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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,051 papers · 148 categories

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12.5%25.0%37.5%50.0% · Mar 199419922001200920182026
48 results for Design rule check

Neural network ensembles predict design rule violations from early stages of IC design.

problem Predicting design rule violations from placement and global routing stages in IC design.
method Proposes a framework using neural network ensembles with soft voting and PCA-based subset selection.
result Significant improvement in model performance compared to baseline, including better performance than random forest.

FinReflectKG builds a comprehensive financial knowledge graph from SEC filings, improving extraction quality.

problem Lack of large-scale, open-source financial knowledge graph datasets.
method Intelligent document parsing, table-aware chunking, schema-guided iterative extraction, reflection-driven feedback loop.
result Reflection-agent-based mode achieves best balance of efficiency, accuracy, and reliability.

We consider rules for discarding predictors in lasso regression and related problems, for computational efficiency. El Ghaoui et al (2010) propose "SAFE" rules that guarantee that a coefficient will be zero in the solution, based on the inner products of each predictor with the outcome. In this paper we propose strong …

2010-11-09abs ↗pdf ↗

Researchers validate ML scenario generators by checking dependencies and detecting memorization effects.

problem Validation of machine learning-based scenario generators differs from classical methods due to data-driven dependencies.
method Two novel validation aspects: checking dependencies and detecting memorization effects. Novel memorization ratio introduced.
result Validation methods successfully detect dependencies and memorization effects in ML-based scenario generators.

A quantitative check of weak efficiency in US dollar/German mark exchange rates is developed using high frequency data. We show the existence of long term return anomalies. We introduce a technique to measure the available information and show it can be profitable following a particular trading rule.

1999-01-21abs ↗pdf ↗

Study finds no significant short-term impact on liquidity supply after protocol fees were reduced.

problem Liquidity provider welfare is affected by protocol fees, but the impact on liquidity supply is unclear.
method Used a matched-overlap event-study difference-in-differences design to estimate the liquidity-supply response to take-rate cuts.
result No significant short-term impact on active liquidity or local depth; no change in LP participation or composition.

Statistical model checking for PCTL on MDPs using reinforcement learning.

problem Model checking PCTL specifications on MDPs with statistical methods.
method Reinforcement learning for policy search, statistical model checking with UCB-based Q-learning.
result Provably guaranteed statistical model checking method for PCTL specifications on MDPs.

Paper uses RNNs to design LDPC codes for binary erasure channels.

problem Designing capacity-approaching LDPC codes for binary erasure channels.
method Model Density Evolution using RNNs to determine LDPC code coefficients and structure.
result NDE improves LDPC design performance and complexity compared to differential evolution.

SMC analysis reveals key transient effects in macroeconomic ABM.

problem Analysis of complex ABMs is challenging and often relies on ad hoc methods.
method Statistical model checking (SMC) implemented through MultiVeStA.
result Clear contrast across parameter families in macro-financial and structural sweeps.

New method evaluates language model forecasters by checking consistency of predictions.

problem Evaluating the performance of language model forecasters is difficult due to lack of ground truth.
method Developed a consistency check framework based on arbitrage to evaluate forecasters.
result Consistency metrics correlate with ground truth performance of LLM forecasters.

The paper proposes a method to evaluate superhuman models by checking for logical inconsistencies.

problem Evaluating superhuman models when ground truth is hard to obtain.
method A framework using consistency checks to identify logical inconsistencies in model decisions.
result Logical inconsistencies can be discovered in superhuman model decisions across various tasks.

ToolChain-CRC addresses the risk-control problem for retrieval-augmented and tool-using agents under drift.

problem Risk-control problem for retrieval-augmented and tool-using agents under drift.
method ToolChain-CRC uses conformal risk-control under exchangeable calibration runs.
result Trajectory-level risk control keeps accepted-trajectory risk below the target.

In the framework of supervised classification (discrimination) for functional data, it is shown that the optimal classification rule can be explicitly obtained for a class of Gaussian processes with "triangular" covariance functions. This explicit knowledge has two practical consequences. First, the consistency of the …

2010-04-28abs ↗pdf ↗

The paper proposes a tool to detect invalid inputs in DL models.

problem Vulnerability of DL models to invalid inputs during runtime.
method Design and implementation of a tool that extracts data flow footprints and conducts assertion-based validation.
result The assertion-based data sanity check mechanism effectively identifies invalid input cases.

System uses neural networks to prove program equivalence via rewrite rules.

problem Proving equivalence between two dataflow graphs.
method Developed a graph-to-sequence neural network trained on example generation to find semantics-preserving rewrite rules.
result System correctly outputs a rewrite sequence for 96% of program pairs, proving equivalence.

Optimal Volt/VAR control rules are designed using deep neural networks.

problem Designing optimal Volt/VAR control rules for distributed energy resources (DERs).
method Formulate optimal rule design as a bilevel program, then reformulate it as training a deep neural network (DNN). Use proximal gradient descent (PGD) iterations to emulate Volt/VAR dynamics.
result The proposed solution can be adapted to single/multi-phase feeders and achieves enhanced steady-state voltage profiles.

New Fourier features improve high-precision approximation in large-scale problems.

problem Designing scalable, high-precision Fourier features for large-scale kernel methods.
method Introducing a new family of quadrature rules that accurately approximate the Gaussian measure in higher dimensions.
result Improved approximation bounds with new Fourier features.

Estimates funding impact from an algorithmic relief rule, finding little effect on hospital activities.

problem Evaluating the impact of algorithmic policy decisions.
method Developed a treatment-effect estimator using algorithmic decisions as instruments.
result Funding from an algorithmic relief rule had little effect on COVID-19-related hospital activities.

State-of-the-art password guessing tools, such as HashCat and John the Ripper, enable users to check billions of passwords per second against password hashes. In addition to performing straightforward dictionary attacks, these tools can expand password dictionaries using password generation rules, such as concatenation…

2017-09-01abs ↗pdf ↗

Distribution grids are currently challenged by frequent voltage excursions induced by intermittent solar generation. Smart inverters have been advocated as a fast-responding means to regulate voltage and minimize ohmic losses. Since optimal inverter coordination may be computationally challenging and preset local contr…

2018-07-10abs ↗pdf ↗

MatGAN uses GAN to efficiently generate new inorganic materials.

problem Efficiently searching the vast chemical design space for new materials.
method Generative adversarial network (GAN) trained on ICSD materials database.
result 92.53% novelty and 84.5% chemically valid samples generated.

We introduce a new weight-decay scaling rule to maintain sublayer gains across different widths in modern scale-invariant architectures.

problem In modern scale-invariant architectures, training quickly enters a steady state where normalization layers create backward scale sensitivity, degrading learning-rate transfer.
method We introduce a weight-decay scaling rule for AdamW that preserves sublayer gain across widths by equalizing the effective learning rate.
result Our empirical weight-decay scaling rule λ2dλ_2\propto \sqrt{d} approximately keeps sublayer gains width invariant, enabling zero-shot transfer of learning rate and weight decay.

New functions derived from arrow diagrams for spherical curves, invariant under certain deformations.

problem Defining and analyzing integer-valued functions on spherical curves.
method Introducing new functions and relators to study spherical curves and their isotopy classes.
result Functions derived from arrow diagrams are invariant under specific deformations.

Paper bridges matching rules and height functions in aperiodic tilings.

problem Relationship between matching rules and height functions in aperiodic tilings.
method Cochain-first framework to establish equivalence between matching rules, Ammann bar continuity, cycle closure of 1-cochains, and height-function existence.
result Unified framework for aperiodic tilings including Penrose and canonical projection tilings.

This paper formalizes Uniswap v3 using PTA and FST for rigorous analysis.

problem Formal modeling of Uniswap v3's concentrated liquidity for rigorous analysis.
method Formal state machine models using PTA and FST, proving rounding bounds.
result Formal justification of Uniswap v3's εε-slack and rounding safety.

A new score function improves explainability and reliability of AI systems.

problem Designing AI systems that are explainable, robust, and trustworthy.
method Integrates conformal prediction with explainable machine learning using a novel score function.
result The method achieves improved performance on target classes and satisfies conformal guarantees.

The study develops a logic reasoner to verify MS case management specifications.

problem Ensuring correctness and solvability of abstract clinical work products.
method Developed a logic reasoner using UML class and state diagrams, SPIN, and ODM.
result Formal representations of UML diagrams proved consistent for MS case management.