Summary of Fedbaf: Federated Learning Aggregation Biased by a Foundation Model, By Jong-ik Park et al.
FedBaF: Federated Learning Aggregation Biased by a Foundation Modelby Jong-Ik Park, Srinivasa Pranav, José M.…
FedBaF: Federated Learning Aggregation Biased by a Foundation Modelby Jong-Ik Park, Srinivasa Pranav, José M.…
Beyond Position: the emergence of wavelet-like properties in Transformersby Valeria Ruscio, Fabrizio SilvestriFirst submitted to…
ALTA: Compiler-Based Analysis of Transformersby Peter Shaw, James Cohan, Jacob Eisenstein, Kenton Lee, Jonathan Berant,…
R2Gen-Mamba: A Selective State Space Model for Radiology Report Generationby Yongheng Sun, Yueh Z. Lee,…
Federated Transformer: Multi-Party Vertical Federated Learning on Practical Fuzzily Linked Databy Zhaomin Wu, Junyi Hou,…
Entity-based Reinforcement Learning for Autonomous Cyber Defenceby Isaac Symes Thompson, Alberto Caron, Chris Hicks, Vasilios…
PETAH: Parameter Efficient Task Adaptation for Hybrid Transformers in a resource-limited Contextby Maximilian Augustin, Syed…
Anomaly Resilient Temporal QoS Prediction using Hypergraph Convoluted Transformer Networkby Suraj Kumar, Soumi Chattopadhyay, Chandranath…
Faster Language Models with Better Multi-Token Prediction Using Tensor Decompositionby Artem Basharin, Andrei Chertkov, Ivan…
Which Client is Reliable?: A Reliable and Personalized Prompt-based Federated Learning for Medical Image Question…