| AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversations Q Wu, G Bansal, J Zhang, Y Wu, B Li, E Zhu, L Jiang, X Zhang, S Zhang, ... COLM 2024, 2024 | 784* | 2024 |
| Datacomp: In search of the next generation of multimodal datasets SY Gadre, G Ilharco, A Fang, J Hayase, G Smyrnis, T Nguyen, R Marten, ... NeurIPS 2023, 2023 | 362 | 2023 |
| 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 | 307* | 2021 |
| 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, ... NeurIPS 2023, 2023 | 185 | 2023 |
| WRENCH: A Comprehensive Benchmark for Weak Supervision J Zhang, Y Yu, Y Li, Y Wang, Y Yang, M Yang, A Ratner NeurIPS 2021, 2021 | 115 | 2021 |
| SugarCrepe: Fixing Hackable Benchmarks for Vision-Language Compositionality CY Hsieh*, J Zhang*, Z Ma, A Kembhavi, R Krishna NeurIPS 2023, 2023 | 104 | 2023 |
| 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, ... ICML 2024, 2024 | 99 | 2024 |
| A Survey on Programmatic Weak Supervision J Zhang, CY Hsieh, Y Yu, C Zhang, A Ratner arXiv preprint arXiv:2202.05433, 2022 | 93 | 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 | 82* | 2023 |
| Datacomp-lm: In search of the next generation of training sets for language models J Li, A Fang, G Smyrnis, M Ivgi, M Jordan, S Gadre, H Bansal, E Guha, ... arXiv preprint arXiv:2406.11794, 2024 | 69* | 2024 |
| 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 | 55 | 2020 |
| 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 | 50* | 2022 |
| xGen-MM (BLIP-3): A Family of Open Large Multimodal Models L Xue, M Shu, A Awadalla, J Wang, A Yan, S Purushwalkam, H Zhou, ... arXiv preprint arXiv:2408.08872, 2024 | 48 | 2024 |
| 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 | 42* | 2022 |
| 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 | 42 | 2021 |
| 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 | 40 | 2022 |
| EHRAgent: Code Empowers Large Language Models for Complex Tabular Reasoning on Electronic Health Records W Shi, R Xu, Y Zhuang, Y Yu, J Zhang, H Wu, Y Zhu, J Ho, C Yang, ... arXiv preprint arXiv:2401.07128, 2024 | 35* | 2024 |
| EcoAssistant: Using LLM Assistant More Affordably and Accurately J Zhang, R Krishna, AH Awadallah, C Wang arXiv preprint arXiv:2310.03046, 2023 | 35 | 2023 |
| 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 | 35 | 2020 |
| Offline Training of Language Model Agents with Functions as Learnable Weights S Zhang, J Zhang, J Liu, L Song, C Wang, R Krishna, Q Wu ICML 2024, 2024 | 25* | 2024 |
Yue YuMeta GenAI確認したメール アドレス: meta.com