Differentiable Soft Quantization: Bridging Full-Precision and Low-Bit Neural Networks. - Ruihao Gong; Xianglong Liu 001; Shenghu Jiang; Tianxiang Li; Peng Hu; Jiazhen Lin; Fengwei Yu; Junjie Yan (ICCV, 2019)

Balanced Binary Neural Networks with Gated Residual. - Mingzhu Shen; Xianglong Liu 001; Kai Han 002; Ruihao Gong; Yunhe Wang 001; Chang Xu 002 (CoRR, 2019)

Forward and Backward Information Retention for Accurate Binary Neural Networks. - Haotong Qin; Ruihao Gong; Xianglong Liu 001; Mingzhu Shen; Ziran Wei; Fengwei Yu; Jingkuan Song (CVPR, 2020)

Rotation Consistent Margin Loss for Efficient Low-Bit Face Recognition. - Yudong Wu; Yichao Wu; Ruihao Gong; Yuanhao Lv; Ken Chen; Ding Liang; Xiaolin Hu 001; Xianglong Liu 001; Junjie Yan (CVPR, 2020)

Towards Unified INT8 Training for Convolutional Neural Network. - Feng Zhu 006; Ruihao Gong; Fengwei Yu; Xianglong Liu 001; Yanfei Wang; Zhelong Li; Xiuqi Yang; Junjie Yan (CVPR, 2020)

Balanced Binary Neural Networks with Gated Residual. - Mingzhu Shen; Xianglong Liu 001; Ruihao Gong; Kai Han 002 (ICASSP, 2020)

Extremely Low-bit Convolution Optimization for Quantized Neural Network on Modern Computer Architectures. - Qingchang Han; Yongmin Hu; Fengwei Yu; Hailong Yang 002; Bing Liu; Peng Hu; Ruihao Gong; Yanfei Wang; Rui Wang 014; Zhongzhi Luan; Depei Qian (ICPP, 2020)

Efficient Bitwidth Search for Practical Mixed Precision Neural Network. - Yuhang Li 001; Wei Wang 059; Haoli Bai; Ruihao Gong; Xin Dong 009; Fengwei Yu (CoRR, 2020)

Learning in School: Multi-teacher Knowledge Inversion for Data-Free Quantization. - Yuhang Li 001; Feng Zhu 006; Ruihao Gong; Mingzhu Shen; Fengwei Yu; Shaoqing Lu; Shi Gu (CoRR, 2020)

Binary neural networks: A survey. - Haotong Qin; Ruihao Gong; Xianglong Liu 001; Xiao Bai 001; Jingkuan Song; Nicu Sebe (Pattern Recognit., 2020)

Diversifying Sample Generation for Accurate Data-Free Quantization. - Xiangguo Zhang; Haotong Qin; Yifu Ding; Ruihao Gong; Qinghua Yan; Renshuai Tao; Yuhang Li 001; Fengwei Yu; Xianglong Liu 001 (CVPR, 2021)

MixMix: All You Need for Data-Free Compression Are Feature and Data Mixing. - Yuhang Li 001; Feng Zhu 006; Ruihao Gong; Mingzhu Shen; Xin Dong 009; Fengwei Yu; Shaoqing Lu; Shi Gu (ICCV, 2021)

Once Quantization-Aware Training: High Performance Extremely Low-bit Architecture Search. - Mingzhu Shen; Feng Liang; Ruihao Gong; Yuhang Li 001; Chuming Li; Chen Lin 003; Fengwei Yu; Junjie Yan; Wanli Ouyang (ICCV, 2021)

BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction. - Yuhang Li 001; Ruihao Gong; Xu Tan; Yang Yang; Peng Hu; Qi Zhang; Fengwei Yu; Wei Wang 059; Shi Gu (ICLR, 2021)

A Free Lunch From ANN: Towards Efficient, Accurate Spiking Neural Networks Calibration. - Yuhang Li 001; Shikuang Deng; Xin Dong 009; Ruihao Gong; Shi Gu (ICML, 2021)

Real World Robustness from Systematic Noise. - Yan Wang 033; Yuhang Li 001; Ruihao Gong; Tianzi Xiao; Fengwei Yu (AdvM @ ACM Multimedia, 2021)

MQBench: Towards Reproducible and Deployable Model Quantization Benchmark. - Yuhang Li 001; Mingzhu Shen; Jian Ma; Yan Ren; Mingxin Zhao; Qi Zhang; Ruihao Gong; Fengwei Yu; Junjie Yan (NeurIPS Datasets and Benchmarks, 2021)

Real World Robustness from Systematic Noise. - Yan Wang 033; Yuhang Li 001; Ruihao Gong (CoRR, 2021)

RobustART: Benchmarking Robustness on Architecture Design and Training Techniques. - Shiyu Tang; Ruihao Gong; Yan Wang 033; Aishan Liu; Jiakai Wang; Xinyun Chen; Fengwei Yu; Xianglong Liu 001; Dawn Song; Alan L. Yuille; Philip H. S. Torr; Dacheng Tao (CoRR, 2021)

QDrop: Randomly Dropping Quantization for Extremely Low-bit Post-Training Quantization. - Xiuying Wei; Ruihao Gong; Yuhang Li 001; Xianglong Liu 001; Fengwei Yu (ICLR, 2022)

NNLQP: A Multi-Platform Neural Network Latency Query and Prediction System with An Evolving Database. - Liang Liu; Mingzhu Shen; Ruihao Gong; Fengwei Yu; Hailong Yang (ICPP, 2022)

Generating Transferable Adversarial Examples against Vision Transformers. - Yuxuan Wang; Jiakai Wang; Zixin Yin; Ruihao Gong; Jingyi Wang; Aishan Liu; Xianglong Liu 001 (ACM Multimedia, 2022)

Outlier Suppression: Pushing the Limit of Low-bit Transformer Language Models. - Xiuying Wei; Yunchen Zhang; Xiangguo Zhang; Ruihao Gong; Shanghang Zhang; Qi Zhang; Fengwei Yu; Xianglong Liu 001 (NeurIPS, 2022)

Exploring the Relationship between Architecture and Adversarially Robust Generalization. - Shiyu Tang; Siyuan Liang; Ruihao Gong; Aishan Liu; Xianglong Liu 001; Dacheng Tao (CoRR, 2022)

Adaptive Contrastive Knowledge Distillation for BERT Compression. - Jinyang Guo; Jiaheng Liu; Zining Wang; Yuqing Ma; Ruihao Gong; Ke Xu 001; Xianglong Liu 001 (ACL (Findings), 2023)

Exploring the Relationship Between Architectural Design and Adversarially Robust Generalization. - Aishan Liu; Shiyu Tang; Siyuan Liang; Ruihao Gong; Boxi Wu; Xianglong Liu 001; Dacheng Tao (CVPR, 2023)

Annealing-based Label-Transfer Learning for Open World Object Detection. - Yuqing Ma; Hainan Li; Zhange Zhang; Jinyang Guo; Shanghang Zhang; Ruihao Gong; Xianglong Liu 001 (CVPR, 2023)

Outlier Suppression+: Accurate quantization of large language models by equivalent and effective shifting and scaling. - Xiuying Wei; Yunchen Zhang; Yuhang Li 001; Xiangguo Zhang; Ruihao Gong; Jinyang Guo; Xianglong Liu 001 (EMNLP, 2023)

Lossy and Lossless (L2) Post-training Model Size Compression. - Yumeng Shi; Shihao Bai; Xiuying Wei; Ruihao Gong; Jianlei Yang 001 (ICCV, 2023)

Exploiting Subgraph Similarities for Efficient Auto-tuning of Tensor Programs. - Mingzhen Li 001; Hailong Yang 002; Shanjun Zhang; Fengwei Yu; Ruihao Gong; Yi Liu 013; Zhongzhi Luan; Depei Qian (ICPP, 2023)

SysNoise: Exploring and Benchmarking Training-Deployment System Inconsistency. - Yan Wang 033; Yuhang Li 001; Ruihao Gong; Aishan Liu; Yanfei Wang; Jian Hu; Yongqiang Yao; Yunchen Zhang; Tianzi Xiao; Fengwei Yu; Xianglong Liu 001 (MLSys, 2023)

Outlier Suppression+: Accurate quantization of large language models by equivalent and optimal shifting and scaling. - Xiuying Wei; Yunchen Zhang; Yuhang Li 001; Xiangguo Zhang; Ruihao Gong; Jinyang Guo; Xianglong Liu 001 (CoRR, 2023)

Exploring the Potential of Flexible 8-bit Format: Design and Algorithm. - Zhuoyi Zhang; Yunchen Zhang; Gonglei Shi; Yu Shen; Ruihao Gong; Xiaoxu Xia; Qi Zhang; Lewei Lu; Xianglong Liu 001 (CoRR, 2023)

Distribution-Sensitive Information Retention for Accurate Binary Neural Network. - Haotong Qin; Xiangguo Zhang; Ruihao Gong; Yifu Ding; Yi Xu 013; Xianglong Liu 001 (Int. J. Comput. Vis., 2023)

Selective Focus: Investigating Semantics Sensitivity in Post-training Quantization for Lane Detection. - Yunqian Fan; Xiuying Wei; Ruihao Gong; Yuqing Ma; Xiangguo Zhang; Qi Zhang; Xianglong Liu 001 (AAAI, 2024)

Fast and Controllable Post-training Sparsity: Learning Optimal Sparsity Allocation with Global Constraint in Minutes. - Ruihao Gong; Yang Yong; Zining Wang; Jinyang Guo; Xiuying Wei; Yuqing Ma; Xianglong Liu 001 (AAAI, 2024)

TFMQ-DM: Temporal Feature Maintenance Quantization for Diffusion Models. - Yushi Huang; Ruihao Gong; Jing Liu 048; Tianlong Chen 001; Xianglong Liu 001 (CVPR, 2024)

LLMC: Benchmarking Large Language Model Quantization with a Versatile Compression Toolkit. - Ruihao Gong; Yang Yong; Shiqiao Gu; Yushi Huang; Chengtao Lv; Yunchen Zhang; Dacheng Tao; Xianglong Liu 001 (EMNLP (Industry Track), 2024)

ProPD: Dynamic Token Tree Pruning and Generation for LLM Parallel Decoding. - Shuzhang Zhong; Zebin Yang; Ruihao Gong; Runsheng Wang; Ru Huang 001; Meng Li 004 (ICCAD, 2024)

QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Models. - Jing Liu; Ruihao Gong; Xiuying Wei; Zhiwei Dong; Jianfei Cai 001; Bohan Zhuang (ICLR, 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 001 (ICML, 2024)

PRoof: A Comprehensive Hierarchical Profiling Framework for Deep Neural Networks with Roofline Analysis. - Siyu Wu 001; Hailong Yang 002; Xin You; Ruihao Gong; Yi Liu 013; Zhongzhi Luan; Depei Qian (ICPP, 2024)

PTSBench: A Comprehensive Post-Training Sparsity Benchmark Towards Algorithms and Models. - Zining Wang; Jinyang Guo; Ruihao Gong; Yang Yong; Aishan Liu; Yushi Huang; Jiaheng Liu; Xianglong Liu 001 (ACM Multimedia, 2024)

2023 Low-Power Computer Vision Challenge (LPCVC) Summary. - Leo Chen; Benjamin Boardley; Ping Hu; Yiru Wang; Yifan Pu; Xin Jin; Yongqiang Yao; Ruihao Gong; Bo Li 026; Gao Huang 001; Xianglong Liu 001; Zifu Wan; et al. (CoRR, 2024)

LLM-QBench: A Benchmark Towards the Best Practice for Post-training Quantization of Large Language Models. - Ruihao Gong; Yang Yong; Shiqiao Gu; Yushi Huang; Yunchen Zhang; Xianglong Liu 001; Dacheng Tao (CoRR, 2024)

ME-Switch: A Memory-Efficient Expert Switching Framework for Large Language Models. - Jing Liu; Ruihao Gong; Mingyang Zhang 007; Yefei He; Jianfei Cai 001; Bohan Zhuang (CoRR, 2024)

Temporal Feature Matters: A Framework for Diffusion Model Quantization. - Yushi Huang; Ruihao Gong; Xianglong Liu 001; Jing Liu 048; Yuhang Li 001; Jiwen Lu; Dacheng Tao (CoRR, 2024)

OmniBal: Towards Fast Instruct-tuning for Vision-Language Models via Omniverse Computation Balance. - Yongqiang Yao; Jingru Tan; Jiahao Hu; Feizhao Zhang; Xin Jin; Bo Li; Ruihao Gong; Pengfei Liu (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 001 (CoRR, 2024)

HarmoniCa: Harmonizing Training and Inference for Better Feature Cache in Diffusion Transformer Acceleration. - Yushi Huang; Zining Wang; Ruihao Gong; Jing Liu; Xinjie Zhang; Jun Zhang (CoRR, 2024)

PTSBench: A Comprehensive Post-Training Sparsity Benchmark Towards Algorithms and Models. - Zining Wnag; Jinyang Guo; Ruihao Gong; Yang Yong; Aishan Liu; Yushi Huang; Jiaheng Liu; Xianglong Liu 001 (CoRR, 2024)

Rectify representation bias in vision-language models for long-tailed recognition. - Bo Li 126; Yongqiang Yao; Jingru Tan; Ruihao Gong; Jianwei Lu; Ye Luo (Neural Networks, 2024)

AtomNet: Designing Tiny Models from Operators Under Extreme MCU Constraints. - Zhiwei Dong; Mingzhu Shen; Shihao Bai; Xiuying Wei; Jinyang Guo; Ruihao Gong; Song-Lu Chen; Xianglong Liu 001; Xu-Cheng Yin (AAAI, 2025)

Pre³: Enabling Deterministic Pushdown Automata for Faster Structured LLM Generation. - Junyi Chen; Shihao Bai; Zaijun Wang; Siyu Wu 001; Chuheng Du; Hailong Yang 002; Ruihao Gong; Shengzhong Liu; Fan Wu 006; Guihai Chen (ACL (1), 2025)

Past-Future Scheduler for LLM Serving under SLA Guarantees. - Ruihao Gong; Shihao Bai; Siyu Wu 001; Yunqian Fan; Zaijun Wang; Xiuhong Li; Hailong Yang 002; Xianglong Liu 001 (ASPLOS (2), 2025)

Tool Playgrounds: A Comprehensive and Analyzable Benchmark for LLM Tool Invocation. - Zhiwei Dong; Ruihao Gong; Yang Yong; Shuo Wu; Yongqiang Yao; Song-Lu Chen; Xu-Cheng Yin (ICASSP, 2025)

Robust long-tailed recognition with distribution-aware adversarial example generation. - Bo Li 126; Yongqiang Yao; Jingru Tan; Dandan Zhu; Ruihao Gong; Ye Luo; Jianwei Lu (Neural Networks, 2025)

Hierarchical Balance Packing: Towards Efficient Supervised Fine-tuning for Long-Context LLM. - Yongqiang Yao; Jingru Tan; Kaihuan Liang; Feizhao Zhang; Yazhe Niu; Jiahao Hu; Ruihao Gong; Dahua Lin; Ningyi Xu (CoRR, 2025)

TokenSim: Enabling Hardware and Software Exploration for Large Language Model Inference Systems. - Feiyang Wu; Zhuohang Bian; Guoyang Duan; Tianle Xu; Junchi Wu; Teng Ma; Yongqiang Yao; Ruihao Gong; Youwei Zhuo (CoRR, 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, 2025)

Pre3: Enabling Deterministic Pushdown Automata for Faster Structured LLM Generation. - Junyi Chen; Shihao Bai; Zaijun Wang; Siyu Wu 001; Chuheng Du; Hailong Yang 002; Ruihao Gong; Shengzhong Liu; Fan Wu 006; Guihai Chen (CoRR, 2025)

Post-Training Quantization for Video Matting. - Tianrui Zhu; Houyuan Chen; Ruihao Gong; Michele Magno; Haotong Qin; Kai Zhang 008 (CoRR, 2025)

Pushing the Limit of Post-Training Quantization. - Ruihao Gong; Xianglong Liu 001; Yuhang Li 001; Yunqian Fan; Xiuying Wei; Jinyang Guo (IEEE Trans. Pattern Anal. Mach. Intell., 2025)

LLMC+: Benchmarking Vision-Language Model Compression with a Plug-and-play Toolkit. - Chengtao Lv; Bilang Zhang; Yang Yong; Ruihao Gong; Yushi Huang; Shiqiao Gu; Jiajun Wu 004; Yumeng Shi; Jinyang Guo; Wenya Wang (CoRR, 2025)