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https://arxiv.org/html/2608.03063v1
8 pp in a production fraud detector serving billion-scale transaction traffic

Efficient Audio Enhancement with a Differentiable Psychoacoustic Loss

https://arxiv.org/html/2608.02918v1
org perpetual non-exclusive license arXiv:2608

I INTRODUCTION

https://arxiv.org/html/2407.10811v1
II RELATED WORK II-A Traditional methods II-B RL methods. III PRELIMINARIES IV METHOD IV-A RL Setup IV-B Network design IV-C Training IV-D Theoretical Analysis V EXPERIMENT V-A Towards Real-world Dataset and Simulation V-B Benchmark

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https://arxiv.org/html/2608.03545v1
org perpetual non-exclusive license arXiv:2608

Global coal trade is resilient to maritime chokepoints

https://arxiv.org/html/2608.00328v2
org perpetual non-exclusive license arXiv:2608

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https://arxiv.org/pdf/2205.01882v5
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Geometric Cross-Modal Token Selection for Latency-Constrained Multimodal

https://arxiv.org/html/2608.03141v1
org perpetual non-exclusive license arXiv:2608

Decoupling Generation and Selection for Budget-Constrained Faithful

https://arxiv.org/html/2608.03655v1
org perpetual non-exclusive license arXiv:2608

When Collaboration Becomes a Trigger:Collective Evidence-Threshold

https://arxiv.org/html/2608.01085v1
org perpetual non-exclusive license arXiv:2608

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https://arxiv.org/pdf/2608.02817
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https://arxiv.org/pdf/2005.14165
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https://arxiv.org/html/2607.27099v1
org perpetual non-exclusive license arXiv:2607

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https://arxiv.org/pdf/2607.26188v1
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https://arxiv.org/pdf/2402.03300
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https://arxiv.org/pdf/2608.03118
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https://arxiv.org/pdf/2608.04008
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https://arxiv.org/pdf/2607.26405v1
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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.

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https://arxiv.org/pdf/2407.02510
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https://arxiv.org/src/2006.02759
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https://arxiv.org/src/2006.01048
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https://arxiv.org/pdf/2608.03411
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https://arxiv.org/pdf/2303.12712v5
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https://arxiv.org/pdf/2006.00342
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https://arxiv.org/pdf/2608.02918
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https://arxiv.org/pdf/2508.02691
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https://arxiv.org/pdf/2607.27070v1
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https://arxiv.org/pdf/2508.04671
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https://arxiv.org/pdf/2608.03233
T+jq8 M\c~wD`%::P sC` zzTrH`${0F{kʆƄ endstream endobj 411 0 obj > stream On the Diversity of Analogy Making in Large Language ModelsYuanhao ShenDaniel Xavier de SousaCaio César Sifuentes BarcelosHongyu GuoXiaodan Zhuhttp://arxiv