Summary of Revisiting Neural Networks For Continual Learning: An Architectural Perspective, by Aojun Lu et al.
Revisiting Neural Networks for Continual Learning: An Architectural Perspectiveby Aojun Lu, Tao Feng, Hangjie Yuan,…
Summary of Brain-inspired Continual Learning-robust Feature Distillation and Re-consolidation For Class Incremental Learning, by Hikmat Khan et al.
Brain-Inspired Continual Learning-Robust Feature Distillation and Re-Consolidation for Class Incremental Learningby Hikmat Khan, Nidhal Carla…
Summary of I2cansay:inter-class Analogical Augmentation and Intra-class Significance Analysis For Non-exemplar Online Task-free Continual Learning, by Songlin Dong et al.
I2CANSAY:Inter-Class Analogical Augmentation and Intra-Class Significance Analysis for Non-Exemplar Online Task-Free Continual Learningby Songlin Dong,…
Summary of Fedmes: Personalized Federated Continual Learning Leveraging Local Memory, by Jin Xie et al.
FedMeS: Personalized Federated Continual Learning Leveraging Local Memoryby Jin Xie, Chenqing Zhu, Songze LiFirst submitted…
Summary of Data-incremental Continual Offline Reinforcement Learning, by Sibo Gai and Donglin Wang
Data-Incremental Continual Offline Reinforcement Learningby Sibo Gai, Donglin WangFirst submitted to arxiv on: 19 Apr…
Summary of Graph Continual Learning with Debiased Lossless Memory Replay, by Chaoxi Niu et al.
Graph Continual Learning with Debiased Lossless Memory Replayby Chaoxi Niu, Guansong Pang, Ling ChenFirst submitted…
Summary of Towards Practical Tool Usage For Continually Learning Llms, by Jerry Huang et al.
Towards Practical Tool Usage for Continually Learning LLMsby Jerry Huang, Prasanna Parthasarathi, Mehdi Rezagholizadeh, Sarath…
Summary of E3: Ensemble Of Expert Embedders For Adapting Synthetic Image Detectors to New Generators Using Limited Data, by Aref Azizpour et al.
E3: Ensemble of Expert Embedders for Adapting Synthetic Image Detectors to New Generators Using Limited…
Summary of Cem: a Data-efficient Method For Large Language Models to Continue Evolving From Mistakes, by Haokun Zhao and Haixia Han and Jie Shi and Chengyu Du and Jiaqing Liang and Yanghua Xiao
CEM: A Data-Efficient Method for Large Language Models to Continue Evolving From Mistakesby Haokun Zhao,…
Summary of Adapterswap: Continuous Training Of Llms with Data Removal and Access-control Guarantees, by William Fleshman et al.
AdapterSwap: Continuous Training of LLMs with Data Removal and Access-Control Guaranteesby William Fleshman, Aleem Khan,…