3 citations · 5 across the 5 of their papers we have counts for
6 papers
Knowledge-Free Correlated Agreement for Incentivizing Federated Learning
Leon Witt, Togrul Abbasli, Kentaroh Toyoda +2
We introduce Knowledge-Free Correlated Agreement (KFCA) to reward client contributions in federated learning (FL) without relying on ground truth, a public test set, or distributio…
Democratizing Federated Learning with Blockchain and Multi-Task Peer Prediction
Leon Witt, Kentaroh Toyoda, Wojciech Samek +1
The synergy between Federated Learning and blockchain has been considered promising; however, the computationally intensive nature of contribution measurement conflicts with the st…
Quasi-Orthogonality and Polysemy: The Limits of Quantum Analogy in Large Language Models
Karl Svozil
We analyze two geometric aspects of meaning-sensitive behavior in next-token models. First, high-dimensional geometry permits exponentially many nearly orthogonal feature direction…
Blockchain and Artificial Intelligence: Synergies and Conflicts
Leon Witt, Armando Teles Fortes, Kentaroh Toyoda +2
Blockchain technology and Artificial Intelligence (AI) have emerged as transformative forces in their respective domains. This paper explores synergies and challenges between these…
Decentral and Incentivized Federated Learning Frameworks: A Systematic Literature Review
Leon Witt, Mathis Heyer, Kentaroh Toyoda +2
The advent of Federated Learning (FL) has ignited a new paradigm for parallel and confidential decentralized Machine Learning (ML) with the potential of utilizing the computational…
Reward-Based 1-bit Compressed Federated Distillation on Blockchain
Leon Witt, Usama Zafar, KuoYeh Shen +3
The recent advent of various forms of Federated Knowledge Distillation (FD) paves the way for a new generation of robust and communication-efficient Federated Learning (FL), where…