| Clip-adapter: Better vision-language models with feature adapters P Gao*, S Geng*, R Zhang*, T Ma, R Fang, Y Zhang, H Li, Y Qiao International Journal of Computer Vision, 2024 | 1015 | 2024 |
| Llama-adapter v2: Parameter-efficient visual instruction model P Gao, J Han, R Zhang, Z Lin, S Geng, A Zhou, W Zhang, P Lu, C He, ... arXiv preprint arXiv:2304.15010, 2023 | 532 | 2023 |
| Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5) S Geng, S Liu, Z Fu, Y Ge, Y Zhang RecSys 2022, 2022 | 480 | 2022 |
| Fairness-aware explainable recommendation over knowledge graphs Z Fu, Y Xian, R Gao, J Zhao, Q Huang, Y Ge, S Xu, S Geng, C Shah, ... Proceedings of the 43rd international ACM SIGIR conference on research and …, 2020 | 258 | 2020 |
| Frozen clip models are efficient video learners Z Lin, S Geng, R Zhang, P Gao, G de Melo, X Wang, J Dai, Y Qiao, H Li ECCV 2022, 2022 | 238 | 2022 |
| Quantized densely connected u-nets for efficient landmark localization Z Tang, X Peng, S Geng, L Wu, S Zhang, D Metaxas Proceedings of the European conference on computer vision (ECCV), 339-354, 2018 | 164 | 2018 |
| Learning and evaluating graph neural network explanations based on counterfactual and factual reasoning J Tan, S Geng, Z Fu, Y Ge, S Xu, Y Li, Y Zhang Proceedings of the ACM web conference 2022, 1018-1027, 2022 | 135 | 2022 |
| Image segmentation with pyramid dilated convolution based on ResNet and U-Net Q Zhang, Z Cui, X Niu, S Geng, Y Qiao Neural Information Processing: 24th International Conference, ICONIP 2017 …, 2017 | 126 | 2017 |
| CAFE: Coarse-to-fine neural symbolic reasoning for explainable recommendation Y Xian, Z Fu, H Zhao, Y Ge, X Chen, Q Huang, S Geng, Z Qin, G De Melo, ... Proceedings of the 29th ACM International Conference on Information …, 2020 | 109 | 2020 |
| SPHINX-X: Scaling Data and Parameters for a Family of Multi-modal Large Language Models D Liu, R Zhang, L Qiu, S Huang, W Lin, S Zhao, S Geng, Z Lin, P Jin, ... ICML 2024, 2024 | 99 | 2024 |
| Path language modeling over knowledge graphsfor explainable recommendation S Geng, Z Fu, J Tan, Y Ge, G De Melo, Y Zhang Proceedings of the ACM web conference 2022, 946-955, 2022 | 90 | 2022 |
| Explainable Fairness in Recommendation Y Ge, J Tan, Y Zhu, Y Xia, J Luo, S Liu, Z Fu, S Geng, Z Li, Y Zhang SIGIR 2022, 2022 | 73 | 2022 |
| VIP5: Towards Multimodal Foundation Models for Recommendation S Geng, J Tan, S Liu, Z Fu, Y Zhang Findings of the Association for Computational Linguistics: EMNLP 2023, 2023 | 69 | 2023 |
| Dynamic graph representation learning for video dialog via multi-modal shuffled transformers S Geng, P Gao, M Chatterjee, C Hori, J Le Roux, Y Zhang, H Li, A Cherian Proceedings of the AAAI Conference on Artificial Intelligence 35 (2), 1415-1423, 2021 | 59* | 2021 |
| Lumina-T2X: Scalable Flow-based Large Diffusion Transformer for Flexible Resolution Generation P Gao, L Zhuo, D Liu, R Du, X Luo, L Qiu, Y Zhang, R Huang, S Geng, ... ICLR 2025 (Spotlight), 2025 | 56* | 2025 |
| Cu-net: Coupled u-nets Z Tang, X Peng, S Geng, Y Zhu, DN Metaxas BMVC 2018, 2018 | 55 | 2018 |
| Unleashing the Potential of Vision-Language Models for Long-Tailed Visual Recognition T Ma, S Geng, M Wang, S Xu, H Li, B Zhang, P Gao, Y Qiao BMVC 2022, 2022 | 50* | 2022 |
| HiCLIP: Contrastive Language-Image Pretraining with Hierarchy-aware Attention S Geng, J Yuan, Y Tian, Y Chen, Y Zhang ICLR 2023, 2023 | 47 | 2023 |
| Hierarchically Self-supervised Transformer for Human Skeleton Representation Learning Y Chen, L Zhao, J Yuan, Y Tian, Z Xia, S Geng, L Han, DN Metaxas ECCV 2022, 2022 | 42 | 2022 |
| Revisiting multimodal representation in contrastive learning: from patch and token embeddings to finite discrete tokens Y Chen, J Yuan, Y Tian, S Geng, X Li, D Zhou, DN Metaxas, H Yang CVPR 2023, 2023 | 37 | 2023 |
