Xiaohan Ding

According to our database, Xiaohan Ding authored at least 44 papers between 2018 and 2024.

Collaborative distances:

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

2024

Manipulating Identical Filter Redundancy for Efficient Pruning on Deep and Complicated CNN.

Tianxiang Hao, Xiaohan Ding, Jungong Han, Yuchen Guo, Guiguang Ding

IEEE Trans. Neural Networks Learn. Syst., November, 2024

Linguistically Differentiating Acts and Recalls of Racial Microaggressions on Social Media.

Uma Sushmitha Gunturi, Anisha Kumar, Xiaohan Ding, Eugenia H. Rho

Proc. ACM Hum. Comput. Interact., 2024

Vision Search Assistant: Empower Vision-Language Models as Multimodal Search Engines.

Zhixin Zhang, Yiyuan Zhang, Xiaohan Ding, Xiangyu Yue

CoRR, 2024

Scaling Up Your Kernels: Large Kernel Design in ConvNets towards Universal Representations.

Yiyuan Zhang, Xiaohan Ding, Xiangyu Yue

CoRR, 2024

Exploring Large Language Models Through a Neurodivergent Lens: Use, Challenges, Community-Driven Workarounds, and Concerns.

Buse Çarik, Kaike Ping, Xiaohan Ding, Eugenia H. Rho

CoRR, 2024

Conversate: Supporting Reflective Learning in Interview Practice Through Interactive Simulation and Dialogic Feedback.

Taufiq Daryanto, Xiaohan Ding, Lance T. Wilhelm, Sophia Stil, Kirk McInnis Knutsen, Eugenia H. Rho

CoRR, 2024

CounterQuill: Investigating the Potential of Human-AI Collaboration in Online Counterspeech Writing.

Xiaohan Ding, Kaike Ping, Uma Sushmitha Gunturi, Buse Çarik, Sophia Stil, Lance T. Wilhelm, Taufiq Daryanto, James Hawdon, Sang Won Lee, Eugenia H. Rho

CoRR, 2024

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation.

Yuying Ge, Sijie Zhao, Jinguo Zhu, Yixiao Ge, Kun Yi, Lin Song, Chen Li, Xiaohan Ding, Ying Shan

CoRR, 2024

Behind the Counter: Exploring the Motivations and Barriers of Online Counterspeech Writing.

Kaike Ping, Anisha Kumar, Xiaohan Ding, Eugenia H. Rho

CoRR, 2024

Leveraging Prompt-Based Large Language Models: Predicting Pandemic Health Decisions and Outcomes Through Social Media Language.

Xiaohan Ding, Buse Çarik, Uma Sushmitha Gunturi, Valerie Reyna, Eugenia H. Rho

CoRR, 2024

InteractiveVideo: User-Centric Controllable Video Generation with Synergistic Multimodal Instructions.

Yiyuan Zhang, Yuhao Kang, Zhixin Zhang, Xiaohan Ding, Sanyuan Zhao, Xiangyu Yue

CoRR, 2024

Online Vectorized HD Map Construction Using Geometry.

Zhixin Zhang, Yiyuan Zhang, Xiaohan Ding, Fusheng Jin, Xiangyu Yue

Proceedings of the Computer Vision - ECCV 2024, 2024

Quantized Prompt for Efficient Generalization of Vision-Language Models.

Tianxiang Hao, Xiaohan Ding, Juexiao Feng, Yuhong Yang, Hui Chen, Guiguang Ding

Proceedings of the Computer Vision - ECCV 2024, 2024

Multimodal Pathway: Improve Transformers with Irrelevant Data from Other Modalities.

Yiyuan Zhang, Xiaohan Ding, Kaixiong Gong, Yixiao Ge, Ying Shan, Xiangyu Yue

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

Low-Rank Approximation for Sparse Attention in Multi-Modal LLMs.

Lin Song, Yukang Chen, Shuai Yang, Xiaohan Ding, Yixiao Ge, Ying-Cong Chen, Ying Shan

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

UniRepLKNet: A Universal Perception Large-Kernel ConvNet for Audio, Video, Point Cloud, Time-Series and Image Recognition.

Xiaohan Ding, Yiyuan Zhang, Yixiao Ge, Sijie Zhao, Lin Song, Xiangyu Yue, Ying Shan

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

Leveraging Prompt-Based Large Language Models: Predicting Pandemic Health Decisions and Outcomes Through Social Media Language.

Xiaohan Ding, Buse Çarik, Uma Sushmitha Gunturi, Valerie Reyna, Eugenia Ha Rim Rho

Proceedings of the CHI Conference on Human Factors in Computing Systems, 2024

2023

VL-GPT: A Generative Pre-trained Transformer for Vision and Language Understanding and Generation.

Jinguo Zhu, Xiaohan Ding, Yixiao Ge, Yuying Ge, Sijie Zhao, Hengshuang Zhao, Xiaohua Wang, Ying Shan

CoRR, 2023

Advancing Vision Transformers with Group-Mix Attention.

Chongjian Ge, Xiaohan Ding, Zhan Tong, Li Yuan, Jiangliu Wang, Yibing Song, Ping Luo

CoRR, 2023

RefConv: Re-parameterized Refocusing Convolution for Powerful ConvNets.

Zhicheng Cai, Xiaohan Ding, Qiu Shen, Xun Cao

CoRR, 2023

Towards Unified and Effective Domain Generalization.

Yiyuan Zhang, Kaixiong Gong, Xiaohan Ding, Kaipeng Zhang, Fangrui Lv, Kurt Keutzer, Xiangyu Yue

CoRR, 2023

Sticker820K: Empowering Interactive Retrieval with Stickers.

Sijie Zhao, Yixiao Ge, Zhongang Qi, Lin Song, Xiaohan Ding, Zehua Xie, Ying Shan

CoRR, 2023

What Makes for Good Visual Tokenizers for Large Language Models?

Guangzhi Wang, Yixiao Ge, Xiaohan Ding, Mohan S. Kankanhalli, Ying Shan

CoRR, 2023

ToxVis: Enabling Interpretability of Implicit vs. Explicit Toxicity Detection Models with Interactive Visualization.

Uma Sushmitha Gunturi, Xiaohan Ding, Eugenia H. Rho

CoRR, 2023

Same Words, Different Meanings: Semantic Polarization in Broadcast Media Language Forecasts Polarization on Social Media Discourse.

Xiaohan Ding, Mike Horning, Eugenia H. Rho

CoRR, 2023

Same Words, Different Meanings: Semantic Polarization in Broadcast Media Language Forecasts Polarity in Online Public Discourse.

Xiaohan Ding, Michael A. Horning, Eugenia H. Rho

Proceedings of the Seventeenth International AAAI Conference on Web and Social Media, 2023

Evolving Semantic Prototype Improves Generative Zero-Shot Learning.

Shiming Chen, Wenjin Hou, Ziming Hong, Xiaohan Ding, Yibing Song, Xinge You, Tongliang Liu, Kun Zhang

Proceedings of the International Conference on Machine Learning, 2023

Re-parameterizing Your Optimizers rather than Architectures.

Xiaohan Ding, Honghao Chen, Xiangyu Zhang, Kaiqi Huang, Jungong Han, Guiguang Ding

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Effects of pricing schemes and platform types on platform-based logistics services.

Xiaohan Ding, Nan Liu

Electron. Commer. Res. Appl., 2022

Scaling Up Your Kernels to 31x31: Revisiting Large Kernel Design in CNNs.

Xiaohan Ding, Xiangyu Zhang, Yizhuang Zhou, Jungong Han, Guiguang Ding, Jian Sun

CoRR, 2022

A Likelihood Ratio Based Domain Adaptation Method for E2E Models.

Chhavi Choudhury, Ankur Gandhe, Xiaohan Ding, Ivan Bulyko

Proceedings of the IEEE International Conference on Acoustics, 2022

RepMLPNet: Hierarchical Vision MLP with Re-parameterized Locality.

Xiaohan Ding, Honghao Chen, Xiangyu Zhang, Jungong Han, Guiguang Ding

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Scaling Up Your Kernels to 31×31: Revisiting Large Kernel Design in CNNs.

Xiaohan Ding, Xiangyu Zhang, Jungong Han, Guiguang Ding

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

RepMLP: Re-parameterizing Convolutions into Fully-connected Layers for Image Recognition.

Xiaohan Ding, Xiangyu Zhang, Jungong Han, Guiguang Ding

CoRR, 2021

ResRep: Lossless CNN Pruning via Decoupling Remembering and Forgetting.

Xiaohan Ding, Tianxiang Hao, Jianchao Tan, Ji Liu, Jungong Han, Yuchen Guo, Guiguang Ding

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

RepVGG: Making VGG-Style ConvNets Great Again.

Xiaohan Ding, Xiangyu Zhang, Ningning Ma, Jungong Han, Guiguang Ding, Jian Sun

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Diverse Branch Block: Building a Convolution as an Inception-Like Unit.

Xiaohan Ding, Xiangyu Zhang, Jungong Han, Guiguang Ding

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Lossless CNN Channel Pruning via Gradient Resetting and Convolutional Re-parameterization.

Xiaohan Ding, Tianxiang Hao, Ji Liu, Jungong Han, Yuchen Guo, Guiguang Ding

CoRR, 2020

2019

Global Sparse Momentum SGD for Pruning Very Deep Neural Networks.

Xiaohan Ding, Guiguang Ding, Xiangxin Zhou, Yuchen Guo, Jungong Han, Ji Liu

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Approximated Oracle Filter Pruning for Destructive CNN Width Optimization.

Xiaohan Ding, Guiguang Ding, Yuchen Guo, Jungong Han, Chenggang Yan

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

ACNet: Strengthening the Kernel Skeletons for Powerful CNN via Asymmetric Convolution Blocks.

Xiaohan Ding, Yuchen Guo, Guiguang Ding, Jungong Han

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Centripetal SGD for Pruning Very Deep Convolutional Networks With Complicated Structure.

Xiaohan Ding, Guiguang Ding, Yuchen Guo, Jungong Han

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Dual-View Ranking with Hardness Assessment for Zero-Shot Learning.

Yuchen Guo, Guiguang Ding, Jungong Han, Xiaohan Ding, Sicheng Zhao, Zheng Wang, Chenggang Yan, Qionghai Dai

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

2018

Auto-Balanced Filter Pruning for Efficient Convolutional Neural Networks.

Xiaohan Ding, Guiguang Ding, Jungong Han, Sheng Tang

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