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https://arxiv.org/list/math.ST/new
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New submissions (showing 6 of 6 entries)
[1] arXiv:2608
https://arxiv.org/html/2407.18010v2
We prove the game respects a dynamic programming principle and that the Markov perfect equilibrium can be computed as a limit point of a sequence of Bellman operations
https://arxiv.org/list/cs.SE/new
Through an analysis of 1,966 open source projects, 1,355 Github issues, 444 CVE reports, and 361 StackOverflow posts, we systematically map the feature support and real-world usage of globs across six common ecosystems that utilize globs
https://arxiv.org/html/2407.20441v1
I Introduction
Training reinforcement learning (RL) algorithms is well-known to be a critically time consuming task that can require several data samples to achieve a desired level of accuracy
https://arxiv.org/html/2508.02739v1
2 Preliminary
3 Methodology
K-line Tokenization
Hierarchical Autoregressive Modeling
Model Pre-training
Dataset
Model Training
Inference
4 Experiments
Experimental Setup
Main Results
Prediction Tasks
Generative Tasks
Investment
https://arxiv.org/pdf/2205.01882v5
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https://arxiv.org/pdf/2608.00785
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https://arxiv.org/pdf/2608.02854v1
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https://arxiv.org/pdf/2608.00426
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https://arxiv.org/pdf/2507.17609
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https://arxiv.org/list/math.ST/2024-03
00186 [pdf, html, other]
Title: Warped Kernel Estimator for I
https://arxiv.org/list/cs.LG/2024-12
3251-3298
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[1] arXiv:2412
https://arxiv.org/list/astro-ph.SR/new
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New submissions (showing 19 of 19 entries)
[1] arXiv:2608
https://arxiv.org/list/cs.DB/new
We propose an architectural pattern for such systems, a trusted kernel with a generative shell, resting on one invariant: a component that can fabricate may influence which question the system answers, never which value it returns
https://arxiv.org/list/cs.OS/new
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New submissions (showing 2 of 2 entries)
[1] arXiv:2608
https://arxiv.org/abs/2504.02246
-->
Computer Science > Programming Languages
arXiv:2504
https://arxiv.org/abs/2609.14858
-->
Computer Science > Computation and Language
arXiv:2609
https://arxiv.org/list/cs.AR/new
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New submissions (showing 4 of 4 entries)
[1] arXiv:2608
https://arxiv.org/html/2609.03027v1
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arXiv is now an independent nonprofit
https://arxiv.org/html/2511.06451v1
Spectral safety and discrete Green kernel
https://arxiv.org/list/cs.LG/2022-12
2001-2004
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[1] arXiv:2212
https://arxiv.org/list/astro-ph.IM/new
In particular, the maximal light deflection of a given Solar System body can be easily estimated for a given observer
https://arxiv.org/html/2608.03411v1
com
Abstract
Accurate Uncertainty Quantification (UQ) is critical for reliable deployment of Large Language Models (LLMs), yet traditional probability-based metrics often fail to capture the model’s true epistemic state
https://arxiv.org/list/quant-ph/new
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https://arxiv.org/html/2407.05763v1
However, centralized observers for plants modeled by nonlinear systems satisfying Ho¨¨o\ddot{\mathrm{o}}over¨ start_ARG roman_o end_ARGlder condition can be found in the recent literature (see, e
https://arxiv.org/html/2407.20187v1
In this paper, we present polynomial-time algorithms which can eliminate majority illusion in a network by altering as few connections as possible
https://arxiv.org/list/eess/new
The design relies on two affine Volterra transformations involving both Fredholm- and Volterra-type integral terms, which results in a four-PIDE kernel equations
https://arxiv.org/pdf/2608.03898
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https://arxiv.org/src/2608.03994
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https://arxiv.org/src/2006.03720
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