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 | 893 | 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 | 494 | 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 | 440 | 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 | 252 | 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 | 216 | 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 | 162 | 2018 |
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 | 123 | 2017 |
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 | 117 | 2022 |
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 |
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 | 86 | 2022 |
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 | 82 | 2024 |
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 | 69 | 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 | 66 | 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 | 57* | 2021 |
Cu-net: Coupled u-nets Z Tang, X Peng, S Geng, Y Zhu, DN Metaxas BMVC 2018, 2018 | 54 | 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 | 45* | 2022 |
HiCLIP: Contrastive Language-Image Pretraining with Hierarchy-aware Attention S Geng, J Yuan, Y Tian, Y Chen, Y Zhang ICLR 2023, 2023 | 44 | 2023 |
COMPOSER: Compositional Reasoning of Group Activity in Videos with Keypoint-Only Modality H Zhou, A Kadav, A Shamsian, S Geng, F Lai, L Zhao, T Liu, M Kapadia, ... ECCV 2022, 2022 | 44 | 2022 |
Lumina-T2X: Transforming Text into Any Modality, Resolution, and Duration via Flow-based Large Diffusion Transformers P Gao, L Zhuo, D Liu, R Du, X Luo, L Qiu, Y Zhang, C Lin, R Huang, ... arXiv preprint arXiv:2405.05945, 2024 | 41* | 2024 |
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 | 36 | 2022 |