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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.

169,181 papers · 148 categories

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7 results for “Reference-free”

All That Glisters Is Not Gold: A Benchmark for Reference-Free Counterfactual Financial Misinformation Detectioncs.CL

Benchmark evaluates financial misinformation detection models, revealing weaknesses without external context.

problem Detecting financial misinformation without external references.

method RFC Bench at paragraph level, two tasks: reference-free detection and comparison-based diagnosis.

result Performance improves with comparative context, revealing model weaknesses in reference-free settings.

financial misinformation reference-free detection counterfactual reasoning language models news analysis

2026-01-07abs ↗pdf ↗

A Machine-learning framework for automatic reference-free quality assessment in MRIcs.CV

Automated MRI image quality assessment framework using machine learning.

problem Manual quality assessment of MRI images is time-consuming and costly.

method Machine learning model trained on human observer labels without reference images.

result Framework achieves 93.7% accuracy in estimating image quality.

MRI Quality assessment Machine learning Reference-free Human observer

2018-06-25abs ↗pdf ↗

Semiparametric Wavelet-based JPEG IV Estimator for endogenously truncated datastat.ME

New JPEG algorithm corrects biases in endogenously truncated data.

problem Correcting biases in data with endogenous truncation.

method Semiparametric wavelet-based approach, avoiding matrix computations.

result Corrects both endogenous truncation and covariate shifts biases.

JPEG algorithm wavelet transform endogenous truncation covariate shift machine learning

2019-08-06abs ↗pdf ↗

Deep learning enables reference-free isotropic super-resolution for volumetric fluorescence microscopycs.CV

Deep learning improves 3D microscopy resolution without matched target images.

problem Anisotropic resolution in volumetric fluorescence microscopy.

method Cycle-consistent generative adversarial network trained on unpaired 2D images.

result Enhanced axial resolution and restored details between imaging planes.

deep learning isotropic super-resolution volumetric fluorescence microscopy optimal transport cycle-consistent GAN

2021-04-19abs ↗pdf ↗

EVODiff: Entropy-aware Variance Optimized Diffusion Inferencecs.CV

EVODiff optimizes DM inference by reducing conditional entropy, improving image generation.

problem Slow and inaccurate inference in diffusion models.

method Entropy-aware variance optimization for efficient inference.

result Significant improvement in image generation quality and efficiency.

diffusion models inference optimization conditional entropy image generation reconstruction error

2025-09-30abs ↗pdf ↗

Do Vendi Scores Converge with Finite Samples? Truncated Vendi Score for Finite-Sample Convergence Guaranteesstat.ML

The paper investigates the convergence of Vendi scores under finite samples and introduces a truncated version for better performance.

problem The Vendi score's convergence is hindered by computational limitations when using large sample sizes.

method The authors introduce the t-truncated Vendi score to address this issue by truncating the eigenspectrum of the kernel matrix.

result The t-truncated Vendi score converges to its asymptotic limit with a smaller number of samples, improving upon the standard Vendi score.

Vendi score finite sample convergence Nyström approximation FKEA image data

2024-10-29abs ↗pdf ↗

k-Space Deep Learning for Reference-free EPI Ghost Correctioncs.CV

A k-space deep learning method corrects EPI ghost artifacts without a reference scan.

problem Nyquist ghost artifacts in EPI MRI due to phase mismatch between even and odd echoes.

method Structured low-rank Hankel matrix approaches combined with data-driven Hankel matrix decomposition and deep convolutional neural networks.

result The proposed k-space deep learning method outperforms existing methods in image quality and computing time.

EPI ghost correction k-space deep learning Nyquist artifacts Hankel matrix Deep neural networks

2018-06-01abs ↗pdf ↗