Jianguo Li's Homepage
Jianguo Li's Homepage
Jianguo Li (in some early publications Jianguo Lee) is a tech-director with Ant Research, leading the R&D in AGI innovation. He joined Ant Group in June 2006, before that he was a research scientist with Intel Labs after he got his PhD degree from Tsinghua University. His research interests includes machine learning, deep learning and their applications in various domains.Â
During his tenure at Intel, he won 3 Intel Labs highest Gordy awards (name after Gordon Moore) including 1 single personal award in 2020. His work at Intel has been transferred to and shipped with Intel Products, including hardware features on CPU & accelerators. Â
At Ant Group, he led team won 2 T-Star awards (highest at in tech domain) in 2021 and 2024 and 1 SuperMA award (highest the whole company) in 2022. His work at Ant has been widely utilized in various infrastructure within Ant Group. He led the development of the CodeFuse LLM project at Ant Group.Â
He had published 70+ peer-reviewed papers with 14K+ citations in top-tier conferences/journals, and hold 50+ US issued patents. He is a senior member of IEEE.Â
Selected PublicationsÂ
Note: * for my students & interns
GALLa: Graph Aligned Large Language Models for Improved Source Code Understanding
Ziyin Zhang, Hang Yu, Shijie Li, Peng Di, Jianguo Li, Rui Wang
ACL 2025, main conf accepted
Rodimus*: Breaking the Accuracy-Efficiency Trade-Off with Efficient Attentions
Zhihao He, Hang Yu, Zi Gong, Shizhan Liu, Jianguo Li, Weiyao Lin
ICLR 2025, accepted
CAKE: Cascading and Adaptive KV Cache Eviction with Layer Preferences
Ziran Qin, Yuchen Cao, Mingbao Lin, Wen Hu, Shixuan Fan, Ke Cheng, Weiyao Lin, Jianguo Li
ICLR 2025, accepted
SCOOT: SLO-Oriented Performance Tuning for LLM Inference EnginesÂ
Ke Cheng, Zhi Wang, Wen Hu, Tiannuo Yang, Jianguo Li, Sheng Zhang
WWW, 2025, accepted (Orals)
Toward Accurate and Robust Pedestrian Detection via Variational Inference
Huanyu He, Weiyao Lin, Yuang Zhang, Tianyao He, Yuxi Li, Jianguo LiÂ
IJCV, 2024, accepted
Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code
Ziyin Zhang, Chaoyu Chen, Bingchang Liu, Cong Liao, Zi Gong, Hang Yu, Jianguo Li, Rui Wang
Trans. Machine Learning Research, 2024, accepted
DeepITE: Designing Variational Graph Autoencoders for Intervention Target Estimation
Hongyuan Tao, Hang Yu, Jianguo Li
NeurIPS 2024, accepted
CoBa: Convergence Balancer for Multitask Finetuning of Large Language Models
Zi Gong, Hang Yu, Cong Liao, Bingchang Liu, Chaoyu Chen, Jianguo Li
EMNLP 2024, accepted
Functional Relation Field: A Model-Agnostic Framework for Multivariate Time Series Forecasting
Ting Li, Bing Yu, Jianguo Li, Zhanxing Zhu
Artificial Intelligence 2024, accepted
DUPLEX: Dual GAT for Complex Embedding of Directed Graphs
Zhaoru Ke, Hang Yu, Jianguo Li, Haipeng Zhang
ICML 2024
MFTCoder: Boosting Code LLMs with Multitask Fine-Tuning
Bingchang Liu, Chaoyu Chen, Zi Gong, Cong Liao, Wanghuanh, Zhichao Lei, Ming Liang, Chen Dajun, Min Shen, Hailian Zhou, wei jiang, Hang Yu, Jianguo Li
KDD 2024
D2LLM: Decomposed and Distilled Large Language Models for Semantic Search
Zihan Liao, Hang Yu, Jianguo Li, Jun Wang, Wei Zhang
ACL 2024
CoCA: Fusing Position Embedding with Collinear Constrained Attention in Transformers for Long Context Window Extending
Shiyi Zhu, Jing Ye, Wei Jiang, Siqiao Xue, Qi Zhang, Yifan Wu, Jianguo Li
ACL 2024
Enabling Efficient Batch Serving for LMaaS via Generation Length Prediction
Ke Chen, Wen Hu, Zhi Wang, Peng Du, Jianguo Li, Sheng Zhang
ICWS 2024
DeepScaling: Autoscaling Microservices with Stable CPU Utilization for Large Scale Production Cloud SystemsÂ
Ziliang Wang, Shiyi Zhu, Jianguo Li, Wei Jiang, K. K. Ramakrishnan, ..., Alex X. Liu
IEEE/ACM Trans. on Networking, accepted
VDTuner: Automated Performance Tuning for Vector Data Management Systems
Tiannuo Yang, Wen Hu, Wangqi Peng, Yusen Li, Jianguo Li, Gang Wang, Xiaoguang Liu
Finite-State Autoregressive Entropy Coding for Efficient Learned Lossless Compression
Yufeng Zhang, Hang Yu, Jianguo Li, Weiyao Lin
ICLR 2024, spotlight  [paper] [code]
AmortizedPeriod: Attention-based Amortized Inference for Periodicity Identification
Hang Yu, Cong Liao, Ruolan Liu, Jianguo Li, Yun Hu, Xinzhe Wang
ICLR 2024 [paper]
BasisFormer: Attention-based Time Series Forecasting with Learnable and Interpretable Basis
Zelin Ni, Hang Yu, Shizhan Liu, Jianguo Li, Weiyao Lin
Neural Lad: A Neural Latent Dynamics Framework for Times Series Modeling
Ting Li, Jianguo Li, Zhanxing Zhu
NeurIPS 2023Â
Twin Graph-based Anomaly Detection via Attentive Multi-Modal Learning for Microservice System
Jun Huang, Yang Yang, Hang Yu, Jianguo Li, Xiao Zheng
ASE 2023Â
ZeroAE: Pre-trained Language Model based Autoencoder for Transductive Zero-shot Text Classification
Kaihao Guo, Hang Yu, Cong Liao, Jianguo Li, Haipeng Zhang
ACL 2023 Findings  [paper]
BALANCE: Bayesian Linear Attribution for Root Cause Localization
Chaoyu Chen, Hang Yu, Zhichao Lei, Jianguo Li, Shaokang Ren, Tingkai Zhang, Silin Hu, Jianchao Wang, Wenhui Shi
SIGMOD 2023 Â [paper]
An Empirical Study on Change-induced Incidents of Online Service Systems
Yifan Wu, Bingxu Chai, Ying Li, Bingchang Liu, Jianguo Li, Yong Yang, Wei Jiang
ICSE (SEIP) 2023
Pyraformer: Low complexity pyramidal Attention For Long-range Time Series Modeling and Forecasting
Shizhan Liu*, Hang Yu, Cong Liao, Jianguo Li, Weiyao Lin...
ICLR 2022 Oral (1.6%)Â [paper] [code]
DeepScaling: Microservices AutoScaling for Stable CPU Utilization in Large Scale Cloud Systems
Ziliang Wang, Shiyi Zhu, Jianguo Li, Wei Jiang, K. K. Ramakrishnan, ..., Alex X. Liu
ACM SoCC 2022 [Slides]
Investigating and Improving Log Parsing in Practice
Ying Fu, Meng Yan, Jian Xu, Jianguo Li, Zhongxin Liu, Xiaohong Zhang, Dan Yang
ACM ESEC/FSE 2022
Regularized Graph Structure Learning with Semantic Knowledge for Multi-variates Time-Series Forecasting
Hongyuan Yu*, Ting Li, Weicheng Yu, Jianguo Li, Yan Huang, Liang Wang...
IJCAI 2022
A Meta Reinforcement Learning Approach for Predictive Autoscaling in the Cloud
Siqiao Xue, Chao Qu, Xiaoming Shi, Cong Liao, Shiyi Zhu, ..., Jianguo Li and James Zhang
KDD 2022
Learning Scale-Consistent Attention Part Network for Fine-grained Image Recognition
Huabing Liu*, Jianguo Li, Dian Li, Weiyao Lin
IEEE Trans. Multimedia 2021.
Variational Pedestrian Detection
YuAng Zhang*, Huanyu He*, Jianguo Li, Yuxi Li, John See, Weiyao Lin
CVPR 2021
Toward Accurate Visual Reasoning With Dual-Path Neural Module Networks
Ke Su*, Hang Su, Jianguo Li, Jun Zhu
Frontiers in Robotics and AI published 2020.
Story driven Video Editing
Zheng Wang, Jianguo Li, Yu-Gang Jiang
IEEE Trans. Multimedia 2021.
ATRW: A benchmark for Amur Tiger Re-Identification in the Wild
Shuyuan Li, Jianguo Li, Hanlin Tang, Rui Qian, Weiyao Lin
ACM Multimedia 2020
AP-Loss for Accurate One-Stage Object Detection
Kean Chen, Jianguo Li, Weiyao Lin, John See, Ji Wang, Junni Zou
IEEE Trans. on PAMI Accepted, April. 2020 [Code]
Few Sample Knowledge Distillation for Efficient Network Compression
Tianhong Li, Jianguo Li, Zhuang Liu, Changshui Zhang
CVPR 2020
Object Detection from Scratch with Deep Supervision
Zhiqiang Shen, Zhuang Liu, Jianguo Li, Yu-Gang Jiang, Yurong Chen, Xiangyang Xue
IEEE Trans. on PAMI Feb., 2020
Towards Accurate One-Stage Object Detection with AP-Loss
Kean Chen, Jianguo Li, Weiyao Lin, John See, et al.
CVPR 2019
Stochastic Quantization for Learning Accurate Low-bit Deep Neural Networks
Yinpeng Dong, Renkun Ni, Jianguo Li, Yurong Chen, Hang Su, Jun Zhu
IJCV Mar., 2019
Composite Binary Decomposition Networks
You Qiaoben, Zheng Wang, Jianguo Li, Yinpeng Dong, Yu-Gang Jiang, Jun Zhu
AAAI 2019
Tiny-DSOD: Lightweight Object Detection for Resource-Restricted Usages
Yuxi Li, Jiuwei Li, Weiyao Lin, Jianguo Li
BMVC 2018 [Code]
Network Decoupling: From Regular to Depthwise Separable Convolutions
Jianbo Guo, Yuxi Li, Weiyao Lin, Yurong Chen, Jianguo Li
BMVC 2018 [Code]
Visual Content Recognition by Exploiting Semantic Feature Map with Attention and Multi-task Learning
Rui-wei Zhao, Qi Zhang, Zuxuan Wu, Jianguo Li, Yu-gang Jiang
ACM ToMM Vol 1. 2019
Boosting Adversarial Attacks with Momentum
Yinpeng Dong, Fangzhou Liao, Tianyu Pang, Hang Su, Jun Zhu, Xiaolin Hu, Jianguo Li
CVPR 2018 (spotlight) [Code]
Learning Visual Knowledge Memory Networks for Visual Question Answering
Zhou Su, Chen Zhu, Yinpeng Dong, Dongqi Cai, Yurong Chen, Jianguo Li
CVPR 2018
Learning Semantic Feature Map for Visual Content Recognition
Rui-wei Zhao, Zuxuan Wu, Jianguo Li, Yu-Gang Jiang
ACM Multimedia 2017 (full-length research paper)
Learning Efficient Convolutional Networks through Network Slimming
Zhuang Liu, Jianguo Li, Zhiqiang Shen, Gao Huang, Shoumeng Yan, Changshui Zhang
ICCV 2017 [Code]
DSOD: Learning Deeply Supervised Object Detectors from Scratch
Zhiqiang Shen, Zhuang Liu, Jianguo Li, Yu-Gang Jiang, Yurong Chen, Xiangyang Xue
ICCV 2017 [Code]
BodyFusion: Real-time Capture of Human Motion and Surface Geometry Using a Single Depth Camera
Tao Yu, Kaiwen Guo, Feng Xu, Yuan Dong, Zhaoqi Su, Jianhui Zhao, Jianguo Li, Qionghai Dai and Yebin Liu
ICCV 2017 [Project Page]
Learning Accurate Low-Bit Deep Neural Networks with Stochastic Quantization
Yinpeng Dong, Renkun Ni, Jianguo Li, Hang Su, Jun Zhu
BMVC 2017 (Oral) [Code] (best paper finalist)
Weakly Supervised Dense Video Captioning
Zhiqiang Shen, Jianguo Li, Zhou Su, Minjun Li, Yurong Chen, Yu-Gang Jiang, Xiangyang Xue
CVPR 2017
Binary Optimized Hashing
Qi Dai, Jianguo Li, Jingdong Wang, Yu-Gang Jiang
ACM Multimedia 2016 (full-length oral paper)
Regional Gating Neural Networks for Multi-Label Image Classification
Rui-wei Zhao, Jianguo Li, Yurong Chen, Yu-Gang Jiang
BMVC 2016 (oral)
A Bayesian Hashing approach and its application to face recognition
Qi Dai, Jianguo Li, Jun Wang, Yurong chen, Yu-Gang Jiang
Neurocomputing June, 2016
Deep Attributes from Context-Aware Regional Neural Codes
Jianwei Luo, Jianguo Li
[CoRR abs/1509.02470]
Optimal Bayesian Hashing for Efficient Face Recognition
Dai Qi, Jianguo Li, Jun Wang, Yu-Gang Jiang
IJCAI 2015
Learning SURF Cascade for Fast and Accurate Object Detection
Jianguo Li
CVPR 2013[Project page]
Interactive Object Segmentation from Multi-view Images
Anh Nguyen, Jianfei Cai, Jianmin Zheng, Jianguo Li
Journal of Visual Communication and Image Representation, 2013.
Face Detection Using SURF Cascade
Jianguo Li, Tao Wang
ICCV 2011 workshop on BeFIT. [Project Page]
Bundled Depth-Map Merging for Multi-View Stereo
Jianguo Li, Eric Li, Yurong Cheng, Lin Xu
CVPR 2010 (oral) [webpage]
A general texture mapping framework for image-based 3D modeling
Lin Xu, Eric Li, Jianguo Li, Yurong Chen
ICIP 2010.
Accelerating Video-Mining Applications Using Many Small, General-Purpose Cores
Eric Li, Wenlong Li, Xiaofeng Tong, Jianguo Li, et al.
IEEE Micro vol. 28, no. 5, pp. 8-21, 2008.
One step beyond histograms: image representation using Markov stationary features
Jianguo Li, Weixin Wu, Tao Wang
CVPR 2008 (Oral) [Win32 binary toolkit]
Novel parallel Hough transform on multi-core processors
Yen-Kuang Chen, Wenlong Li, Jianguo Li, et al.
ICASSP 2008.
Discriminant Additive Tangent Space for Object Recognition
Liang Xiong, Jianguo Li, Changshui Zhang
CVPR 2007
Cast Indexing for videos by ncuts and page ranking
Yong Gao, Tao Wang, Jianguo Li, et al.
ACM CIVR 2007.
Generalized Additive Bayesian Network Classifiers
Jianguo Li, Changshui Zhang, Tao Wang
IJCAI 2007
Face Recognition using Integral Gabor-Haar Transformation
Jianguo Li, Tao Wang, Yimin Zhang
IEEE ICIP 2007.[SDK]
Semantic Event Detection using Conditional Random Fields
Tao Wang, Jianguo Li, et al.
In: Proc. CVPR 2006 Workshop; 109~116
Soccer highlight detection Using two-dependence Bayesian network
Jianguo Li, Tao Wang, et al.
ICME 2006
Classification of Gene-expression Data: the Manifold based Metric Learning Way
Jianguo Lee, Changshui Zhang
Pattern Recognition, 39:2450-2463, 2006
Visual Object Recognition using Probabilistic Kernel Subspace Similarity
Jianguo Lee, Jingdong Wang, Changshui Zhang, Zhaoqi Bian
Pattern Recognition, 38: 997-1008, 2005
Probabilistic Tangent Subspace: A Unified View
Jianguo Lee, Jingdong Wang, Changshui Zhang, Zhaoqi Bian
ICML 2004
Kernel trick embedded Gaussian Mixture model
Jingdong Wang, Jianguo Lee, Changshui Zhang
In Algorithmic Learning Theory, 2003
Color Image Segmentation: Kernel Do the Feature Space
Jianguo Lee, Jingdong Wang, Changshui Zhang
ECML 2003
Copyright (C) Jianguo Lee 2006~2025.