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https://arxiv.org/html/2609.02852v1
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https://arxiv.org/html/2609.03371v1
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Computer Vision and Pattern Recognition

https://arxiv.org/list/cs.CV/new
Project Page: this https URL [2] arXiv:2608

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https://arxiv.org/html/2608.02613v1
Then it must make an even harder judgment: even if the answer is known, is it actually appropriate to tell Bob

Stochastic Games with Minimally Bounded Action Costs

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

Homogeneous Distributed Observers for Quasilinear Systems

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

Statistics Theory Mar 2024

https://arxiv.org/list/math.ST/2024-03
00186 [pdf, html, other] Title: Warped Kernel Estimator for I

Electrical Engineering and Systems Science

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

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

Solar and Stellar Astrophysics

https://arxiv.org/list/astro-ph.SR/new
per page: fewer | more | all New submissions (showing 19 of 19 entries) [1] arXiv:2608

Computer Science > Computation and Language

https://arxiv.org/abs/2609.14858
--> Computer Science > Computation and Language arXiv:2609

Microstructural Foundations of Rough Noise1footnote

https://arxiv.org/html/2607.29442v2
In an asymptotic framework inspired by Rosenbaum2018, we show that the rescaled price process converges to a Bachelier-type semimartingale plus a Gaussian moving average whose kernel is determined explicitly by the trawl function

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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

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https://arxiv.org/pdf/2006.02318
org/pdfua/ns/id/ pdfuaid PDF/UA ID Schema internal Part of PDF/UA standard part Integer PRISM metadata http://prismstandard

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https://arxiv.org/pdf/2508.11152
com three Proceedings of ACM Conference (Conference'17) book 1 1 9 9 Tianjiao ZhaoJingrao LyuStokes JonesHarrison GarberStefano PasqualiDhagash Mehtahttp://arxiv

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https://arxiv.org/pdf/2608.01934
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https://arxiv.org/pdf/2607.26327v3
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https://arxiv.org/pdf/2609.18842
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https://arxiv.org/pdf/2608.02694
Ìfó_דiF¨íp`°Ÿª˜ê›ÜŽÓe¡ì ÿܽUœ/&+²éKø¬ÒSÐV‘O„` ˜Þ

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https://arxiv.org/pdf/2006.00342
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https://arxiv.org/src/2303.12712
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https://arxiv.org/pdf/2506.01844
SmolVLA: A Vision-Language-Action Model for Affordable and Efficient RoboticsMustafa ShukorDana AubakirovaFrancesco CapuanoPepijn KooijmansSteven PalmaAdil ZouitineMichel AractingiCaroline PascalMartino RussiAndres MarafiotiSimon

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https://arxiv.org/src/1910.03771
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https://arxiv.org/pdf/2608.02609
,”œ6ýúJtLÊ’ ËÎåÌá5&(Bñ1„‰@!�H"PŒ(g(A G(E,Nüà .‰H€?ŠŒ0E)‡;H€)\9X0\áCSŠp & _ ˜lø$àO"ø ±Ã �Ò)\Á$R†|R7Ql�¢ª€ÅpNîSD°lšFœá °(A,â‚àÓßÞ¿G“�~oÐäJýh ïö÷µ4ªl,°ööN7…‚œí݇›ÀÔ dƒ�×F½ â'a8LÂÜê´ZCÜ1E“�ÚÔ °Þš/$ü޽:ÉxÔa½

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https://arxiv.org/pdf/2608.02872
‰¼~ýž Ðè™ÜM•CÐh¦uút쪅 :Ó˜Á,‡™Lè6³˜ð,f3Ý6™Ã Ã`.35�yÌ´aš&;äúÁSDº¥ r›YÆì¿ÌMi…"{°.Ò|ùkksìσ¸BbŽÎz7=9'ÜÖ9Qš¤-k˜Ó°*5«ÂÝÕéÇâxb+ºæUà)–VKÈ£fQ˜ŸvŽï ŽBd°òÒ’ šñ¸ K‚Q³$tNû·™‚n[ ZE•¯cÊŒ3+$À.åxžÝÖktûööø´Š¿ºÒÜ–7írŽ—eª¹Xñ”\W”ü0|z

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https://arxiv.org/src/2608.04007
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https://arxiv.org/pdf/2205.11916v2
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https://arxiv.org/pdf/2006.00064
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https://arxiv.org/src/2405.20232
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https://arxiv.org/pdf/2608.03494
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