Merge or Not? Learning to Group Faces via Imitation Learning. - Yue He; Kaidi Cao; Cheng Li 009; Chen Change Loy (AAAI, 2018)

Pose-Robust Face Recognition via Deep Residual Equivariant Mapping. - Kaidi Cao; Yu Rong 003; Cheng Li 009; Xiaoou Tang; Chen Change Loy (CVPR, 2018)

DNN Dataflow Choice Is Overrated. - Xuan Yang; Mingyu Gao 001; Jing Pu; Ankita Nayak; Qiaoyi Liu; Steven Bell; Jeff Setter; Kaidi Cao; Heonjae Ha; Christos Kozyrakis; Mark Horowitz (CoRR, 2018)

CariGANs: unpaired photo-to-caricature translation. - Kaidi Cao; Jing Liao 001; Lu Yuan (ACM Trans. Graph., 2018)

TransGaGa: Geometry-Aware Unsupervised Image-To-Image Translation. - Wayne Wu; Kaidi Cao; Cheng Li 009; Chen Qian 006; Chen Change Loy (CVPR, 2019)

Learning Temporal Action Proposals With Fewer Labels. - Jingwei Ji; Kaidi Cao; Juan Carlos Niebles (ICCV, 2019)

Delving Deep Into Hybrid Annotations for 3D Human Recovery in the Wild. - Yu Rong 003; Ziwei Liu 002; Cheng Li 009; Kaidi Cao; Chen Change Loy (ICCV, 2019)

Disentangling Content and Style via Unsupervised Geometry Distillation. - Wayne Wu; Kaidi Cao; Cheng Li 009; Chen Qian 006; Chen Change Loy (DGS@ICLR, 2019)

Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss. - Kaidi Cao; Colin Wei; Adrien Gaidon; Nikos Aréchiga; Tengyu Ma 001 (NeurIPS, 2019)

Interstellar: Using Halide's Scheduling Language to Analyze DNN Accelerators. - Xuan Yang; Mingyu Gao 001; Qiaoyi Liu; Jeff Setter; Jing Pu; Ankita Nayak; Steven Bell; Kaidi Cao; Heonjae Ha; Priyanka Raina; Christos Kozyrakis; Mark Horowitz (ASPLOS, 2020)

Few-Shot Video Classification via Temporal Alignment. - Kaidi Cao; Jingwei Ji; Zhangjie Cao; Chien-Yi Chang; Juan Carlos Niebles (CVPR, 2020)

Coresets for Robust Training of Deep Neural Networks against Noisy Labels. - Baharan Mirzasoleiman; Kaidi Cao; Jure Leskovec (NeurIPS, 2020)

Concept Learners for Generalizable Few-Shot Learning. - Kaidi Cao; Maria Brbic; Jure Leskovec (CoRR, 2020)

Coresets for Robust Training of Neural Networks against Noisy Labels. - Baharan Mirzasoleiman; Kaidi Cao; Jure Leskovec (CoRR, 2020)

Concept Learners for Few-Shot Learning. - Kaidi Cao; Maria Brbic; Jure Leskovec (ICLR, 2021)

Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization. - Kaidi Cao; Yining Chen; Junwei Lu; Nikos Aréchiga; Adrien Gaidon; Tengyu Ma 001 (ICLR, 2021)

Open-World Semi-Supervised Learning. - Kaidi Cao; Maria Brbic; Jure Leskovec (ICLR, 2022)

Relational Multi-Task Learning: Modeling Relations between Data and Tasks. - Kaidi Cao; Jiaxuan You; Jure Leskovec (ICLR, 2022)

Learning Backward Compatible Embeddings. - Weihua Hu; Rajas Bansal; Kaidi Cao; Nikhil Rao 001; Karthik Subbian; Jure Leskovec (KDD, 2022)

Learning Large-scale Subsurface Simulations with a Hybrid Graph Network Simulator. - Tailin Wu; Qinchen Wang; Yinan Zhang; Rex Ying; Kaidi Cao; Rok Sosic; Ridwan Jalali; Hassan Hamam; Marko Maucec; Jure Leskovec (KDD, 2022)

TuneUp: A Training Strategy for Improving Generalization of Graph Neural Networks. - Weihua Hu; Kaidi Cao; Kexin Huang; Edward W. Huang; Karthik Subbian; Jure Leskovec (CoRR, 2022)

AutoTransfer: AutoML with Knowledge Transfer - An Application to Graph Neural Networks. - Kaidi Cao; Jiaxuan You; Jiaju Liu; Jure Leskovec (ICLR, 2023)

Learning Large Graph Property Prediction via Graph Segment Training. - Kaidi Cao; Phitchaya Mangpo Phothilimthana; Sami Abu-El-Haija; Dustin Zelle; Yanqi Zhou; Charith Mendis; Jure Leskovec; Bryan Perozzi (NeurIPS, 2023)

TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs. - Phitchaya Mangpo Phothilimthana; Sami Abu-El-Haija; Kaidi Cao; Bahare Fatemi; Michael Burrows; Charith Mendis; Bryan Perozzi (NeurIPS, 2023)

Communication-Free Distributed GNN Training with Vertex Cut. - Kaidi Cao; Rui Deng; Shirley Wu; Edward W. Huang; Karthik Subbian; Jure Leskovec (CoRR, 2023)

TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs. - Phitchaya Mangpo Phothilimthana; Sami Abu-El-Haija; Kaidi Cao; Bahare Fatemi; Charith Mendis; Bryan Perozzi (CoRR, 2023)

GraphMETRO: Mitigating Complex Distribution Shifts in GNNs via Mixture of Aligned Experts. - Shirley Wu; Kaidi Cao; Bruno Ribeiro 001; James Zou 001; Jure Leskovec (CoRR, 2023)

GraphMETRO: Mitigating Complex Graph Distribution Shifts via Mixture of Aligned Experts. - Shirley Wu; Kaidi Cao; Bruno Ribeiro 001; James Y. Zou; Jure Leskovec (NeurIPS, 2024)

AvaTaR: Optimizing LLM Agents for Tool Usage via Contrastive Reasoning. - Shirley Wu; Shiyu Zhao; Qian Huang; Kexin Huang; Michihiro Yasunaga; Kaidi Cao; Vassilis N. Ioannidis; Karthik Subbian; Jure Leskovec; James Y. Zou (NeurIPS, 2024)

STaRK: Benchmarking LLM Retrieval on Textual and Relational Knowledge Bases. - Shirley Wu; Shiyu Zhao; Michihiro Yasunaga; Kexin Huang; Kaidi Cao; Qian Huang; Vassilis N. Ioannidis; Karthik Subbian; James Y. Zou; Jure Leskovec (NeurIPS, 2024)

PyTorch Frame: A Modular Framework for Multi-Modal Tabular Learning. - Weihua Hu; Yiwen Yuan; Zecheng Zhang; Akihiro Nitta; Kaidi Cao; Vid Kocijan; Jure Leskovec; Matthias Fey (CoRR, 2024)

AvaTaR: Optimizing LLM Agents for Tool-Assisted Knowledge Retrieval. - Shirley Wu; Shiyu Zhao; Qian Huang; Kexin Huang; Michihiro Yasunaga; Kaidi Cao; Vassilis N. Ioannidis; Karthik Subbian; Jure Leskovec; James Zou 001 (CoRR, 2024)

Periodic Wave Train Solutions of the Age-Structured SIRS Epidemic Model with Diffusion. - Kaidi Cao; Yajing Li; Zhihua Liu (Int. J. Bifurc. Chaos, 2025)