Related papers: Ira: Efficient Transaction Replay for Distributed …
Caches are used to reduce the speed differential between the CPU and memory to improve the performance of modern processors. However, attackers can use contention-based cache timing attacks to steal sensitive information from victim…
Nakamoto's seminal work gave rise to permissionless blockchains -- as well as a wide range of proposals to mitigate their performance shortcomings. Despite substantial throughput and energy efficiency achievements, most proposals only bring…
Decentralized Identifiers (DIDs) are increasingly deployed on distributed ledgers, yet systematic cross-platform evidence on their operational behavior remains limited. We present an empirical benchmarking study of three prominent…
Each LLM serving request goes through two phases. The first is prefill which processes the entire input prompt and produces the first output token and the second is decode which generates the rest of output tokens, one-at-a-time. Prefill…
Recent advancements in LLM post-training, particularly through reinforcement learning and preference optimization, are key to boosting their reasoning capabilities. However, these methods often suffer from low sample efficiency and a…
A rollup network is a type of popular "Layer 2" scaling solution for general purpose "Layer 1" blockchains like Ethereum. Rollups networks separate execution of transactions from other aspects like consensus, processing transactions off of…
Reinforcement Learning (RL) struggles in problems with delayed rewards, and one approach is to segment the task into sub-tasks with incremental rewards. We propose a framework called Hierarchical Inverse Reinforcement Learning (HIRL), which…
In recent years, effectively modeling multivariate time series has gained significant popularity, mainly due to its wide range of applications, ranging from healthcare to financial markets and energy management. Transformers, MLPs, and…
Parameter-efficient fine-tuning (PEFT) methods, such as LoRA, reduce adaptation cost by injecting low-rank updates into pretrained weights. However, LoRA's down-projection is randomly initialized and data-agnostic, discarding potentially…
Proto-Danksharding, proposed in Ethereum Improvement Proposal 4844 (EIP-4844), aims to incrementally improve the scalability of the Ethereum blockchain by introducing a new type of transaction known as blob-carrying transactions. These…
One of the main bottlenecks of blockchains is smart contract execution. To increase throughput, modern blockchains try to execute transactions in parallel. Unfortunately, however, common blockchain use cases introduce read-write conflicts…
Blockchain platforms such as Ethereum and several others execute complex transactions in blocks through user-defined scripts known as smart contracts. To append a correct block into blockchain, miners execute these transactions of smart…
The emergence of blockchain technology has renewed the interest in consensus-based data management systems that are resilient to failures. To maximize the throughput of these systems, we have recently seen several prototype consensus…
Multi-Head Attention (MHA) is the core computational primitive underlying modern Large Language Models (LLMs). However, MHA suffers from a fundamental linear scaling limitation: $H$ attention heads produce exactly $H$ independent attention…
Blockchains such as Bitcoin and Ethereum execute payment transactions securely, but their performance is limited by the need for global consensus. Payment networks overcome this limitation through off-chain transactions. Instead of writing…
State-of-the-art \emph{software transactional memory (STM)} implementations achieve good performance by carefully avoiding the overhead of \emph{incremental validation} (i.e., re-reading previously read data items to avoid inconsistency)…
In today's blockchain system, designing a secure and high throughput blockchain on par with a centralized payment system is a difficult task. Sharding is one of the most worthwhile emerging technologies for improving the system throughput…
Ethereum's current Gasper consensus mechanism, which combines the Latest Message Driven Greediest Heaviest Observed SubTree (LMD-GHOST) fork choice rule with the probabilistic Casper the Friendly Finality Gadget (FFG) finality overlay,…
Even though reinforcement-learning-based algorithms achieved superhuman performance in many domains, the field of robotics poses significant challenges as the state and action spaces are continuous, and the reward function is predominantly…
The recent surge in federated data management applications has brought forth concerns about the security of underlying data and the consistency of replicas in the presence of malicious attacks. A prominent solution in this direction is to…