Summary of In-context Symmetries: Self-supervised Learning Through Contextual World Models, by Sharut Gupta et al.
In-Context Symmetries: Self-Supervised Learning through Contextual World Modelsby Sharut Gupta, Chenyu Wang, Yifei Wang, Tommi…
In-Context Symmetries: Self-Supervised Learning through Contextual World Modelsby Sharut Gupta, Chenyu Wang, Yifei Wang, Tommi…
Delving into Differentially Private Transformerby Youlong Ding, Xueyang Wu, Yining Meng, Yonggang Luo, Hao Wang,…
IM-Context: In-Context Learning for Imbalanced Regression Tasksby Ismail Nejjar, Faez Ahmed, Olga FinkFirst submitted to…
Trustworthy DNN Partition for Blockchain-enabled Digital Twin in Wireless IIoT Networksby Xiumei Deng, Jun Li,…
Cost-Sensitive Multi-Fidelity Bayesian Optimization with Transfer of Learning Curve Extrapolationby Dong Bok Lee, Aoxuan Silvia…
The Evolution of Multimodal Model Architecturesby Shakti N. Wadekar, Abhishek Chaurasia, Aman Chadha, Eugenio CulurcielloFirst…
Online Merging Optimizers for Boosting Rewards and Mitigating Tax in Alignmentby Keming Lu, Bowen Yu,…
Towards Communication-efficient Federated Learning via Sparse and Aligned Adaptive Optimizationby Xiumei Deng, Jun Li, Kang…
RC-Mixup: A Data Augmentation Strategy against Noisy Data for Regression Tasksby Seong-Hyeon Hwang, Minsu Kim,…
Efficient Prior Calibration From Indirect Databy O. Deniz Akyildiz, Mark Girolami, Andrew M. Stuart, Arnaud…