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7 application/pdf SeqLLM: Augmenting LLMs with Behavioral-Sequence Modeling for High-Stakes Decisions at WeChat Pay arXiv 2026-08-05T00:26:47Z Text Guilin LiJiaxing ZhangMatthias Hwai Yong TanBo WangWeiran Huang kdd2027_main
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https://arxiv.org/pdf/2608.03063
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https://arxiv.org/pdf/2608.02122
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https://arxiv.org/pdf/2608.02764
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https://arxiv.org/pdf/2608.01785
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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/2607.28577v1
) /Title (Train Often, Deploy Selectively: Forward-Gated Model Replacement in Crypto Markets) /Trapped /False /arXivID (https://arxiv

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https://arxiv.org/pdf/2607.27188v1
) /Title (Inverse Learning of Latent Risk-Neutral Densities from Irregular Option Quotes) /Trapped /False /arXivID (https://arxiv

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https://arxiv.org/pdf/2608.03883
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https://arxiv.org/pdf/2508.11152
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https://arxiv.org/src/2608.03994
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https://arxiv.org/src/2006.02318
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https://arxiv.org/src/2006.02759
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https://arxiv.org/pdf/2608.01651v1
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https://arxiv.org/pdf/2006.00342
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https://arxiv.org/src/2205.11916v1
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https://arxiv.org/pdf/2109.12196
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https://arxiv.org/src/2006.01048
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https://arxiv.org/pdf/2608.03118
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https://arxiv.org/src/2205.11916v3
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https://arxiv.org/pdf/2407.02510
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https://arxiv.org/pdf/2607.28410v1
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https://arxiv.org/src/2211.10435
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https://arxiv.org/pdf/2608.02758
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https://arxiv.org/pdf/2608.02615
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https://arxiv.org/pdf/2303.12712v5
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https://arxiv.org/pdf/2402.03300
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https://arxiv.org/pdf/2508.04671
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https://arxiv.org/pdf/2005.13905
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