10 papers
Diffusion LLMs as Targets and Adversaries: Mechanistic Safety Exploits
Elena Dumitrescu, Gert Lek, Lydia Y. Chen +1
Diffusion Large Language Models (DLLMs) replace autoregressive next-token prediction with iterative parallel denoising, yet their internal safety mechanisms remain poorly understoo…
Robust and Automated Reconfiguration of Byzantine Wide-Area Replication
Rowdy Chotkan, Bulat Nasrulin, Johan Pouwelse +1
Distributed systems handle adversarial nodes through redundancy, which imposes a significant performance overhead. In blockchain systems, Byzantine fault-tolerant state-machine rep…
Dynamic Topology Optimization for Non-IID Data in Decentralized Learning
Bart Cox, Antreas Ioannou, Jérémie Decouchant
Decentralized learning (DL) enables a set of nodes to train a model collaboratively without central coordination, offering benefits for privacy and scalability. However, DL struggl…
Balancing Fairness and Performance in Multi-User Spark Workloads with Dynamic Scheduling (extended version)
DÄvis Kažemaks, Laurens Versluis, Burcu Kulahcioglu Ozkan +1
Apache Spark is a widely adopted framework for large-scale data processing. However, in industrial analytics environments, Spark's built-in schedulers, such as FIFO and fair schedu…
NEMO: Faster Parallel Execution for Highly Contended Blockchain Workloads (Full version)
François Ezard, Can Umut Ileri, Jérémie Decouchant
Following the design of more efficient blockchain consensus algorithms, the execution layer has emerged as the new performance bottleneck of blockchains, especially under high cont…
StarveSpam: Mitigating Spam with Local Reputation in Permissionless Blockchains
Rowdy Chotkan, Bulat Nasrulin, Jérémie Decouchant +1
Spam poses a growing threat to blockchain networks. Adversaries can easily create multiple accounts to flood transaction pools, inflating fees and degrading service quality. Existi…