Haotong Qin

According to our database, Haotong Qin authored at least 81 papers between 2020 and 2025.

Collaborative distances:

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

2025

S²Q-VDiT: Accurate Quantized Video Diffusion Transformer with Salient Data and Sparse Token Distillation.

Weilun Feng, Haotong Qin, Chuanguang Yang, Xiangqi Li, Han Yang, Yuqi Li, Zhulin An, Libo Huang, Michele Magno, Yongjun Xu

CoRR, August, 2025

First-Order Error Matters: Accurate Compensation for Quantized Large Language Models.

Xingyu Zheng, Haotong Qin, Yuye Li, Jiakai Wang, Jinyang Guo, Michele Magno, Xianglong Liu

CoRR, July, 2025

BiVM: Accurate Binarized Neural Network for Efficient Video Matting.

Haotong Qin, Xianglong Liu, Xudong Ma, Lei Ke, Yulun Zhang, Jie Luo, Michele Magno

CoRR, July, 2025

MPQ-DMv2: Flexible Residual Mixed Precision Quantization for Low-Bit Diffusion Models with Temporal Distillation.

Weilun Feng, Chuanguang Yang, Haotong Qin, Yuqi Li, Xiangqi Li, Zhulin An, Libo Huang, Boyu Diao, Fuzhen Zhuang, Michele Magno, Yongjun Xu, Yingli Tian, Tingwen Huang

CoRR, July, 2025

Pay Less Attention to Deceptive Artifacts: Robust Detection of Compressed Deepfakes on Online Social Networks.

Manyi Li, Renshuai Tao, Yufan Liu, Chuangchuang Tan, Haotong Qin, Bing Li, Yunchao Wei, Yao Zhao

CoRR, June, 2025

PicoSAM2: Low-Latency Segmentation In-Sensor for Edge Vision Applications.

Pietro Bonazzi, Nicola Farronato, Stefan Zihlmann, Haotong Qin, Michele Magno

CoRR, June, 2025

Pushing the Limits of Safety: A Technical Report on the ATLAS Challenge 2025.

Zonghao Ying, Siyang Wu, Run Hao, Peng Ying, Shixuan Sun, Pengyu Chen, Junze Chen, Hao Du, Kaiwen Shen, Shangkun Wu, Jiwei Wei, Shiyuan He, Yang Yang, Xiaohai Xu, Ke Ma, Qianqian Xu, Qingming Huang, Shi Lin, Xun Wang, Changting Lin, Meng Han, Yilei Jiang, Siqi Lai, Yaozhi Zheng, Yifei Song, Xiangyu Yue, Zonglei Jing, Tianyuan Zhang, Zhilei Zhu, Aishan Liu, Jiakai Wang, Siyuan Liang, Xianglong Kong, Hainan Li, Junjie Mu, Haotong Qin, Yue Yu, Lei Chen, Felix Juefei-Xu, Qing Guo, Xinyun Chen, Yew Soon Ong, Xianglong Liu, Dawn Song, Alan L. Yuille, Philip Torr, Dacheng Tao

CoRR, June, 2025

Post-Training Quantization for Video Matting.

Tianrui Zhu, Houyuan Chen, Ruihao Gong, Michele Magno, Haotong Qin, Kai Zhang

CoRR, June, 2025

Q-SAM2: Accurate Quantization for Segment Anything Model 2.

Nicola Farronato, Florian Scheidegger, Mattia Rigotti, Cristiano Malossi, Michele Magno, Haotong Qin

CoRR, June, 2025

Event-Priori-Based Vision-Language Model for Efficient Visual Understanding.

Haotong Qin, Cheng Hu, Michele Magno

CoRR, June, 2025

QuantFace: Low-Bit Post-Training Quantization for One-Step Diffusion Face Restoration.

Jiatong Li, Libo Zhu, Haotong Qin, Jingkai Wang, Linghe Kong, Guihai Chen, Yulun Zhang, Xiaokang Yang

CoRR, June, 2025

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers.

Weilun Feng, Chuanguang Yang, Haotong Qin, Xiangqi Li, Yu Wang, Zhulin An, Libo Huang, Boyu Diao, Zixiang Zhao, Yongjun Xu, Michele Magno

CoRR, May, 2025

QVGen: Pushing the Limit of Quantized Video Generative Models.

Yushi Huang, Ruihao Gong, Jing Liu, Yifu Ding, Chengtao Lv, Haotong Qin, Jun Zhang

CoRR, May, 2025

Low-bit Model Quantization for Deep Neural Networks: A Survey.

Kai Liu, Qian Zheng, Kaiwen Tao, Zhiteng Li, Haotong Qin, Wenbo Li, Yong Guo, Xianglong Liu, Linghe Kong, Guihai Chen, Yulun Zhang, Xiaokang Yang

CoRR, May, 2025

RGB-Event Fusion with Self-Attention for Collision Prediction.

Pietro Bonazzi, Christian Vogt, Michael Jost, Haotong Qin, Lyes Khacef, Federico Paredes-Vallés, Michele Magno

CoRR, May, 2025

An Empirical Study of Qwen3 Quantization.

Xingyu Zheng, Yuye Li, Haoran Chu, Yue Feng, Xudong Ma, Jie Luo, Jinyang Guo, Haotong Qin, Michele Magno, Xianglong Liu

CoRR, May, 2025

Enhancing Autonomous Driving Systems with On-Board Deployed Large Language Models.

Nicolas Baumann, Cheng Hu, Paviththiren Sivasothilingam, Haotong Qin, Lei Xie, Michele Magno, Luca Benini

CoRR, April, 2025

Q-MambaIR: Accurate Quantized Mamba for Efficient Image Restoration.

Yujie Chen, Haotong Qin, Zhang Zhang, Michelo Magno, Luca Benini, Yawei Li

CoRR, March, 2025

TR-DQ: Time-Rotation Diffusion Quantization.

Yihua Shao, Deyang Lin, Fanhu Zeng, Minxi Yan, Muyang Zhang, Siyu Chen, Yuxuan Fan, Ziyang Yan, Haozhe Wang, Jingcai Guo, Yan Wang, Haotong Qin, Hao Tang

CoRR, March, 2025

FSDP: Fast and Safe Data-Driven Overtaking Trajectory Planning for Head-to-Head Autonomous Racing Competitions.

Cheng Hu, Jihao Huang, Wule Mao, Yonghao Fu, Xuemin Chi, Haotong Qin, Nicolas Baumann, Zhitao Liu, Michele Magno, Lei Xie

CoRR, March, 2025

QArtSR: Quantization via Reverse-Module and Timestep-Retraining in One-Step Diffusion based Image Super-Resolution.

Libo Zhu, Haotong Qin, Kaicheng Yang, Wenbo Li, Yong Guo, Yulun Zhang, Susanto Rahardja, Xiaokang Yang

CoRR, March, 2025

Q&C: When Quantization Meets Cache in Efficient Image Generation.

Xin Ding, Xin Li, Haotong Qin, Zhibo Chen

CoRR, March, 2025

SAGNet: Decoupling Semantic-Agnostic Artifacts From Limited Training Data for Robust Generalization in Deepfake Detection.

Renshuai Tao, Chuangchuang Tan, Huan Liu, Jiakai Wang, Haotong Qin, Yakun Chang, Wei Wang, Rongrong Ni, Yao Zhao

IEEE Trans. Inf. Forensics Secur., 2025

Dual Intention Escape: Penetrating and Toxic Jailbreak Attack against Large Language Models.

Yanni Xue, Jiakai Wang, Zixin Yin, Yuqing Ma, Haotong Qin, Renshuai Tao, Xianglong Liu

Proceedings of the ACM on Web Conference 2025, 2025

BinaryDM: Accurate Weight Binarization for Efficient Diffusion Models.

Xingyu Zheng, Xianglong Liu, Haotong Qin, Xudong Ma, Mingyuan Zhang, Haojie Hao, Jiakai Wang, Zixiang Zhao, Jinyang Guo, Michele Magno

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

ARB-LLM: Alternating Refined Binarizations for Large Language Models.

Zhiteng Li, Xianglong Yan, Tianao Zhang, Haotong Qin, Dong Xie, Jiang Tian, Zhongchao Shi, Linghe Kong, Yulun Zhang, Xiaokang Yang

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution.

Libo Zhu, Jianze Li, Haotong Qin, Wenbo Li, Yulun Zhang, Yong Guo, Xiaokang Yang

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

Harnessing Global-Local Collaborative Adversarial Perturbation for Anti-Customization.

Long Xu, Jiakai Wang, Haojie Hao, Haotong Qin, Jiejie Zhao, Xianglong Liu

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

ODDN: Addressing Unpaired Data Challenges in Open-World Deepfake Detection on Online Social Networks.

Renshuai Tao, Manyi Le, Chuangchuang Tan, Huan Liu, Haotong Qin, Yao Zhao

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

MPQ-DM: Mixed Precision Quantization for Extremely Low Bit Diffusion Models.

Weilun Feng, Haotong Qin, Chuanguang Yang, Zhulin An, Libo Huang, Boyu Diao, Fei Wang, Renshuai Tao, Yongjun Xu, Michele Magno

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

2024

Generate Transferable Adversarial Physical Camouflages via Triplet Attention Suppression.

Jiakai Wang, Xianglong Liu, Zixin Yin, Yuxuan Wang, Jun Guo, Haotong Qin, Qingtao Wu, Aishan Liu

Int. J. Comput. Vis., November, 2024

BiFSMNv2: Pushing Binary Neural Networks for Keyword Spotting to Real-Network Performance.

Haotong Qin, Xudong Ma, Yifu Ding, Xiaoyang Li, Yang Zhang, Zejun Ma, Jiakai Wang, Jie Luo, Xianglong Liu

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

Towards Defending Multiple ℓ _p-Norm Bounded Adversarial Perturbations via Gated Batch Normalization.

Aishan Liu, Shiyu Tang, Xinyun Chen, Lei Huang, Haotong Qin, Xianglong Liu, Dacheng Tao

Int. J. Comput. Vis., June, 2024

An empirical study of LLaMA3 quantization: from LLMs to MLLMs.

Wei Huang, Xingyu Zheng, Xudong Ma, Haotong Qin, Chengtao Lv, Hong Chen, Jie Luo, Xiaojuan Qi, Xianglong Liu, Michele Magno

Vis. Intell., 2024

DynamicPAE: Generating Scene-Aware Physical Adversarial Examples in Real-Time.

Jin Hu, Xianglong Liu, Jiakai Wang, Junkai Zhang, Xianqi Yang, Haotong Qin, Yuqing Ma, Ke Xu

CoRR, 2024

BiDense: Binarization for Dense Prediction.

Rui Yin, Haotong Qin, Yulun Zhang, Wenbo Li, Yong Guo, Jianjun Zhu, Cheng Wang, Biao Jia

CoRR, 2024

GWQ: Gradient-Aware Weight Quantization for Large Language Models.

Yihua Shao, Siyu Liang, Xiaolin Lin, Zijian Ling, Zixian Zhu, Minxi Yan, Haiyang Liu, Siyu Chen, Ziyang Yan, Yilan Meng, Chenyu Zhang, Haotong Qin, Michele Magno, Yang Yang, Zhen Lei, Yan Wang, Jingcai Guo, Ling Shao, Hao Tang

CoRR, 2024

A Survey of Low-bit Large Language Models: Basics, Systems, and Algorithms.

Ruihao Gong, Yifu Ding, Zining Wang, Chengtao Lv, Xingyu Zheng, Jinyang Du, Haotong Qin, Jinyang Guo, Michele Magno, Xianglong Liu

CoRR, 2024

SliM-LLM: Salience-Driven Mixed-Precision Quantization for Large Language Models.

Wei Huang, Haotong Qin, Yangdong Liu, Yawei Li, Xianglong Liu, Luca Benini, Michele Magno, Xiaojuan Qi

CoRR, 2024

How Good Are Low-bit Quantized LLaMA3 Models? An Empirical Study.

Wei Huang, Xudong Ma, Haotong Qin, Xingyu Zheng, Chengtao Lv, Hong Chen, Jie Luo, Xiaojuan Qi, Xianglong Liu, Michele Magno

CoRR, 2024

BinaryDM: Towards Accurate Binarization of Diffusion Model.

Xingyu Zheng, Haotong Qin, Xudong Ma, Mingyuan Zhang, Haojie Hao, Jiakai Wang, Zixiang Zhao, Jinyang Guo, Xianglong Liu

CoRR, 2024

SeeMore: a spatiotemporal predictive model with bidirectional distillation and level-specific meta-adaptation.

Yuqing Ma, Wei Liu, Yajun Gao, Yang Yuan, Shihao Bai, Haotong Qin, Xianglong Liu

Sci. China Inf. Sci., 2024

Transferable Multimodal Attack on Vision-Language Pre-training Models.

Haodi Wang, Kai Dong, Zhilei Zhu, Haotong Qin, Aishan Liu, Xiaolin Fang, Jiakai Wang, Xianglong Liu

Proceedings of the IEEE Symposium on Security and Privacy, 2024

BiDM: Pushing the Limit of Quantization for Diffusion Models.

Xingyu Zheng, Xianglong Liu, Yichen Bian, Xudong Ma, Yulun Zhang, Jiakai Wang, Jinyang Guo, Haotong Qin

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

LLMCBench: Benchmarking Large Language Model Compression for Efficient Deployment.

Ge Yang, Changyi He, Jinyang Guo, Jianyu Wu, Yifu Ding, Aishan Liu, Haotong Qin, Pengliang Ji, Xianglong Liu

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

2DQuant: Low-bit Post-Training Quantization for Image Super-Resolution.

Kai Liu, Haotong Qin, Yong Guo, Xin Yuan, Linghe Kong, Guihai Chen, Yulun Zhang

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

Binarized Diffusion Model for Image Super-Resolution.

Zheng Chen, Haotong Qin, Yong Guo, Xiongfei Su, Xin Yuan, Linghe Kong, Yulun Zhang

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

Image Fusion via Vision-Language Model.

Zixiang Zhao, Lilun Deng, Haowen Bai, Yukun Cui, Zhipeng Zhang, Yulun Zhang, Haotong Qin, Dongdong Chen, Jiangshe Zhang, Peng Wang, Luc Van Gool

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

Flexible Residual Binarization for Image Super-Resolution.

Yulun Zhang, Haotong Qin, Zixiang Zhao, Xianglong Liu, Martin Danelljan, Fisher Yu

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

Accurate LoRA-Finetuning Quantization of LLMs via Information Retention.

Haotong Qin, Xudong Ma, Xingyu Zheng, Xiaoyang Li, Yang Zhang, Shouda Liu, Jie Luo, Xianglong Liu, Michele Magno

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

BiLLM: Pushing the Limit of Post-Training Quantization for LLMs.

Wei Huang, Yangdong Liu, Haotong Qin, Ying Li, Shiming Zhang, Xianglong Liu, Michele Magno, Xiaojuan Qi

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

Compressing Large Language Models by Joint Sparsification and Quantization.

Jinyang Guo, Jianyu Wu, Zining Wang, Jiaheng Liu, Ge Yang, Yifu Ding, Ruihao Gong, Haotong Qin, Xianglong Liu

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

DB-LLM: Accurate Dual-Binarization for Efficient LLMs.

Hong Chen, Chengtao Lv, Liang Ding, Haotong Qin, Xiabin Zhou, Yifu Ding, Xuebo Liu, Min Zhang, Jinyang Guo, Xianglong Liu, Dacheng Tao

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

2023

Diverse Sample Generation: Pushing the Limit of Generative Data-Free Quantization.

Haotong Qin, Yifu Ding, Xiangguo Zhang, Jiakai Wang, Xianglong Liu, Jiwen Lu

IEEE Trans. Pattern Anal. Mach. Intell., October, 2023

How Good is Google Bard's Visual Understanding? An Empirical Study on Open Challenges.

Haotong Qin, Ge-Peng Ji, Salman Khan, Deng-Ping Fan, Fahad Shahbaz Khan, Luc Van Gool

Mach. Intell. Res., October, 2023

RobustMQ: benchmarking robustness of quantized models.

Yisong Xiao, Aishan Liu, Tianyuan Zhang, Haotong Qin, Jinyang Guo, Xianglong Liu

Vis. Intell., 2023

Distribution-Sensitive Information Retention for Accurate Binary Neural Network.

Haotong Qin, Xiangguo Zhang, Ruihao Gong, Yifu Ding, Yi Xu, Xianglong Liu

Int. J. Comput. Vis., 2023

RdimKD: Generic Distillation Paradigm by Dimensionality Reduction.

Yi Guo, Yiqian He, Xiaoyang Li, Haotong Qin, Van Tung Pham, Yang Zhang, Shouda Liu

CoRR, 2023

Binarized 3D Whole-body Human Mesh Recovery.

Zhiteng Li, Yulun Zhang, Jing Lin, Haotong Qin, Jinjin Gu, Xin Yuan, Linghe Kong, Xiaokang Yang

CoRR, 2023

OHQ: On-chip Hardware-aware Quantization.

Wei Huang, Haotong Qin, Yangdong Liu, Jingzhuo Liang, Yifu Ding, Ying Li, Xianglong Liu

CoRR, 2023

Benchmarking the Robustness of Quantized Models.

Yisong Xiao, Tianyuan Zhang, Shunchang Liu, Haotong Qin

CoRR, 2023

QuantSR: Accurate Low-bit Quantization for Efficient Image Super-Resolution.

Haotong Qin, Yulun Zhang, Yifu Ding, Yifan Liu, Xianglong Liu, Martin Danelljan, Fisher Yu

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

BiMatting: Efficient Video Matting via Binarization.

Haotong Qin, Lei Ke, Xudong Ma, Martin Danelljan, Yu-Wing Tai, Chi-Keung Tang, Xianglong Liu, Fisher Yu

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

BiBench: Benchmarking and Analyzing Network Binarization.

Haotong Qin, Mingyuan Zhang, Yifu Ding, Aoyu Li, Zhongang Cai, Ziwei Liu, Fisher Yu, Xianglong Liu

Proceedings of the International Conference on Machine Learning, 2023

2022

Towards Accurate Post-Training Quantization for Vision Transformer.

Yifu Ding, Haotong Qin, Qinghua Yan, Zhenhua Chai, Junjie Liu, Xiaolin Wei, Xianglong Liu

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

BiFSMN: Binary Neural Network for Keyword Spotting.

Haotong Qin, Xudong Ma, Yifu Ding, Xiaoyang Li, Yang Zhang, Yao Tian, Zejun Ma, Jie Luo, Xianglong Liu

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

BiBERT: Accurate Fully Binarized BERT.

Haotong Qin, Yifu Ding, Mingyuan Zhang, Qinghua Yan, Aishan Liu, Qingqing Dang, Ziwei Liu, Xianglong Liu

Proceedings of the Tenth International Conference on Learning Representations, 2022

Defensive Patches for Robust Recognition in the Physical World.

Jiakai Wang, Zixin Yin, Pengfei Hu, Aishan Liu, Renshuai Tao, Haotong Qin, Xianglong Liu, Dacheng Tao

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

An Empirical study of Data-Free Quantization's Tuning Robustness.

Hong Chen, Yuxuan Wen, Yifu Ding, Zhen Yang, Yufei Guo, Haotong Qin

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

2021

Boosting Temporal Binary Coding for Large-Scale Video Search.

Yan Wu, Xianglong Liu, Haotong Qin, Ke Xia, Sheng Hu, Yuqing Ma, Meng Wang

IEEE Trans. Multim., 2021

Sequential alignment attention model for scene text recognition.

Yan Wu, Jiaxin Fan, Renshuai Tao, Jiakai Wang, Haotong Qin, Aishan Liu, Xianglong Liu

J. Vis. Commun. Image Represent., 2021

Diverse Sample Generation: Pushing the Limit of Data-free Quantization.

Haotong Qin, Yifu Ding, Xiangguo Zhang, Aoyu Li, Jiakai Wang, Xianglong Liu, Jiwen Lu

CoRR, 2021

Over-sampling De-occlusion Attention Network for Prohibited Items Detection in Noisy X-ray Images.

Renshuai Tao, Yanlu Wei, Hainan Li, Aishan Liu, Yifu Ding, Haotong Qin, Xianglong Liu

CoRR, 2021

Improving Generalization of Deepfake Detection with Domain Adaptive Batch Normalization.

Zixin Yin, Jiakai Wang, Yifu Ding, Yisong Xiao, Jun Guo, Renshuai Tao, Haotong Qin

Proceedings of the ADVM '21: Proceedings of the 1st International Workshop on Adversarial Learning for Multimedia, 2021

Hardware-friendly Deep Learning by Network Quantization and Binarization.

Haotong Qin

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Multi-Pretext Attention Network For Few-Shot Learning With Self-Supervision.

Hainan Li, Renshuai Tao, Jun Li, Haotong Qin, Yifu Ding, Shuo Wang, Xianglong Liu

Proceedings of the 2021 IEEE International Conference on Multimedia and Expo, 2021

BiPointNet: Binary Neural Network for Point Clouds.

Haotong Qin, Zhongang Cai, Mingyuan Zhang, Yifu Ding, Haiyu Zhao, Shuai Yi, Xianglong Liu, Hao Su

Proceedings of the 9th International Conference on Learning Representations, 2021

Towards Real-world X-ray Security Inspection: A High-Quality Benchmark And Lateral Inhibition Module For Prohibited Items Detection.

Renshuai Tao, Yanlu Wei, Xiangjian Jiang, Hainan Li, Haotong Qin, Jiakai Wang, Yuqing Ma, Libo Zhang, Xianglong Liu

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

Diversifying Sample Generation for Accurate Data-Free Quantization.

Xiangguo Zhang, Haotong Qin, Yifu Ding, Ruihao Gong, Qinghua Yan, Renshuai Tao, Yuhang Li, Fengwei Yu, Xianglong Liu

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

2020

Binary neural networks: A survey.

Haotong Qin, Ruihao Gong, Xianglong Liu, Xiao Bai, Jingkuan Song, Nicu Sebe

Pattern Recognit., 2020

Forward and Backward Information Retention for Accurate Binary Neural Networks.

Haotong Qin, Ruihao Gong, Xianglong Liu, Mingzhu Shen, Ziran Wei, Fengwei Yu, Jingkuan Song

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020