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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.

168,657 papers · 148 categories

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5099149198 · Jun 202019922001200920172026
48 results for Digital Transformation

This paper reviews digital transformation research from 2011-2024, focusing on corporate finance.

problem Lack of systematic review in digital transformation from corporate finance perspective.
method Combines bibliometric and content analysis methods.
result Emerging and rapidly growing focus on digital transformation, particularly in developed countries.

Digital transformation boosts corporate financial asset allocation, especially short-term.

problem Understanding how digital transformation affects corporate financial decisions.
method Fixed-effects models and staggered DID design using A-share listed companies data.
result Digital transformation significantly promotes corporate financial asset allocation, more pronounced in short-term.

This study identifies financial risk paths in digital-transformed enterprises.

problem Identifying financial risks in digital-transformed enterprises.
method DEMATEL-ISM-MICMAC method.
result Political and economic environment affects enterprise's financial structure.

Digitwashing gap boosts stock crash risk, study finds.

problem The gap between companies' digital promises and actual performance increases stock crash risk.
method Empirical analysis of Shanghai and Shenzhen A-share companies from 2010 to 2021, robustness tests conducted.
result GDT significantly increases stock price crash risk, confirmed by robust tests.

Study evaluates digital transformation impact on financial performance using LLMs.

problem Measuring and understanding the impact of digital transformation on financial performance.
method Constructed DT indicators from company reports; analyzed effects of different digital technologies.
result Digital transformation improves financial performance, but varies by technology.

We present a general theory of fractal transformations and show how it leads to a new type of method for filtering and transforming digital images. This work substantially generalizes earlier work on fractal tops. The approach involves fractal geometry, chaotic dynamics, and an interplay between discrete and continuous…

2011-02-15abs ↗pdf ↗

Financial fraud detection in digital banking requires reasoning over multiple heterogeneous event streams.

problem Financial fraud detection in digital banking requires reasoning over multiple heterogeneous event streams.
method Multi-Stream Fraud Transformer (MSFT) architecture that encodes each event stream with independent Transformer encoders and fuses their representations through configurable mechanisms.
result Sequence models significantly outperform gradient-boosted trees operating on aggregated features.

A new method streamlines digital payment programming using smart contracts.

problem High costs and security challenges in programming smart contracts for digital payments.
method Transforming digital currencies into token streams and using configurable templates to generate specialized smart contracts.
result Reduces payment programming costs and enhances security, self-enforcement, adaptability, and controllability.

This study synthesizes stablecoin systems and develops a performance evaluation framework.

problem Fragmented academic research on stablecoins across economics, law, and computer science.
method Multi-method research design including literature synthesis, performance evaluation framework, and case study.
result Unified taxonomy and performance evaluation framework for stablecoin design.

Digital tools may hinder or facilitate multidisciplinary collaboration in occupational health.

problem Challenges in multidisciplinary collaboration in occupational health.
method Study of a precursor SPSTI's digital tools and their impacts.
result Digital tools can act as both brakes and levers for multidisciplinary dynamics.

Study develops smart contract framework for procurement under demand variability.

problem Operational and economic implications of smart contract adoption under moderate uncertainty.
method Multi-supplier model with endogenized adoption costs, supplier readiness, and inventory penalties; analytical and numerical results.
result Partial adoption strategies support moderate demand variability, while excessive digital investment reduces profitability.

Transformer struggles with arithmetic length but improves with explicit structure encoding.

problem Transformers fail to generalize length in arithmetic tasks.
method Explicitly encoding structural symmetries via modified number formatting and custom positional encodings.
result Transformer can generalize up to 50-digit numbers without additional data.

Our goal is to extract meaningful transformations from raw images, such as varying the thickness of lines in handwriting or the lighting in a portrait. We propose an unsupervised approach to learn such transformations by attempting to reconstruct an image from a linear combination of transformations of its nearest neig…

2017-11-06abs ↗pdf ↗

Transformer models improve arithmetic accuracy with number decomposition.

problem Transformer models struggle with arithmetic operations without decomposition.
method Fine-tuning models with a pipeline that decomposes numbers into units, tens, etc.
result Accuracy increased by 63% in five-digit addition tasks.

Study assesses impact of CBDC on financial stability in dual-currency economy.

problem Impact of CBDC on financial stability in dual-currency economy (Romania).
method Integrated analytical framework combining econometrics, machine learning, and behavioural modelling. CBDC adoption probabilities estimated using XGBoost and logistic regression models. Liquidity stress simulations and VAR, MSVAR, SVAR models capture macro-financial transmission.
result CBDC uptake would be moderate, primarily driven by digital readiness and trust in the central bank.

This paper improves anomaly detection in lane rendering images for safer navigation.

problem Anomalies in lane rendering images can mislead drivers, posing safety risks.
method Proposes a four-phase pipeline using Transformer models, self-supervised pre-training, and fine-tuning.
result The pipeline enhances detection accuracy and reduces training time.

Orchestrating the Twin Transition in GBS: A Socio-Technical Framework

problem MNCs' need to harmonize digital efficiency with environmental stewardship
method Technology Roadmapping (TRM) with ICT-centric innovation ecosystem toolkit
result Central 'operational airlock' for GBS in harmonizing digital and environmental transformation

A tailored HTR system improves CER to 0.015 for medieval Latin.

problem Digitizing handwritten medieval Latin records for a low-resource language.
method End-to-end pipeline using image segmentation and transformer-based models with extensive data augmentation.
result Best-performing setup achieved CER of 0.015, superior to commercial models.

This paper reviews bank performance determinants, highlighting future research areas.

problem Understanding bank performance factors to improve sector efficiency and knowledge.
method Analysis of 54 studies in peer-reviewed journals.
result Bank performance factors remain largely unexplored, especially post-COVID-19.

MoCA uses a novel autoencoder to analyze multi-modal health data.

problem Challenges in analyzing continuous multi-modal health data from wearable devices.
method Proposes MoCA, a self-supervised learning framework combining transformer and masked autoencoder methods.
result Demonstrates strong performance boosts across reconstruction and classification tasks.

Many transformations in deep learning architectures are sparsely connected. When such transformations cannot be designed by hand, they can be learned, even through plain backpropagation, for instance in attention mechanisms. However, during learning, such sparse structures are often represented in a dense form, as we d…

2018-10-22abs ↗pdf ↗

In this paper, we show how to construct graph theoretical models of n-dimensional continuous objects and manifolds. These models retain topological properties of their continuous counterparts. An LCL collection of n-cells in Euclidean space is introduced and investigated. If an LCL collection of n-cells is a cover of a…

2017-05-02abs ↗pdf ↗

This paper uses LLMs to streamline industrial data-centric R&D cycles.

problem High costs in human, computational, and time resources in data-centric R&D.
method Explores how large language models can understand domain-specific requirements and automate R&D tasks.
result Promising results show potential for automating industrial data-centric R&D cycles.

Incorrect fixed point assertions in digital topology are discussed.

problem Incorrect, incorrectly proven, or trivial fixed point assertions in digital topology.
method Continues earlier work on identifying and critiquing bad fixed point assertions.
result Clarifies the nature and extent of incorrect fixed point assertions in digital topology.

The study examines lower and upper bounds of Wasserstein distances for affine transformations of random vectors.

problem Understanding Wasserstein distances for affine transformations of random vectors.
method Lower and upper bounds for affine transformations of random vectors in Rn\mathbb{R}^n are derived using Bures metric and compositions of affine maps.
result Concrete lower bounds and upper bounds for affine transformations are derived and applied to various distributions.