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cs.DC updates on arXiv.org

DUAL-BLADE: Dual-Path NVMe-Direct KV-Cache Offloading for Edge LLM Inference Progressive Semantic Communication for Efficient Edge-Cloud Vision-Language Models Efficient, VRAM-Constrained xLM Inference on Clients Folding Tensor and Sequence Parallelism for Memory-Efficient Transformer Training & Inference DORA: A Scalable Asynchronous Reinforcement Learning System for Language Model Training AMMA: A Multi-Chiplet Memory-Centric Architecture for Low-Latency 1M Context Attention Serving RaMP: Runtime-Aware Megakernel Polymorphism for Mixture-of-Experts Spark Policy Toolkit: Semantic Contracts and Scalable Execution for Policy Learning in Spark Internet of Everything in the 6G Era: Paradigms, Enablers, Potentials and Future Directions PolyKV: A Shared Asymmetrically-Compressed KV Cache Pool for Multi-Agent LLM Inference A Survey on Split Learning for LLM Fine-Tuning: Models, Systems, and Privacy Optimizations ITAS: A Multi-Agent Architecture for LLM-Based Intelligent Tutoring Latency and Cost of Multi-Agent Intelligent Tutoring at Scale TACO: Efficient Communication Compression of Intermediate Tensors for Scalable Tensor-Parallel LLM Training FreeScale: Distributed Training for Sequence Recommendation Models with Minimal Scaling Cost CommFuse: Hiding Tail Latency via Communication Decomposition and Fusion for Distributed LLM Training A Taxonomy and Resolution Strategy for Client-Level Disagreements in Federated Learning Usable Agent Discovery for Decentralized AI Systems Cloud to Edge: Benchmarking LLM Inference On Hardware-Accelerated Single-Board Computers Data-Free Contribution Estimation in Federated Learning using Gradient von Neumann Entropy Shard the Gradient, Scale the Model: Serverless Federated Aggregation via Gradient Partitioning Promoting Simple Agents: Ensemble Methods for Event-Log Prediction GraphLeap: Decoupling Graph Construction and Convolution for Vision GNN Acceleration on FPGA AGNT2: Autonomous Agent Economies on Interaction-Optimized Layer 2 Infrastructure FedSIR: Spectral Client Identification and Relabeling for Federated Learning with Noisy Labels Stream-CQSA: Avoiding Out-of-Memory in Attention Computation via Flexible Workload Scheduling A Delta-Aware Orchestration Framework for Scalable Multi-Agent Edge Computing Federated Learning over Blockchain-Enabled Cloud Infrastructure Optimal Routing for Federated Learning over Dynamic Satellite Networks: Tractable or Not? Sherpa.ai Privacy-Preserving Multi-Party Entity Alignment without Intersection Disclosure for Noisy Identifiers
Democratic Value and Money for Decentralized Digital Society
Bryan Ford · 2020-03-26 · via cs.DC updates on arXiv.org

Classical monetary systems regularly subject the most vulnerable majority of the world's population to debilitating financial shocks, and have manifestly allowed uncontrolled global inequality over the long term. Given these basic failures, how can we avoid asking whether mainstream macroeconomic principles are actually compatible with democratic principles such as equality or the protection of human rights and dignity? This idea paper takes a constructive look at this question, by exploring how alternate monetary principles might result in a form of money more compatible with democratic principles -- dare we call it "democratic money"? In this alternative macroeconomic philosophy, both the supply of and the demand for money must be rooted in people, so as to give all people both equal opportunities for economic participation. Money must be designed around equality, not only across all people alive at a given moment, but also across past and future generations of people, guaranteeing that our descendants cannot be enslaved by their ancestors' economic luck or misfortune. Democratic money must reliably give all people a means to enable everyday commerce, investment, and value creation in good times and bad, and must impose hard limits on financial inequality. Democratic money must itself be governed democratically, and must economically facilitate the needs of citizens in a democracy for trustworthy and unbiased information with which to make wise collective decisions. An intriguing approach to implementing and deploying democratic money is via a cryptocurrency built on a proof-of-personhood foundation, giving each opt-in human participant one equal unit of stake. Such a cryptocurrency would have both interesting similarities to, and important differences from, a Universal Basic Income (UBI) denominated in an existing currency.