Li

Proceedings of the 36th International Conference on Machine Learning, 2019

Transferable End-to-End Aspect-based Sentiment Analysis with Selective Adversarial Learning.

Zheng Li, Xin Li, Ying Wei, Lidong Bing, Yu Zhang, Qiang Yang

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Exploiting Coarse-to-Fine Task Transfer for Aspect-Level Sentiment Classification.

Zheng Li, Ying Wei, Yu Zhang, Xiang Zhang, Xin Li

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Exploiting Coarse-to-Fine Task Transfer for Aspect-level Sentiment Classification.

Zheng Li, Ying Wei, Yu Zhang, Xiang Zhang, Xin Li, Qiang Yang

CoRR, 2018

Learning to Multitask.

Yu Zhang, Ying Wei, Qiang Yang

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Transfer Learning via Learning to Transfer.

Ying Wei, Yu Zhang, Junzhou Huang, Qiang Yang

Proceedings of the 35th International Conference on Machine Learning, 2018

Transferable Contextual Bandit for Cross-Domain Recommendation.

Bo Liu, Ying Wei, Yu Zhang, Zhixian Yan, Qiang Yang

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Hierarchical Attention Transfer Network for Cross-Domain Sentiment Classification.

Zheng Li, Ying Wei, Yu Zhang, Qiang Yang

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Learning to Transfer.

Ying Wei, Yu Zhang, Qiang Yang

CoRR, 2017

Deep Neural Networks for High Dimension, Low Sample Size Data.

Bo Liu, Ying Wei, Yu Zhang, Qiang Yang

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

End-to-End Adversarial Memory Network for Cross-domain Sentiment Classification.

Zheng Li, Yu Zhang, Ying Wei, Yuxiang Wu, Qiang Yang

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

2016

Heterogeneous Translated Hashing: A Scalable Solution Towards Multi-Modal Similarity Search.

Ying Wei, Yangqiu Song, Yi Zhen, Bo Liu, Qiang Yang

ACM Trans. Knowl. Discov. Data, 2016

Transfer Knowledge between Cities.

Ying Wei, Yu Zheng, Qiang Yang

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Instilling Social to Physical: Co-Regularized Heterogeneous Transfer Learning.

Ying Wei, Yin Zhu, Cane Wing-ki Leung, Yangqiu Song, Qiang Yang

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2014

Scalable heterogeneous translated hashing.

Ying Wei, Yangqiu Song, Yi Zhen, Bo Liu, Qiang Yang

Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014