| Exploring the potential of large language models (llms) in learning on graphs Z Chen, H Mao, H Li, W Jin, H Wen, X Wei, S Wang, D Yin, W Fan, H Liu, ... ACM SIGKDD Explorations Newsletter 25 (2), 42-61, 2024 | 454 | 2024 |
| Label-free node classification on graphs with large language models (llms) Z Chen, H Mao, H Wen, H Han, W Jin, H Zhang, H Liu, J Tang arXiv preprint arXiv:2310.04668, 2023 | 132 | 2023 |
| Graph neural networks for multimodal single-cell data integration H Wen, J Ding, W Jin, Y Wang, Y Xie, J Tang Proceedings of the 28th ACM SIGKDD conference on knowledge discovery and …, 2022 | 101 | 2022 |
| Copyright protection in generative ai: A technical perspective J Ren, H Xu, P He, Y Cui, S Zeng, J Zhang, H Wen, J Ding, P Huang, ... arXiv preprint arXiv:2402.02333, 2024 | 76 | 2024 |
| Amazon-m2: A multilingual multi-locale shopping session dataset for recommendation and text generation W Jin, H Mao, Z Li, H Jiang, C Luo, H Wen, H Han, H Lu, Z Wang, R Li, ... Advances in Neural Information Processing Systems 36, 8006-8026, 2023 | 73 | 2023 |
| CellPLM: Pre-training of Cell Language Model Beyond Single Cells H Wen, W Tang, X Dai, J Ding, W Jin, Y Xie, J Tang The Twelfth International Conference on Learning Representations, https …, 2024 | 72* | 2024 |
| Deep learning in single-cell analysis D Molho, J Ding, W Tang, Z Li, H Wen, Y Wang, J Venegas, W Jin, R Liu, ... ACM Transactions on Intelligent Systems and Technology 15 (3), 1-62, 2024 | 42 | 2024 |
| Content knowledge identification with multi-agent large language models (LLMs) K Yang, Y Chu, T Darwin, A Han, H Li, H Wen, Y Copur-Gencturk, J Tang, ... International Conference on Artificial Intelligence in Education, 284-292, 2024 | 28 | 2024 |
| DANCE: a deep learning library and benchmark platform for single-cell analysis J Ding, R Liu, H Wen, W Tang, Z Li, J Venegas, R Su, D Molho, W Jin, ... Genome Biology 25 (1), 72, 2024 | 27* | 2024 |
| Investigating out-of-distribution generalization of gnns: An architecture perspective K Guo, H Wen, W Jin, Y Guo, J Tang, Y Chang Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and …, 2024 | 24 | 2024 |
| Single-cell multimodal prediction via transformers W Tang, H Wen, R Liu, J Ding, W Jin, Y Xie, H Liu, J Tang Proceedings of the 32nd ACM International Conference on Information and …, 2023 | 23 | 2023 |
| Single cells are spatial tokens: Transformers for spatial transcriptomic data imputation H Wen, W Tang, W Jin, J Ding, R Liu, X Dai, F Shi, L Shang, H Liu, Y Xie arXiv preprint arXiv:2302.03038, 2023 | 21 | 2023 |
| Are Large Language Models (LLMs) Good Social Predictors? K Yang, H Li, H Wen, TQ Peng, J Tang, H Liu arXiv preprint arXiv:2402.12620, 2024 | 18 | 2024 |
| Iteralign: Iterative constitutional alignment of large language models X Chen, H Wen, S Nag, C Luo, Q Yin, R Li, Z Li, W Wang arXiv preprint arXiv:2403.18341, 2024 | 16 | 2024 |
| Revisiting the graph reasoning ability of large language models: Case studies in translation, connectivity and shortest path X Dai, Q Wen, Y Shen, H Wen, D Li, J Tang, C Shan arXiv preprint arXiv:2408.09529, 2024 | 13 | 2024 |
| Sreyashi Nag, Chen Luo, Qingyu Yin, Ruirui Li, Zheng Li, and Wei Wang. 2024. ITERALIGN: Iterative Constitutional Alignment of Large Language Models X Chen, H Wen arXiv preprint arXiv:2403.18341, 2024 | 12 | 2024 |
| Learning on graphs with large language models (llms): A deep dive into model robustness K Guo, Z Liu, Z Chen, H Wen, W Jin, J Tang, Y Chang arXiv preprint arXiv:2407.12068, 2024 | 11 | 2024 |
| Exploring the potential of large language models (LLMs) in learning on graph Z Chen, H Mao, H Li, W Jin, H Wen, X Wei, S Wang, D Yin, W Fan, H Liu, ... NeurIPS 2023 Workshop: New Frontiers in Graph Learning, 2023 | 11 | 2023 |
| SpatialCTD: A Large-Scale Tumor Microenvironment Spatial Transcriptomic Dataset to Evaluate Cell Type Deconvolution for Immuno-Oncology J Ding, L Li, Q Lu, J Venegas, Y Wang, L Wu, W Jin, H Wen, R Liu, ... Journal of Computational Biology 31 (9), 871-885, 2024 | 10* | 2024 |
| A general single-cell analysis framework via conditional diffusion generative models W Tang, R Liu, H Wen, X Dai, J Ding, H Li, W Fan, Y Xie, J Tang bioRxiv, 2023.10. 13.562243, 2023 | 10 | 2023 |
