On-device research index

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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6 results for “scale-aware”

On the sensitivity of machine-learned probabilistic weather forecast models to scale-aware scoring rulesphysics.ao-ph

Study compares different scoring rules for machine-learned weather forecasts, finding scale-awareness improves forecast realism.

problem Improving the accuracy of machine-learned probabilistic weather forecasts.

method Comparison of scoring rules (CRPS, fair global energy score, graph energy score) and analysis of their impact on forecast field spectra.

result Scale-awareness improves forecast realism, particularly in the tropics.

weather forecasting machine learning scoring rules scale-awareness forecast accuracy

2026-07-21abs ↗pdf ↗

AutoScale: Scale-Aware Data Mixing for Pre-Training LLMscs.LG

AutoScale improves LLM pre-training by adjusting data mixtures at different scales.

problem Data mixtures that work well at small scales may not perform as well at larger scales.

method AutoScale uses a two-stage approach: fitting a model to predict loss under different compositions and extrapolating optimal compositions to larger scales.

result AutoScale accelerates convergence and improves downstream performance.

LLM pre-training domain reweighting data mixing scale-aware perplexity reduction

2024-07-29abs ↗pdf ↗

FisheyeDistanceNet: Self-Supervised Scale-Aware Distance Estimation using Monocular Fisheye Camera for Autonomous Drivingcs.CV

Fisheye cameras are commonly used in applications like autonomous driving and surveillance to provide a large field of view ( $>180^{\circ}$ ). However, they come at the cost of strong non-linear distortions which require more complex algorithms. In this paper, we explore Euclidean distance estimation on fisheye cameras …

2019-10-07abs ↗pdf ↗

Understanding the Mechanisms of Fast Hyperparameter Transfercs.LG

New framework explains fast transfer of hyperparameters across model scales.

problem Understanding and optimizing hyperparameters for large-scale models.

method Developed a conceptual framework for HP transfer across scale, showing fast transfer is equivalent to useful transfer for compute-optimal grid search.

result Fast transfer of hyperparameters is equivalent to useful transfer for compute-optimal grid search, offering asymptotic computational advantage.

hyperparameter optimization scale-aware HPs fast transfer compute efficiency Maximal Update Parameterization

2025-12-28abs ↗pdf ↗

Sparse Network Inference under Imperfect Detection and its Application to Ecological Networksstat.ML

Framework for inferring latent structure from sparse, imperfectly detected bipartite networks.

problem Recovering latent structure from sparse, imperfectly detected bipartite networks in ecology.

method Structured sparse nonnegative low-rank factorization with detection probability estimation and ADMM-based algorithm.

result Improved recovery of latent factors and structure compared to existing methods.

network inference sparse networks bipartite networks ecology nonnegative low-rank factorization

2026-04-20abs ↗pdf ↗

Feasibility-First Satellite Integration in Robust Portfolio Architecturesq-fin.PM

Develops a new framework for integrating satellite allocations in small portfolios.

problem Feasibility constraints in small portfolios, not return predictability, are the primary concerns.

method A four-layer feasibility framework: physical, economic, structural, and epistemic.

result Closed-form feasibility bounds on satellite size, turnover, and breadth without return forecasts.

satellite integration portfolio architecture feasibility small portfolios non-predictive

2026-01-13abs ↗pdf ↗