Web This site Trusted
30 result(s) for “ip com target site does openstack org site can kernel org site cliki apache org site:arxiv.org” of 72 matched · 939 ms
Scope: Nishi’s own index (our crawl + Common Crawl) — not the whole live web. Some sites block all automated crawlers (anti-bot walls), so their pages may be absent here even though we never filter lawful content.
Did you mean ip com target site does openstack org site can kernel org site cwiki apache org site:arxiv.org?
Freshness: no result on this page carries a fetch time yet (indexed before the fetch epoch was stored beside the doc)
This study synthesizes adjacent research and introduces Enactive AI as a conceptual framework for enterprise and industry reasoning, site-level decision support, and execution feedback
from the top result below
https://arxiv.org/list/cs.AI/new
Extending the pattern-generation paradigm of Neural Cellular Automata (NCA), it navigates the degenerate Boolean search space to satisfy a computational task, rather than regenerating a fixed target state
https://arxiv.org/html/2609.03371v1
5-meter Segmented-Mirror Robotic Space Telescope does not carry a mid-infrared channel
https://arxiv.org/list/cs.CV/new
CV)
Fine-grained wildlife classification in aerial imagery is limited not only by model performance, but also by unreliable labels: animals occupy few pixels, key visual cues vary seasonally, and modality-specific evidence can be ambiguous
https://arxiv.org/html/2607.22511v2
A statement can be free of sorry and still be mathematically uninformative: a definition may reduce to True; or an unproven step may be introduced as an axiom that the kernel accepts
https://arxiv.org/html/2607.27099v1
org perpetual non-exclusive license
arXiv:2607
https://arxiv.org/list/econ/new
The paper develops a mechanism-design model showing that the same delegated intermediation structure can generate both Stiglitz-Weiss underinvestment and De Meza-Webb overinvestment distortions
https://arxiv.org/html/2608.02613v1
6 Ingest Overhead: When Does Structured Memory Pay Off
https://arxiv.org/html/2608.02817v1
expressed here are those of the authors and not necessarily those of the Federal Reserve Bank of Atlanta or the Federal Reserve System. The authors are grateful for the invaluable feedback they received on an earlier draft from Jón
https://arxiv.org/list/math/new
Their finite iterates can develop rapidly increasing numbers of linear pieces, making them a natural test case for the expressive power of deep neural networks
https://arxiv.org/html/2608.02851v1
org perpetual non-exclusive license
arXiv:2608
https://arxiv.org/html/2608.02612v1
org perpetual non-exclusive license
arXiv:2608
https://arxiv.org/list/cond-mat/new
The mixed anomaly between these is accommodated by the not-on-site action of the symmetries
https://arxiv.org/pdf/2608.02122
ؤϩ Øœ6U;ÉÁàN~û-á½O&¹g´ÊèÌîàE¿˜ýÄœ–Ö~¦Ã‰ÄA{‹8ß\Ž'—°q»�ÄAg2˜µÃçMf]‚¯Ip,«ùÍ›ö,óo †cÅì E" ²‰�SKº×3@‹ò ”“›Ù&†™˜å¯OÆÓ�+jeÖ÷Xz—¯*
https://arxiv.org/pdf/2407.00125
document was published isbn Text external ISBN for the publication in which the document was published doi Text external Digital Object Identifier for the document url URL external URL at which the document can be found byteCount Integer internal Approximate file size in octets pageCount Integer internal Number of
https://arxiv.org/pdf/2608.01785
+ÖÑÖ1‡}ª$jšdKmo€Át‹u°ê«bUQÍHF8‘†B™!’0Ή"ÌX¢ —š …rb‰d¡‘ZJ‰ ø‰¦ðÁ‰ÖœPAŒ¡„Jb¹%¸ž;î — HIF(�¬£2fa@â>�$€Î@‘d`˜#!ð•*M }šÃ'è3ÐAŸ1 Ç‚* søÊX ,Ò‚K Êfœ€3œjxð§xD¸†ý¸""Sˆàèà¦ðl‰0–‘H*øN¤Ì€È #•3Q™áD¢8¸,$BBŠ(ÎM”6°nˆ²Š0‚cDfDs
https://arxiv.org/abs/2608.12700
A kernel can pass that test and still be silently wrong
https://arxiv.org/abs/2204.04218
In many situations, computed tomography (CT) or magnetic resonance imaging (MRI) techniques capture several scans (modes) during a single investigation, which can jointly be used (in a multimodal fashion) to further boost the quality of super-resolution results
https://arxiv.org/abs/2006.02833
We also explore performance evaluation of cloud bursting for six modern and distributed database systems on the hybrid cloud spanning over local OpenStack and Microsoft Azure
https://arxiv.org/abs/2608.02851v1
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/abs/2512.09590
Using an extension of the exponential-affine transformation formula for those processes, we establish in the long run the existence of limiting distributions, which (unlike in the case of classical affine diffusion processes) may depend on the initial state of the process, unless the Volterra kernel coincides with the
https://arxiv.org/abs/2608.01651
We present Bole, a kernel--runtime co-design that enables efficient tree speculation for hybrid-attention LLMs
https://arxiv.org/list/math.ST/new
If \(T_\star\) is the selected physical trajectory length and \(a_\star=\sqrt m\,T_\star\), a terminal-depth transfer argument yields restricted conductance and warm-start mixing without lazifying either kernel
https://arxiv.org/pdf/2205.01882v5
žÄ35šÄAâ,:ÿ¾¤-e[ÖdN£�ùÞ#¥h‚ @�ô4(kÁ€±,8§ÀAá-x�² %H-HÒ"}�´É�EA räÔ€V[�°@²[P(¤¥í÷ œ!{Z §Í QÑf ZiJ† µ£$ ´¥z¨�>J@Úò[Ð…¡äŒ0(…‘¦ b`ÐQrFY J‚ц8!Z •0–’*MµúíåK¸úX¯ëvÿÁ³í®Ù6ûº›ÍÌ'c³#³éÍ»j]î~ÌäsV°7ë‘QI=0R%ŒßàÕ«öc˜} >
https://arxiv.org/pdf/2608.00785
*¥ä¸"ï Ñ¥îå4‘XÚâ¢Ô]滉¼³`Yd)©$’Þéw©(P©¯\éw™÷»¼ó²’´Åe©»$ºS IG–R¯¸Ç¼´Å%‘:V‹ûéŸÍ¶g¿Á{*ÆŠ´ÑŠ$ðï ðv˜búyxZü¹ç1ì—ËphNß"lŽÍ€ >´›ïþ=ÔÝðÈêó9œ¶ÍŸï^1ãÏõ1”>"½þñ©m‡S;„wün ¶´ ´ºÒ*áj§ò[¶çGx»Âð.‹Ÿ±¾¹½Ú›�7ûp•� Ïi¸†®
https://arxiv.org/pdf/2608.02854v1
�“kñP`úûÜïž8‡„È 4GŽ´HQ@æ%¤R› Ø�«F¼@Ë~„Î9¡ (B9ãìÖ5ÎOS«7WŸ›k¬zSÛD–ëØn©õ> endobj 9 0 obj > stream xœ�ZYsÛ8~ß_ÁÇxS“7P55U–ïC¶#ɇ¼µ´ÍXÜØ’‡’g&óë·›% $¡òT9‘Ùh ___”Iš¤ !‰„ÿiB|°„2øà KYBDÂ$|È„+øP‰`ð¡A_&Ä$RÊ„¦‰RðAÍàƒ&&5°Db$|ð„¤œ&TÀ&°
https://arxiv.org/abs/1202.3424
, dust particles), but may also be 1-d or 2-d periodic arrays of "target unit cells", which can be used to study absorption, scattering, and electric fields around arrays of nanostructures
https://arxiv.org/list/cs.DC/new
SE)
Automating GPU kernel optimization remains difficult in practice: generated variants can violate correctness constraints, runtime measurements are noisy, and search often stalls early
https://arxiv.org/list/cs.NA/new
NA)
Imaging a target sample in near-field scanning optical microscopy (NSOM) is fundamentally limited by measurement artifacts and data contamination from multiple probe-sample scattering
https://arxiv.org/list/cs.CR/new
We also show that coarse-to-fine label selection can create near-perfect measured correlation without learned dependence
https://arxiv.org/html/2508.20101v1
In an empirical application, we demonstrate how the model can be applied to financial stock networks