Hailin Hu

According to our database, Hailin Hu authored at least 26 papers between 2017 and 2025.

Collaborative distances:

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

2025

Pangu Embedded: An Efficient Dual-system LLM Reasoner with Metacognition.

Hanting Chen, Yasheng Wang, Kai Han, Dong Li, Lin Li, Zhenni Bi, Jinpeng Li, Haoyu Wang, Fei Mi, Mingjian Zhu, Bin Wang, Kaikai Song, Yifei Fu, Xu He, Yu Luo, Chong Zhu, Quan He, Xueyu Wu, Wei He, Hailin Hu, Yehui Tang, Dacheng Tao, Xinghao Chen, Yunhe Wang

CoRR, May, 2025

Transferable text data distillation by trajectory matching.

Rong Yao, Hailin Hu, Yifei Fu, Hanting Chen, Wenyi Fang, Fanyi Du, Kai Han, Yunhe Wang

CoRR, April, 2025

Saliency-driven Dynamic Token Pruning for Large Language Models.

Yao Tao, Yehui Tang, Yun Wang, Mingjian Zhu, Hailin Hu, Yunhe Wang

CoRR, April, 2025

GenVidBench: A Challenging Benchmark for Detecting AI-Generated Video.

Zhenliang Ni, Qiangyu Yan, Mouxiao Huang, Tianning Yuan, Yehui Tang, Hailin Hu, Xinghao Chen, Yunhe Wang

CoRR, January, 2025

Single Domain Generalization for Few-Shot Counting via Universal Representation Matching.

Xianing Chen, Si Huo, Borui Jiang, Hailin Hu, Xinghao Chen

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

GIM: A Million-scale Benchmark for Generative Image Manipulation Detection and Localization.

Yirui Chen, Xudong Huang, Quan Zhang, Wei Li, Mingjian Zhu, Qiangyu Yan, Simiao Li, Hanting Chen, Hailin Hu, Jie Yang, Wei Liu, Jie Hu

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

Omni-Dimensional Frequency Learner for General Time Series Analysis.

Xianing Chen, Hanting Chen, Hailin Hu

CoRR, 2024

A Survey on Transformer Compression.

Yehui Tang, Yunhe Wang, Jianyuan Guo, Zhijun Tu, Kai Han, Hailin Hu, Dacheng Tao

CoRR, 2024

2023

PanGu-π: Enhancing Language Model Architectures via Nonlinearity Compensation.

Yunhe Wang, Hanting Chen, Yehui Tang, Tianyu Guo, Kai Han, Ying Nie, Xutao Wang, Hailin Hu, Zheyuan Bai, Yun Wang, Fangcheng Liu, Zhicheng Liu, Jianyuan Guo, Sinan Zeng, Yinchen Zhang, Qinghua Xu, Qun Liu, Jun Yao, Chao Xu, Dacheng Tao

CoRR, 2023

GenDet: Towards Good Generalizations for AI-Generated Image Detection.

Mingjian Zhu, Hanting Chen, Mouxiao Huang, Wei Li, Hailin Hu, Jie Hu, Yunhe Wang

CoRR, 2023

Data-Free Distillation of Language Model by Text-to-Text Transfer.

Zheyuan Bai, Xinduo Liu, Hailin Hu, Tianyu Guo, Qinghua Zhang, Yunhe Wang

CoRR, 2023

GenImage: A Million-Scale Benchmark for Detecting AI-Generated Image.

Mingjian Zhu, Hanting Chen, Qiangyu Yan, Xudong Huang, Guanyu Lin, Wei Li, Zhijun Tu, Hailin Hu, Jie Hu, Yunhe Wang

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

Less is More: Focus Attention for Efficient DETR.

Dehua Zheng, Wenhui Dong, Hailin Hu, Xinghao Chen, Yunhe Wang

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

2022

DensE: An enhanced non-commutative representation for knowledge graph embedding with adaptive semantic hierarchy.

Haonan Lu, Hailin Hu, Xiaodong Lin

Neurocomputing, 2022

How Well Does Self-Supervised Pre-Training Perform with Streaming Data?

Dapeng Hu, Shipeng Yan, Qizhengqiu Lu, Lanqing Hong, Hailin Hu, Yifan Zhang, Zhenguo Li, Xinchao Wang, Jiashi Feng

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

How Well Self-Supervised Pre-Training Performs with Streaming Data?

Dapeng Hu, Qizhengqiu Lu, Lanqing Hong, Hailin Hu, Yifan Zhang, Zhenguo Li, Alfred Shen, Jiashi Feng

CoRR, 2021

Riboexp: an interpretable reinforcement learning framework for ribosome density modeling.

Hailin Hu, Xianggen Liu, An Xiao, Yangyang Li, Chengdong Zhang, Tao Jiang, Dan Zhao, Sen Song, Jianyang Zeng

Briefings Bioinform., 2021

2020

DensE: An Enhanced Non-Abelian Group Representation for Knowledge Graph Embedding.

Haonan Lu, Hailin Hu

CoRR, 2020

Secure multiparty computation for privacy-preserving drug discovery.

Rong Ma, Yi Li, Chenxing Li, Fangping Wan, Hailin Hu, Wei Xu, Jianyang Zeng

Bioinform., 2020

DATSING: Data Augmented Time Series Forecasting with Adversarial Domain Adaptation.

Hailin Hu, MingJian Tang, Chengcheng Bai

Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

2019

DeepCPI: A Deep Learning-based Framework for Large-scale <i>in silico</i> Drug Screening.

Fangping Wan, Yue Zhu, Hailin Hu, Antao Dai, Xiaoqing Cai, Ligong Chen, Haipeng Gong, Tian Xia, Dehua Yang, Ming-Wei Wang, Jianyang Zeng

Genom. Proteom. Bioinform., 2019

DeepShape: estimating isoform-level ribosome abundance and distribution with Ribo-seq data.

Hongfei Cui, Hailin Hu, Jianyang Zeng, Ting Chen

BMC Bioinform., 2019

DeepHINT: understanding HIV-1 integration via deep learning with attention.

Hailin Hu, An Xiao, Sai Zhang, Yangyang Li, Xuanling Shi, Tao Jiang, Linqi Zhang, Lei Zhang, Jianyang Zeng

Bioinform., 2019

ACME: pan-specific peptide-MHC class I binding prediction through attention-based deep neural networks.

Yan Hu, Ziqiang Wang, Hailin Hu, Fangping Wan, Lin Chen, Yuanpeng Xiong, Xiaoxia Wang, Dan Zhao, Weiren Huang, Jianyang Zeng

Bioinform., 2019

2017

TITER: predicting translation initiation sites by deep learning.

Sai Zhang, Hailin Hu, Tao Jiang, Lei Zhang, Jianyang Zeng

Bioinform., 2017

ROSE: A Deep Learning Based Framework for Predicting Ribosome Stalling.

Sai Zhang, Hailin Hu, Jingtian Zhou, Xuan He, Tao Jiang, Jianyang Zeng

Proceedings of the Research in Computational Molecular Biology, 2017