11 citations · 29 across the 19 of their papers we have counts for
19 papers
Adaptive Adapter Routing for Long-Tailed Class-Incremental Learning
Zhi-Hong Qi, Da-Wei Zhou, Yiran Yao +2
In our ever-evolving world, new data exhibits a long-tailed distribution, such as e-commerce platform reviews. This necessitates continuous model learning imbalanced data without f…
Weight Scope Alignment: A Frustratingly Easy Method for Model Merging
Yichu Xu, Xin-Chun Li, Le Gan +1
Merging models becomes a fundamental procedure in some applications that consider model efficiency and robustness. The training randomness or Non-I.I.D. data poses a huge challenge…
Leveraging Cross-Modal Neighbor Representation for Improved CLIP Classification
Chao Yi, Lu Ren, De-Chuan Zhan +1
CLIP showcases exceptional cross-modal matching capabilities due to its training on image-text contrastive learning tasks. However, without specific optimization for unimodal scena…
TV100: A TV Series Dataset that Pre-Trained CLIP Has Not Seen
Da-Wei Zhou, Zhi-Hong Qi, Han-Jia Ye +1
The era of pre-trained models has ushered in a wealth of new insights for the machine learning community. Among the myriad of questions that arise, one of paramount importance is:…
MAP: Model Aggregation and Personalization in Federated Learning with Incomplete Classes
Xin-Chun Li, Shaoming Song, Yinchuan Li +4
In some real-world applications, data samples are usually distributed on local devices, where federated learning (FL) techniques are proposed to coordinate decentralized clients wi…
SENSOR: Imitate Third-Person Expert's Behaviors via Active Sensoring
Kaichen Huang, Minghao Shao, Shenghua Wan +4
In many real-world visual Imitation Learning (IL) scenarios, there is a misalignment between the agent's and the expert's perspectives, which might lead to the failure of imitation…