Cao, Kaidi

17 publications

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 Zou

NeurIPS 2024 GraphMETRO: Mitigating Complex Graph Distribution Shifts via Mixture of Aligned Experts Shirley Wu, Kaidi Cao, Bruno Ribeiro, James Zou, Jure Leskovec

NeurIPSW 2024 PyTorch Frame: A Modular Framework for Multi-Modal Tabular Learning Weihua Hu, Yiwen Yuan, Zecheng Zhang, Akihiro Nitta, Kaidi Cao, Vid Kocijan, Jinu Sunil, Jure Leskovec, Matthias Fey

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 Zou, Jure Leskovec

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

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

ICMLW 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 Mangpo Phothilimthana, Sami Abu-El-Haija, Kaidi Cao, Bahare Fatemi, Michael Burrows, Charith Mendis, Bryan Perozzi

NeurIPSW 2022 AutoTransfer: AutoML with Knowledge Transfer - An Application to Graph Neural Networks Kaidi Cao, Jiaxuan You, Jiaju Liu, Jure Leskovec

ICLR 2022 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 2021 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 Arechiga, Adrien Gaidon, Tengyu Ma

NeurIPS 2020 Coresets for Robust Training of Deep Neural Networks Against Noisy Labels Baharan Mirzasoleiman, Kaidi Cao, Jure Leskovec

ICLRW 2019 Disentangling Content and Style via Unsupervised Geometry Distillation Wayne Wu, Kaidi Cao, Cheng Li, Chen Qian, Chen Change Loy

NeurIPS 2019 Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss Kaidi Cao, Colin Wei, Adrien Gaidon, Nikos Arechiga, Tengyu Ma

AAAI 2018 Merge or Not? Learning to Group Faces via Imitation Learning Yue He, Kaidi Cao, Cheng Li, Chen Change Loy