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Instrumentation and Methods for Astrophysics

https://arxiv.org/list/astro-ph.IM/new
Total of 28 entries New submissions (showing 11 of 11 entries) Subjects: Instrumentation and Methods for Astrophysics (astro-ph.IM); General Relativity and Quantum Cosmology (gr-qc) With the observational accuracy of astrometric space

Width, Memory, and Delay: A Resource Accountingfor the Limits of Flat

https://arxiv.org/html/2608.00028v1
This paper replaces the single flat/deep axis with a resource triangle —width, memory, and delay-prediction (Fig

Every Wrong Answer Counts: Option-Level Psychometrics for LLM Multiple

https://arxiv.org/html/2608.02966v1
-Choice Benchmarks Report GitHub Issue × Title: Content selection saved. Describe the issue below: Description: Submit without GitHub Submit in GitHub arXiv is now an independent nonprofit! Learn more × Back to arXiv Why HTML?

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https://arxiv.org/html/1802.00050v1
Deep Learning methods combine basic and generated features using various activation functions such as sigmoid or softmax

I INTRODUCTION

https://arxiv.org/html/2407.10811v1
Despite all efforts in this field, there is no real-world deployment of an actual RL-based TSC to date

Consensus Measures for Unstructured Biomedical Text Annotations

https://arxiv.org/html/2608.03529v1
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https://arxiv.org/html/2609.03103v1
The resulting soft X-ray sky coverage is extremely valuable and has generated deep serendipitous XRT source catalogues [8], but it is an opportunistic archive rather than a designed survey

Underspecification in Language Modeling Tasks: A Causality-Informed

https://arxiv.org/html/2210.00131v4
Study of Gendered Pronoun Resolution 1 Introduction 1.1 Related Work 1.2 Contributions 2 Background: Selection Bias 3 Problem Settings 3.1 Illustrative Toy Task 3.2 Toy Data Structural Causal Model 3.3 Gendered Pronoun Resolution Task 4

Efficient Audio Enhancement with a Differentiable Psychoacoustic Loss

https://arxiv.org/html/2608.02918v1
Miranda is also with LCTI, Télécom Paris, IP Paris, France

MDGAM-Based Cooperative Task Scheduling for Communication-Constrained

https://arxiv.org/html/2608.00648v1
Distributed Multi-Agent Systems Report GitHub Issue × Title: Content selection saved. Describe the issue below: Description: Submit without GitHub Submit in GitHub arXiv is now an independent nonprofit! Learn more × Back to arXiv

Cryptography and Security

https://arxiv.org/list/cs.CR/new
Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Cryptography and Security New submissions Cross-lists Replacements See recent articles Showing new listings for Friday, 7 August 2026

Condensed Matter

https://arxiv.org/list/cond-mat/new
The mixed anomaly between these is accommodated by the not-on-site action of the symmetries

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https://arxiv.org/html/2609.03159v1
An XMM-Newton deep, wide (>1>1 deg2) extragalactic X-ray survey (Hasinger et al

Electrical Engineering and Systems Science

https://arxiv.org/list/eess/new
We note that ScoreField significantly improves reconstruction fidelity and suppresses artifacts relative to classical full-wave methods and deep learning baselines, achieving an average PSNR improvement of $1

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https://arxiv.org/html/2401.02063v2
Astronomy Observatory, 520 Edgemont Rd, Charlottesville VA 22903, USA    Deep Chatterjee Affiliation: LIGO Laboratory and Kavli Institute for Astrophysics and Space Research, Massachusetts Institute of Technology, 185 Albany Street, Cambridge, Massachusetts 02139, USA    Alessandra Corsi Affiliation:

Distributed Instruments for Planetary Surface Science: Scientific

https://arxiv.org/html/2407.01757v1
However, to date, their adoption in planetary surface science has been minimal

Finance-Informed Neural Network: Learning the Geometry of Option Pricing

https://arxiv.org/html/2412.12213v2
By learning prices and sensitivities that support effective replication, FINN enforces economic consistency by construction while retaining the flexibility of modern deep learning architectures

Computation and Language

https://arxiv.org/list/cs.CL/new
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Preying on Leveraged ETFsPreliminary and incomplete. This project was

https://arxiv.org/html/2608.03703v1
begun on July 20, 2026; the present version is dated August 4, 2026. Claude Opus 5 and Fable 5 provided research assistance throughout, spanning code development, data construction and empirical analysis, and the drafting of the manuscript.

Computer Vision and Pattern Recognition

https://arxiv.org/list/cs.CV/new
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Mathematics

https://arxiv.org/list/math/new
Their finite iterates can develop rapidly increasing numbers of linear pieces, making them a natural test case for the expressive power of deep neural networks

Artificial Intelligence

https://arxiv.org/list/cs.AI/new
Skip to main content System maintenance August 4th and 5th Learn more × Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Artificial Intelligence New submissions Cross-lists Replacements See recent