Ethereum transition to PoS reduces energy consumption and decentralizes the network.
problem Transitioning from proof-of-work to proof-of-stake to reduce energy consumption and decentralize the network.
method Analyzed the impact of the Ethereum transition to proof-of-stake on network performance, competing platforms, and transaction fees.
result The transition to PoS has reduced energy consumption by 99.98% and decreased network concentration.
DeFi lending protocols faced challenges during Ethereum's merge, but avoided major liquidations.
problem Ethereum's merge caused volatility and potential liquidations in DeFi lending.
method Analyzed AAVE and Compound lending protocols during the merge and hard fork.
result Borrowing rates spiked but no significant liquidations occurred.
Non-atomic arbitrage exploits price differences on Ethereum and other blockchains, accounting for over 10% of Ethereum's block value.
problem Price differences on decentralized exchanges and centralized exchanges lead to MEV.
method Analyzed non-atomic arbitrage on Ethereum's largest DEXes, identifying its prevalence and impact.
result More than 10% of Ethereum's block value is attributed to non-atomic arbitrage, involving over $132 billion.
Ethereum's Pectra upgrade introduces 0x02 compounding validators, offering higher stake and potential APR uplifts.
problem Staking rewards on Ethereum
method Analyzing compounding effects on consensus-layer rewards
result 0x02 validators achieve modestly higher median CL APR
Ethereum tackles bribery in blockchain transactions with new fee mechanism.
problem Bribing miners in Ethereum blockchain to manipulate transaction fees.
method Filtered transactions, constructed proxies for bribery level, analyzed effects on blockchain and financial markets.
result Bribing affects Ethereum and other blockchains, influencing cryptocurrency, transaction stats, and network adoption.
The paper assesses dimensionality reduction for cryptocurrency link prediction.
problem Establishing a link between cryptocurrencies using dimensionality reduction techniques.
method Used canonical correlation analysis and principal component analysis on log returns and covariates of Bitcoin and Ethereum.
result Performance of dimensionality reduction techniques in forecasting Ethereum returns with Bitcoin features.
Study compares Bitcoin and Ethereum tail behavior using Q-Q plots.
problem Examining tail risk in cryptocurrency returns.
method Used Q-Q plots and Generalized Tempered Stable (GTS) distribution.
result Ethereum shows more extreme values than Bitcoin, indicating greater tail risk.
Research examines how strategic latency manipulation impacts Ethereum's network efficiency and decentralization.
problem Impact of artificial latency on Ethereum's network efficiency and decentralization.
method Comprehensive analysis of MEV-Boost auction system and empirical validation with a pilot.
result Increased profitability for node operators and significant systemic challenges like heightened network inefficiencies and centralization risks.
This paper analyzes Ethereum's gas fees and their derivatives, providing a comprehensive model.
problem Understanding and predicting gas fees on the Ethereum blockchain.
method Analyzed Ethereum's gas fee structure and used a fractional Ornstein-Uhlenbeck process to model gas prices.
result A model for pricing and trading gas fee derivatives to hedge against volatility.
Ethereum trends analyzed through blockchain transactions and Google searches.
problem Identifying market manipulation in crypto prices.
method Big data analysis of Ethereum transactions, smart contracts, and search volumes.
result Big players manipulate crypto markets after price drops.
Transformer predicts Ethereum prices using cross-currency correlation and sentiment analysis.
problem Predicting Ethereum cryptocurrency prices with limited data.
method Transformer-based neural network with cross-currency correlation and sentiment analysis.
result Transformer model outperforms other models on some parameters.
Panoptic trades options without oracles on Ethereum.
problem Trading options without relying on oracles.
method Perpetual, trustless, instant-settlement protocol on Ethereum.
result Trustless, permissionless trading of options on Uniswap v3.
Maker Protocol manages Dai stable coin on Ethereum blockchain.
problem Managing decentralized finance applications on blockchain.
method Analyzes Maker Protocol's components and governance.
result Maker Protocol is a significant decentralized finance application.
Faster Ethereum slots boost CEX-DEX arbitrage by 535% and 203%.
problem Reducing Ethereum slot time impacts CEX-DEX arbitrage opportunities.
method Developed a trading model to simulate and compare agent behavior under different slot times.
result Faster slot times increase CEX-DEX arbitrage activity and returns.
Ethereum upgrades increased TPS and lowered fees, with L2s surpassing Solana in 2029.
problem Transaction speed and fees in Ethereum
method Comparing Ethereum Mainnet and Layer 2 networks, Solana, and Polygon
result Ethereum Mainnet and L2 networks surpassed Solana in terms of TPS and lowered fees
Ethereum block builders can earn up to $14M/month by reordering transactions, harming users.
problem Block builders can exploit transaction reordering to earn significant profits, harming users.
method Estimation of MEV payments and analysis of reordering effects.
result Block builders can earn up to $14M/month by reordering transactions, skewing the distribution.
Study examines revenue from scam tokens on Ethereum, revealing key characteristics and market factors.
problem Revenue from scam tokens on Ethereum blockchain.
method Empirical analysis of Uniswap, examining characteristics and market factors.
result Revenue from scam tokens is influenced by market economic factors and community engagement.
SVAR-LiNGAM reveals causal order in crypto-asset markets.
problem Understanding the causal relationships between spot rates and crypto-assets.
method Applied SVAR-LiNGAM to analyze spot exchange rates and crypto-asset exchange rates.
result Causal order found: EUR_USD spot rate -> Bitcoin -> Ethereum -> Ripple.
TLMG4Eth combines language and graph models for Ethereum fraud detection.
problem Current fraud detection methods fail to consider semantic and similarity patterns in Ethereum transactions.
method TLMG4Eth uses a transaction language model and graph-based methods to capture semantic, similarity, and structural features.
result TLMG4Eth detects anomalies in Ethereum transactions more effectively than existing methods.
Enhances Ponzi scheme detection on Ethereum using time-aware metapaths.
problem Lack of temporal information in heterogeneous transaction graphs.
method Time-aware Metapath Feature Augmentation (TMFAug) module.
result Significant performance improvements in Ponzi scheme detection.
This study evaluates Algorand and Ethereum 2.0 for blockchain trilemma challenges.
problem Balancing decentralization, security, and scalability in blockchain systems.
method Comparative analysis of Algorand and Ethereum 2.0 using metrics for decentralization, scalability, and security.
result Each system has strengths in addressing the blockchain trilemma, providing insights for other blockchain technologies.
Blockchain technology and, in particular, blockchain-based cryptocurrencies offer us information that has never been seen before in the financial world. In contrast to fiat currencies, all transactions of crypto-currencies and crypto-tokens are permanently recorded on distributed ledgers and are publicly available. As …
LEWIS merges LLMs without training, improving performance on specific tasks.
problem Limited performance improvement of merged models on specific benchmarks.
method Guided model merging using layer-wise sparsity and task-vector pruning.
result Improved model performance by up to 11.3% on math-solving tasks.
This study evaluates price improvements in order flow auctions on Ethereum.
problem Improving trading outcomes in blockchain-based trading platforms.
method Utilized open-source tools to attribute price improvements to specific system inputs.
result Auction-enhanced interfaces can provide statistically significant improvements in trading outcomes, averaging 4-5 basis points.
The paper analyzes CEX-DEX arbitrage and profitability on Ethereum, revealing centralization trends and market impacts.
problem Ethereum's decentralization and CEX-DEX arbitrages.
method Empirical analysis of 19 months' data from 7.2M CEX-DEX transactions, refining heuristics to identify and estimate arbitrage revenue.
result Three searchers captured three-quarters of volume and extracted value, and profitability is tied to integration with block builders.
Study finds Aave token network has core-periphery structure, with high decentralization predicting better returns.
problem Understanding the actual decentralization in DeFi token transactions on the Ethereum blockchain.
method Applied social network analysis to measure decentralization in Aave token transactions.
result A more decentralized Aave token network predicts higher returns and lower volatility.
SLEID detects illicit accounts in DeFi transactions using semi-supervised learning.
problem Detecting illicit accounts in DeFi transactions with scarce labeled data.
method SLEID uses Isolation Forest for initial detection and self-training for pseudo-labels.
result SLEID outperforms baselines with significant improvements in precision and accuracy.
Study shows training duration impacts model merging quality, suggesting joint selection of duration and method.
problem Impact of expert training duration on model merging quality for large language models (LLMs).
method Systematically fine-tuned experts on five domains across three model sizes, evaluating five merging methods at each duration.
result Training duration affects merging quality, with simple averaging degrading sharply and sparsification-based methods performing well past the validation optimum.
Study shows training duration affects model merging quality, suggesting joint selection of duration and method.
problem Impact of expert training duration on model merging quality for large language models (LLMs).
method Systematically fine-tuned experts on five domains across three model sizes, evaluated five merging methods at each duration.
result Training duration and merging method should be chosen jointly, not independently.
Paper improves transaction-based Ponzi detection on Ethereum.
problem Low accuracy of current transaction-based Ponzi detection models.
method Employ time-series features to improve accuracy.
result Up to 30% higher F1-scores achieved with new features.
EpiMer merges models by solving Fréchet mean on a Riemannian manifold.
problem Integrating knowledge from multiple models without retraining.
method EpiMer casts model merging as solving the Fréchet mean on a Riemannian manifold, restricting computation to a low-rank subspace.
result EpiMer outperforms flat-geometry methods on image classification tasks.
New Bayesian method improves Pareto front estimation in multitask finetuning.
problem Efficiently estimating Pareto fronts for multitask finetuning.
method Variational Model Merging using non-Gaussian posteriors.
result More flexible posteriors lead to better Pareto front estimates.
Deep reinforcement learning (DRL) on Markov decision processes (MDPs) with continuous action spaces is often approached by directly training parametric policies along the direction of estimated policy gradients (PGs). Previous research revealed that the performance of these PG algorithms depends heavily on the bias-var…
Study on merging predictors in causal and anticausal directions using CMAXENT.
problem Comparing merging predictors in causal and anticausal directions.
method Using CMAXENT as inductive bias, study differences in merging predictors.
result CMAXENT solution reduces to logistic regression in causal direction and LDA in anticausal direction.
In this paper, a similarity-driven cluster merging method is proposed for unsuper-vised fuzzy clustering. The cluster merging method is used to resolve the problem of cluster validation. Starting with an overspecified number of clusters in the data, pairs of similar clusters are merged based on the proposed similarity-…
New method merges MCMC samples without distributional assumptions.
problem Efficiently merging MCMC samples from disjoint subsets.
method Diffusion generative modelling for density approximation.
result Outperforms existing methods on high-dimensional problems.
Quantum computing poses a threat to Bitcoin and Ethereum, but only to spending and not mining.
problem Quantum computing threat to Bitcoin and Ethereum
method Separation of Shor's and Grover's quantum algorithms
result Quantum algorithms' impact on Bitcoin and Ethereum
Securely evaluates the benefits of merging datasets for causal estimation.
problem Challenges in assessing the value of merging datasets for causal treatment effect estimation.
method Cryptographically secure multi-party computation to evaluate Expected Information Gain (EIG) while ensuring privacy.
result Demonstrates the first privacy-preserving method for dataset acquisition tailored to causal estimation.
A new method merges neural networks using CCA to improve model performance.
problem Improving model accuracy through ensembling while reducing computational and storage costs.
method CCA Merge, a new model merging algorithm based on Canonical Correlation Analysis.
result CCA Merge leads to better model performance than past methods, especially in merging more than two models.
This paper reverses a construction by merging boundary critical points into an interior one.
problem Pushing interior critical points to the boundary and splitting them into two boundary points.
method Specific assumptions allow merging two boundary critical points into one interior critical point.
result Merging two boundary critical points into a single interior critical point.
Budgeted Stochastic Gradient Descent (BSGD) is a state-of-the-art technique for training large-scale kernelized support vector machines. The budget constraint is maintained incrementally by merging two points whenever the pre-defined budget is exceeded. The process of finding suitable merge partners is costly; it can a…
NAMEx merges experts using Nash bargaining for improved performance.
problem Sparse Mixture of Experts merging strategies lack a principled weighting mechanism.
method Reinterpreting expert merging through game theory, introducing Nash Merging and complex momentum.
result NAMEx consistently outperforms competing methods across various tasks and system sizes.
Efficiently estimates longitudinal networks by merging sparse networks.
problem Estimating longitudinal networks with sparse and temporal data.
method Adaptive network merging, tensor decomposition, point process.
result Significantly reduces estimation error and provides guidance for network merging.
Model shows how Ethereum can capture MEV from block construction, but centralization remains a concern.
problem Ethereum's ability to capture MEV from block construction.
method Economic model of Execution Tickets to study MEV extraction.
result MEV capture decreases with risk aversion and capital costs, and can be low with heterogeneous buyers.
Study reveals dynamic causal relationships between Ethereum transaction fees and economic subsystems.
problem Historical gas fee volatility caused economic disequilibria and stakeholder challenges.
method Time-varying Granger causality analysis using data on active wallets and transaction volume.
result Dynamic bidirectional causal relationships between transaction fees and economic subsystems across Ethereum.
A new method reduces task interference in model merging.
problem Model merging overlooks structural information and is susceptible to task interference.
method Task Singular Vectors (TSV) and TSV-Compress for compression and interference reduction.
result TSV-Merge significantly outperforms existing methods.
Discrete knot theory models use lattice-filtered graphs to detect merging knot components.
problem Detecting merging knot components in discrete models.
method Lattice-filtered move graphs to model knot types, identifying connected components and merge scales.
result Merge scale defined by connected components of lattice-filtered move graphs, with specific examples for the figure-eight knot.
Paper quantifies MEV on L2 networks, finding significant amounts on Polygon.
problem Lack of research on quantifying MEV on Ethereum Layer 2 networks.
method Analysis of Polygon's MEV, focusing on arbitrage opportunities and liquidations.
result Substantial MEV ($213 million) on L2s, mostly from arbitrage opportunities.