Jieyu Zhang
Cited by
Cited by
A Survey on Graph Structure Learning: Progress and Opportunities
Y Zhu, W Xu, J Zhang, Y Du, J Zhang, Q Liu, C Yang, S Wu
arXiv preprint arXiv:2103.03036, 2021
AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework
Q Wu, G Bansal, J Zhang, Y Wu, S Zhang, E Zhu, B Li, L Jiang, X Zhang, ...
arXiv preprint arXiv:2308.08155, 2023
Datacomp: In search of the next generation of multimodal datasets
SY Gadre, G Ilharco, A Fang, J Hayase, G Smyrnis, T Nguyen, R Marten, ...
Advances in Neural Information Processing Systems 36, 2024
WRENCH: A Comprehensive Benchmark for Weak Supervision
J Zhang, Y Yu, Y Li, Y Wang, Y Yang, M Yang, A Ratner
35th Conference on Neural Information Processing Systems (NeurIPS 2021 …, 2021
A Survey on Programmatic Weak Supervision
J Zhang, CY Hsieh, Y Yu, C Zhang, A Ratner
arXiv preprint arXiv:2202.05433, 2022
Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias
Y Yu*, Y Zhuang*, J Zhang*, Y Meng, A Ratner, R Krishna, J Shen, ...
Advances in Neural Information Processing Systems 36, 2023
A survey on deep graph generation: Methods and applications
Y Zhu, Y Du, Y Wang, Y Xu, J Zhang, Q Liu, S Wu
Learning on Graphs Conference, 47: 1-47: 21, 2022
Single-pass contrastive learning can work for both homophilic and heterophilic graph
H Wang, J Zhang, Q Zhu, W Huang, K Kawaguchi, X Xiao
Transactions on Machine Learning Research, 2023
Relation learning on social networks with multi-modal graph edge variational autoencoders
C Yang, J Zhang, H Wang, S Li, M Kim, M Walker, Y Xiao, J Han
Proceedings of the 13th International Conference on Web Search and Data …, 2020
Scibench: Evaluating college-level scientific problem-solving abilities of large language models
X Wang, Z Hu, P Lu, Y Zhu, J Zhang, S Subramaniam, AR Loomba, ...
arXiv preprint arXiv:2307.10635, 2023
AcTune: Uncertainty-Based Active Self-Training for Active Fine-Tuning of Pretrained Language Models
Y Yu, L Kong, J Zhang, R Zhang, C Zhang
Proceedings of the 2022 Conference of the North American Chapter of the …, 2022
Co-embedding network nodes and hierarchical labels with taxonomy based generative adversarial networks
C Yang, J Zhang, J Han
2020 IEEE International Conference on Data Mining (ICDM), 721-730, 2020
SugarCrepe: Fixing Hackable Benchmarks for Vision-Language Compositionality
CY Hsieh*, J Zhang*, Z Ma, A Kembhavi, R Krishna
arXiv preprint arXiv:2306.14610, 2023
Taxonomy Completion via Triplet Matching Network
J Zhang, X Song, Y Zeng, J Chen, J Shen, Y Mao, L Li
Proceedings of the AAAI Conference on Artificial Intelligence, 2021
Cold-Start Data Selection for Few-shot Language Model Fine-tuning: A Prompt-Based Uncertainty Propagation Approach
Y Yu, R Zhang, R Xu, J Zhang, J Shen, C Zhang
arXiv preprint arXiv:2209.06995, 2022
TaxoEnrich: Self-Supervised Taxonomy Completion via Structure-Semantic Representations
M Jiang, X Song, J Zhang, J Han
Proceedings of the ACM Web Conference 2022, 925-934, 2022
Neural embedding propagation on heterogeneous networks
C Yang*, J Zhang*, J Han
2019 IEEE International Conference on Data Mining (ICDM), 698-707, 2019
Creating Training Sets via Weak Indirect Supervision
J Zhang, B Wang, X Song, Y Wang, Y Yang, J Bai, A Ratner
International Conference on Learning Representations (ICLR 2022), 2021
EcoAssistant: Using LLM Assistant More Affordably and Accurately
J Zhang, R Krishna, AH Awadallah, C Wang
arXiv preprint arXiv:2310.03046, 2023
Learning Hyper Label Model for Programmatic Weak Supervision
XC Renzhi Wu, Shen-En Chen, Jieyu Zhang
The Eleventh International Conference on Learning Representations, 2023
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