Jinda Lu

According to our database, Jinda Lu authored at least 17 papers between 2023 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Interventional Feature Generation for Few-shot Learning.

Shuo Wang, Jinda Lu, Huixia Ben, Yanbin Hao, Xingyu Gao, Meng Wang

ACM Trans. Multim. Comput. Commun. Appl., June, 2025

Recursive Offloading for LLM Serving in Multi-tier Networks.

Zhiyuan Wu, Sheng Sun, Yuwei Wang, Min Liu, Bo Gao, Jinda Lu, Zheming Yang, Tian Wen

CoRR, May, 2025

AdaViP: Aligning Multi-modal LLMs via Adaptive Vision-enhanced Preference Optimization.

Jinda Lu, Jinghan Li, Yuan Gao, Junkang Wu, Jiancan Wu, Xiang Wang, Xiangnan He

CoRR, April, 2025

Aligning Multimodal LLM with Human Preference: A Survey.

Tao Yu, Yifan Zhang, Chaoyou Fu, Junkang Wu, Jinda Lu, Kun Wang, Xingyu Lu, Yunhang Shen, Guibin Zhang, Dingjie Song, Yibo Yan, Tianlong Xu, Qingsong Wen, Zhang Zhang, Yan Huang, Liang Wang, Tieniu Tan

CoRR, March, 2025

Accelerating Diffusion Transformer via Gradient-Optimized Cache.

Junxiang Qiu, Lin Liu, Shuo Wang, Jinda Lu, Kezhou Chen, Yanbin Hao

CoRR, March, 2025

DAMA: Data- and Model-aware Alignment of Multi-modal LLMs.

Jinda Lu, Junkang Wu, Jinghan Li, Xiaojun Jia, Shuo Wang, Yifan Zhang, Junfeng Fang, Xiang Wang, Xiangnan He

CoRR, February, 2025

Accelerating Diffusion Transformer via Error-Optimized Cache.

Junxiang Qiu, Shuo Wang, Jinda Lu, Lin Liu, Houcheng Jiang, Yanbin Hao

CoRR, January, 2025

Multimodal Generation with Consistency Transferring.

Junxiang Qiu, Jinda Lu, Shuo Wang

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2025, Albuquerque, New Mexico, USA, April 29, 2025

DiffGAD: A Diffusion-based Unsupervised Graph Anomaly Detector.

Jinghan Li, Yuan Gao, Jinda Lu, Junfeng Fang, Congcong Wen, Hui Lin, Xiang Wang

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Unified Parameter-Efficient Unlearning for LLMs.

Chenlu Ding, Jiancan Wu, Yancheng Yuan, Jinda Lu, Kai Zhang, Alex Su, Xiang Wang, Xiangnan He

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

FedCache: A Knowledge Cache-Driven Federated Learning Architecture for Personalized Edge Intelligence.

Zhiyuan Wu, Sheng Sun, Yuwei Wang, Min Liu, Ke Xu, Wen Wang, Xuefeng Jiang, Bo Gao, Jinda Lu

IEEE Trans. Mob. Comput., October, 2024

Feature Mixture on Pre-Trained Model for Few-Shot Learning.

Shuo Wang, Jinda Lu, Haiyang Xu, Yanbin Hao, Xiangnan He

IEEE Trans. Image Process., 2024

Rethinking Visual Content Refinement in Low-Shot CLIP Adaptation.

Jinda Lu, Shuo Wang, Yanbin Hao, Haifeng Liu, Xiang Wang, Meng Wang

CoRR, 2024

Modality-Guided Collaborative Filtering for Recommendation.

Kai Zhang, Linping Gao, Jinda Lu, Yutong Yuan, Xiaofen Xing

Proceedings of the Advanced Intelligent Computing Technology and Applications, 2024

GLCM-Adapter: Global-Local Content Matching for Few-shot CLIP Adaptation.

Shuo Wang, Xieenlong, Jinda Lu, Jinghan Li, Yanbin Hao

Proceedings of the 35th British Machine Vision Conference, 2024

Boosting Few-Shot Learning via Attentive Feature Regularization.

Xingyu Zhu, Shuo Wang, Jinda Lu, Yanbin Hao, Haifeng Liu, Xiangnan He

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Semantic-based Selection, Synthesis, and Supervision for Few-shot Learning.

Jinda Lu, Shuo Wang, Xinyu Zhang, Yanbin Hao, Xiangnan He

Proceedings of the 31st ACM International Conference on Multimedia, 2023