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Freshness: newest result fetched 24 d ago · median age of these results 24 d · 1 of 30 carry a fetch time

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https://arxiv.org/pdf/2608.00328
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https://arxiv.org/pdf/2407.00125
) /Title (A Survey on Failure Analysis and Fault Injection in AI Systems) /Trapped /False /arXivID (https://arxiv

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https://arxiv.org/pdf/2608.01785
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https://arxiv.org/pdf/2508.11152
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https://arxiv.org/src/2006.02833
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https://arxiv.org/pdf/2608.03833
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https://arxiv.org/pdf/2005.14165
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https://arxiv.org/pdf/2608.00426
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https://arxiv.org/pdf/2608.03233
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https://arxiv.org/pdf/2608.02854v1
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https://arxiv.org/pdf/2608.03157
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https://arxiv.org/pdf/2608.02918
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https://arxiv.org/pdf/2507.17609
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https://arxiv.org/pdf/2608.04008
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Information Retrieval

https://arxiv.org/list/cs.IR/new
IR) Industrial recommenders increasingly adopt the pretrain-then-transfer paradigm, yet behavioral distribution drift raises two questions: what to learn from behavior sequences, and how to transfer the learned knowledge while the pretrained model is continually refreshed

Computers and Society Aug 2026

https://arxiv.org/list/cs.CY/current
251-256 Showing up to 50 entries per page: fewer | more | all [1] arXiv:2608

Social and Information Networks

https://arxiv.org/list/cs.SI/new
per page: fewer | more | all New submissions (showing 4 of 4 entries) [1] arXiv:2608

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https://arxiv.org/src/2006.03178
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General Economics

https://arxiv.org/list/econ.GN/recent
RM) Tue, 4 Aug 2026 (showing 16 of 16 entries ) [13] arXiv:2608

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https://arxiv.org/src/2002.02145
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1 Introduction

https://arxiv.org/html/2403.08299v1
Introduction As developers increasingly adopt AI assistants such as ChatGPT for their development tasks, productivity gains become evident

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https://arxiv.org/pdf/2608.02609
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Machine Learning Dec 2024

https://arxiv.org/list/cs.LG/2024-12
3251-3298 Showing up to 50 entries per page: fewer | more | all [1] arXiv:2412

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https://arxiv.org/pdf/2608.03898
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https://arxiv.org/pdf/2407.00391
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https://arxiv.org/pdf/2609.02852
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https://arxiv.org/pdf/2608.02244
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https://arxiv.org/pdf/2412.12213
Finance-Informed Neural Network: Learning the Geometry of Option PricingAmine M. AboussalahXuanze LiCheng ChiRaj Patelhttp://creativecommons.org/licenses/by/4.0/cs.LGq-fin.CPstat.ML endstream endobj 4 0 obj > endobj 5 0 obj > endobj 6 0 obj

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https://arxiv.org/pdf/2508.02758
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https://arxiv.org/src/2403.08299
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