
2025-05-28 07:26:31
Restricted (2 1)-TQFTs supported by thickened and solid tori
Du\v{s}an {\DJ}or{\dj}evi\'c, Danica Kosanovi\'c, Jovana Nikoli\'c, Zoran Petri\'c
https://arxiv.org/abs/2505.21373
Restricted (2 1)-TQFTs supported by thickened and solid tori
Du\v{s}an {\DJ}or{\dj}evi\'c, Danica Kosanovi\'c, Jovana Nikoli\'c, Zoran Petri\'c
https://arxiv.org/abs/2505.21373
On the Erd\H{o}s-Ko-Rado problem of flags with type $\{1, n-3 \}$ of finite sets
Philipp Heering
https://arxiv.org/abs/2506.20556 https://
Weil jetzt sehr viel Empörung unter meinem Post zur Ablehnung der SPD zum Familiennachzug entsteht: Die Abgeordneten konnten nicht anders. Sonst wäre die Koalition geplatzt. Alternative? AfD mit Union? Hm.
Das eigentliche Problem hat zwei Teile:
1. Das Ergebnis der Wahl = keine progressive Mehrheit.
2. Die Prioritäten der SPD in der Koalitionsverhandlung. Eine Katastrophe. (Auch für die SPD.)
Einmal verhandelt, muss die Fraktion so abstimmen - oder Klingbeil stürzen.…
This https://arxiv.org/abs/1512.03127 has been replaced.
link: https://scholar.google.com/scholar?q=a
Arithmetic properties and zeros of the Bergman kernel on a class of quotient domains
Luke D. Edholm, Vikram T. Mathew
https://arxiv.org/abs/2505.20489 http…
The final solution of the Hitchhiker's problem #5
Matja\v{z} Omladi\v{c}, Martin Vuk, Alja\v{z} Zalar
https://arxiv.org/abs/2506.20672 https://
On the convergence of critical points on real algebraic sets and applications to optimization
Saugata Basu, Ali Mohammad-Nezhad
https://arxiv.org/abs/2506.20565
Replaced article(s) found for cs.CE. https://arxiv.org/list/cs.CE/new
[1/1]:
- Solving Inverse Problem for Multi-armed Bandits via Convex Optimization
Hao Zhu, Joschka Boedecker
All-Pairs Shortest Paths with Few Weights per Node
Amir Abboud, Nick Fischer, Ce Jin, Virginia Vassilevska Williams, Zoe Xi
https://arxiv.org/abs/2506.20017
Guarding Offices with Maximum Dispersion
S\'andor P. Fekete, Kai Kobbe, Dominik Krupke, Joseph S. B. Mitchell, Christian Rieck, Christian Scheffer
https://arxiv.org/abs/2506.21307
Replaced article(s) found for quant-ph. https://arxiv.org/list/quant-ph/new
[1/2]:
- Possible consequences for physics of the negative resolution of Tsirelson's problem
Ad\'an Cabello, Marco T\'ulio Quintino, Matthias Kleinmann
Falls ihr übrigens das Problem habt, dass ihr das mit Firefox nicht drucken könnt, nur anzeigen (scheint so zu sein), dann empfehle ich euch die Tastenkombination Umschalt Command 4 auf MacOS. Die macht einen Screenshot, den ihr dann ausdrucken und einscannen könnt.
Folgt mir für mehr Digitalisierungstipps.
Finite groups with nearly half as many cyclic subgroups as elements
Vaibhav Chhajer, Sumana Hatui, Palash Sharma
https://arxiv.org/abs/2506.21163 https://
Replaced article(s) found for stat.ML. https://arxiv.org/list/stat.ML/new
[1/1]:
- High-dimensional Contextual Bandit Problem without Sparsity
Junpei Komiyama, Masaaki Imaizumi
Making Graphs Irregular through Irregularising Walks
Julien Bensmail, Romain Bourneuf, Paul Colinot, Samuel Humeau, Timoth\'ee Martinod
https://arxiv.org/abs/2506.21254
A Flavor of SO(10) Unification with a Spinor Higgs
Juanca Carrasco-Martinez, Lawrence J. Hall, Keisuke Harigaya, Kevin Langhoff
https://arxiv.org/abs/2506.20708
I get mixed feelings when I can create a small reproduction project for an issue caused by a single version bump in a third party dependency. It's nice to know it's not my code, but a fix-release is also out of my control
Today's problem; The compiler in #Kotlin 2.1.20. I've even managed to boil it down to a 1 line change where "2.1.10" works, and "2.1.20" o…
A Taylor-Hood finite element method for the surface Stokes problem without penalization
Alan Demlow, Michael Neilan
https://arxiv.org/abs/2506.20419 https:…
A Framework for Building Data Structures from Communication Protocols
Alexandr Andoni, Shunhua Jiang, Omri Weinstein
https://arxiv.org/abs/2506.20761 https…
Quantum k-SAT Related Hypergraph Problems
Simon-Luca Kremer, Dorian Rudolph, Sevag Gharibian
https://arxiv.org/abs/2506.17066 https://
Just got a small space heater and damn it’s so much more comfortable here now
As a @… fan I’d prefer if my AC/heat pump supported heating mode, but welp it was already installed when I moved here so an electric heater will do it for the 2 days a year it’s actually cold enough for that to be useful here. Getting all that heat from the bedroom to the living room would be a problem anyway.
And I didn’t even need to make a fire hazard in order to use it since a 20A outlet was already around due to the coffee thingy, yay!
It’s been on for just around 40mins and it’s already sooo much better in here (the temp sensor is not on the side the heater is pointing to (the sofa) so it’ll take a while for it to reflect the change specially since this is a big room (kitchen dinner living), but just pointing the heater to where I’m at is enough to make it a comfortable temperature (and probably even way too hot in a bit)).
I’ve been wanting this for a while, but it never felt worth it bc we don’t really have many cold days here. Tho this year we got some more I think and today was specially cold (9~11°C) so I decided to just do it. Extra points bc it was available on fucking iFood of all places so it arrived less than an hour after I ordered it lmao.
Bosonized theory of de Haas-van Alphen quantum oscillation in Fermi liquids
Yuxuan Wang
https://arxiv.org/abs/2506.20735 https://arxi…
This https://arxiv.org/abs/2406.11369 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCG_…
Adaptive Supergeo Design: A Scalable Framework for Geographic Marketing Experiments
Charles Shaw
https://arxiv.org/abs/2506.20499 https://
A Nonlinear Nonlocal Problem for the Caputo Fractional Subdiffusion Equation
Ravshan Ashurov, Rajapboy Saparboyev, Navbahor Nuraliyeva
https://arxiv.org/abs/2506.19516
Replaced article(s) found for cs.SC. https://arxiv.org/list/cs.SC/new
[1/1]:
- A matrix criterion and algorithmic approach for the Peterson hit problem: Part I
Dang Vo Phuc
Hybrid Deep Learning and Signal Processing for Arabic Dialect Recognition in Low-Resource Settings
Ghazal Al-Shwayyat, Omer Nezih Gerek
https://arxiv.org/abs/2506.21386
On the Maximization of Real Sequences
Assal\'e Adj\'e
https://arxiv.org/abs/2506.18409 https://arxiv.org/pdf/2506.18409
Another essential thread from @… ...
https://mamot.fr/@pluralistic/114733317506784669
pluralistic@mamot.fr - A major problem with letting billionaires decide how your country is run is that they will back whichever psycho promises the lowest taxes and least regulation, no matter how completely batshit and unfit that person is:
https://www.hamiltonnolan.com/p/nations-are-people
--
If you'd like an essay-formatted version of this thread to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:
https://pluralistic.net/2025/06/23/billionaires-eh/#galen-weston-is-a-rat
1/
Self-Interacting Dark-Matter Spikes and the Final-Parsec Problem: Bayesian constraints from the NANOGrav 15-Year Gravitational-Wave Background
Shreyas Tiruvaskar, Chris Gordon
https://arxiv.org/abs/2506.18153
Finite energy foliations in the restricted three-body problem
Lei Liu, Pedro A. S. Salom\~ao
https://arxiv.org/abs/2506.17867 https://
Stable Minima of ReLU Neural Networks Suffer from the Curse of Dimensionality: The Neural Shattering Phenomenon
Tongtong Liang, Dan Qiao, Yu-Xiang Wang, Rahul Parhi
https://arxiv.org/abs/2506.20779
Every tech oligarch wants to build an Everything App - because they now have the power to do so, but also because they're completely out of ideas.
This week's issue of my newsletter tackles the rise of the "data-driven" Nothing Manager responsible for building Everything, with the "power" of #GenAI.
Low-order finite element complex with application to a fourth-order elliptic singular perturbation problem
Xuewei Cui, Xuehai Huang
https://arxiv.org/abs/2506.20240
from my link log —
Elementary functions NOT following the IEEE 754 floating-point standard.
http://www.hlsl.co.uk/blog/2020/1/29/ieee754-is-not-followed
saved 2025-02-11
This https://arxiv.org/abs/1907.13457 has been replaced.
link: https://scholar.google.com/scholar?q=a
Weird $\mathbb R$-Factorizable Groups
Evgenii Reznichenko, Ol'ga Sipacheva
https://arxiv.org/abs/2506.18733 https://arxiv.org/pdf…
Replaced article(s) found for math.HO. https://arxiv.org/list/math.HO/new
[1/1]:
- An old number theory problem related to the Legendre symbol
Wenpeng Zhang
End-to-End Learning of Probabilistic Constellation Shaping through Importance Sampling
Shrinivas Chimmalgi, Laurent Schmalen, Vahid Aref
https://arxiv.org/abs/2506.16098
The Optimality of a Nested Generalized Pairwise Group Testing Procedure
Yaakov Malinovsky, Viktor Skorniakov
https://arxiv.org/abs/2506.15797 https://
A progressive (#Mamdani) has a chance of winning the #NYCMayoralRace D primary, so of course billionaires are going to throw money at the problem. But rather than propping up someone more reasonable, they're picking the scummiest, most corrupt piece of shit in the race (
Replaced article(s) found for math.CV. https://arxiv.org/list/math.CV/new
[1/1]:
- On the Commuting Problem of Toeplitz Operators on the Harmonic Bergman Space
H. Iqtaish, I. Louhichi, A. Yousef
Unstable $1$-semiadditivity as classifying Goodwillie towers
Connor Malin
https://arxiv.org/abs/2506.11245 https://arxiv.org/pdf/2506…
Pattern formation and film rupture in a two-dimensional thermocapillary thin-film model of the B\'enard-Marangoni problem
Stefano B\"ohmer, Bastian Hilder, Jonas Jansen
https://arxiv.org/abs/2506.19795
${\sf QMA}={\sf QMA}_1$ with an infinite counter
Stacey Jeffery, Freek Witteveen
https://arxiv.org/abs/2506.15551 https://arxiv.org/p…
Fast and Accurate Reconstruction of Voronoi Generators in Large Tessellations
Carlos M Hernandez-Suarez
https://arxiv.org/abs/2506.19076 https://
Quasi-Monte Carlo with one categorical variable
Valerie N. P. Ho, Art B. Owen, Zexin Pan
https://arxiv.org/abs/2506.16582 https://arx…
Oh, boo, am I irrationally angry about genocide?
Do gently fuck off. https://autistics.life/@VulcanTourist/114659503436582815
Meeting a Challenge raised by Ekhad and Zeilberger related to Stern's Triangle
Jinlong Tang, Guoce Xin
https://arxiv.org/abs/2506.13375 https://…
Topological slow entropy, sequence entropy, and generalized $[T,T^{-1}]$ systems
Nicanor Carrasco-Vargas
https://arxiv.org/abs/2506.17932 https://
A Two-Operator Calculus for Arithmetic-Progression Paths in the Collatz Graph
Sebastian Angermund
https://arxiv.org/abs/2506.19115 https://
The Word Problem for Products of Symmetric Groups
Hans U. Simon
https://arxiv.org/abs/2506.13655 https://arxiv.org/pdf/2506.13655
Why AI can't possibly make you more productive; long
#AI and "productivity", some thoughts:
Productivity is a concept that isn't entirely meaningless outside the context of capitalism, but it's a concept that is heavily inflected in a capitalist context. In many uses today it effectively means "how much you can satisfy and/or exceed your boss' expectations." This is not really what it should mean: even in an anarchist utopia, people would care about things like how many shirts they can produce in a week, although in an "I'd like to voluntarily help more people" way rather than an "I need to meet this quota to earn my survival" way. But let's roll with this definition for a second, because it's almost certainly what your boss means when they say "productivity", and understanding that word in a different (even if truer) sense is therefore inherently dangerous.
Accepting "productivity" to mean "satisfying your boss' expectations," I will now claim: the use of generative AI cannot increase your productivity.
Before I dive in, it's imperative to note that the big generative models which most people think of as constituting "AI" today are evil. They are 1: pouring fuel on our burning planet, 2: psychologically strip-mining a class of data laborers who are exploited for their precarity, 3: enclosing, exploiting, and polluting the digital commons, and 4: stealing labor from broad classes of people many of whom are otherwise glad to give that labor away for free provided they get a simple acknowledgement in return. Any of these four "ethical issues" should be enough *alone* to cause everyone to simply not use the technology. These ethical issues are the reason that I do not use generative AI right now, except for in extremely extenuating circumstances. These issues are also convincing for a wide range of people I talk to, from experts to those with no computer science background. So before I launch into a critique of the effectiveness of generative AI, I want to emphasize that such a critique should be entirely unnecessary.
But back to my thesis: generative AI cannot increase your productivity, where "productivity" has been defined as "how much you can satisfy and/or exceed your boss' expectations."
Why? In fact, what the fuck? Every AI booster I've met has claimed the opposite. They've given me personal examples of time saved by using generative AI. Some of them even truly believe this. Sometimes I even believe they saved time without horribly compromising on quality (and often, your boss doesn't care about quality anyways if the lack of quality is hard to measure of doesn't seem likely to impact short-term sales/feedback/revenue). So if generative AI genuinely lets you write more emails in a shorter period of time, or close more tickets, or something else along these lines, how can I say it isn't increasing your ability to meet your boss' expectations?
The problem is simple: your boss' expectations are not a fixed target. Never have been. In virtue of being someone who oversees and pays wages to others under capitalism, your boss' game has always been: pay you less than the worth of your labor, so that they can accumulate profit and this more capital to remain in charge instead of being forced into working for a wage themselves. Sure, there are layers of manservant caught in between who aren't fully in this mode, but they are irrelevant to this analysis. It matters not how much you please your manager if your CEO thinks your work is not worth the wages you are being paid. And using AI actively lowers the value of your work relative to your wages.
Why do I say that? It's actually true in several ways. The most obvious: using generative AI lowers the quality of your work, because the work it produces is shot through with errors, and when your job is reduced to proofreading slop, you are bound to tire a bit, relax your diligence, and let some mistakes through. More than you would have if you are actually doing and taking pride in the work. Examples are innumerable and frequent, from journalists to lawyers to programmers, and we laugh at them "haha how stupid to not check whether the books the AI reviewed for you actually existed!" but on a deeper level if we're honest we know we'd eventually make the same mistake ourselves (bonus game: spot the swipe-typing typos I missed in this post; I'm sure there will be some).
But using generative AI also lowers the value of your work in another much more frightening way: in this era of hype, it demonstrates to your boss that you could be replaced by AI. The more you use it, and no matter how much you can see that your human skills are really necessary to correct its mistakes, the more it appears to your boss that they should hire the AI instead of you. Or perhaps retain 10% of the people in roles like yours to manage the AI doing the other 90% of the work. Paradoxically, the *more* you get done in terms of raw output using generative AI, the more it looks to your boss as if there's an opportunity to get enough work done with even fewer expensive humans. Of course, the decision to fire you and lean more heavily into AI isn't really a good one for long-term profits and success, but the modern boss did not get where they are by considering long-term profits. By using AI, you are merely demonstrating your redundancy, and the more you get done with it, the more redundant you seem.
In fact, there's even a third dimension to this: by using generative AI, you're also providing its purveyors with invaluable training data that allows them to make it better at replacing you. It's generally quite shitty right now, but the more use it gets by competent & clever people, the better it can become at the tasks those specific people use it for. Using the currently-popular algorithm family, there are limits to this; I'm not saying it will eventually transcend the mediocrity it's entwined with. But it can absolutely go from underwhelmingly mediocre to almost-reasonably mediocre with the right training data, and data from prompting sessions is both rarer and more useful than the base datasets it's built on.
For all of these reasons, using generative AI in your job is a mistake that will likely lead to your future unemployment. To reiterate, you should already not be using it because it is evil and causes specific and inexcusable harms, but in case like so many you just don't care about those harms, I've just explained to you why for entirely selfish reasons you should not use it.
If you're in a position where your boss is forcing you to use it, my condolences. I suggest leaning into its failures instead of trying to get the most out of it, and as much as possible, showing your boss very clearly how it wastes your time and makes things slower. Also, point out the dangers of legal liability for its mistakes, and make sure your boss is aware of the degree to which any of your AI-eager coworkers are producing low-quality work that harms organizational goals.
Also, if you've read this far and aren't yet of an anarchist mindset, I encourage you to think about the implications of firing 75% of (at least the white-collar) workforce in order to make more profit while fueling the climate crisis and in most cases also propping up dictatorial figureheads in government. When *either* the AI bubble bursts *or* if the techbros get to live out the beginnings of their worker-replacement fantasies, there are going to be an unimaginable number of economically desperate people living in increasingly expensive times. I'm the kind of optimist who thinks that the resulting social crucible, though perhaps through terrible violence, will lead to deep social changes that effectively unseat from power the ultra-rich that continue to drag us all down this destructive path, and I think its worth some thinking now about what you might want the succeeding stable social configuration to look like so you can advocate towards that during points of malleability.
As others have said more eloquently, generative AI *should* be a technology that makes human lives on average easier, and it would be were it developed & controlled by humanists. The only reason that it's not, is that it's developed and controlled by terrible greedy people who use their unfairly hoarded wealth to immiserate the rest of us in order to maintain their dominance. In the long run, for our very survival, we need to depose them, and I look forward to what the term "generative AI" will mean after that finally happens.
"The big problem is 'bottlenecks' that make it harder to produce housing, expand energy production, or build new roads and bridges."
vs.
"The big problem is that big corporations have way too much power over our economy and our government."
By 12pts all voters and by 42pts Dem voters prefer the second statement. They're right!
AbRank: A Benchmark Dataset and Metric-Learning Framework for Antibody-Antigen Affinity Ranking
Chunan Liu, Aurelien Pelissier, Yanjun Shao, Lilian Denzler, Andrew C. R. Martin, Brooks Paige, Mariia Rodriguez Martinez
https://arxiv.org/abs/2506.17857
Asymptotic Plateau problem for $2$-convex hypersurface in $\mathbb{H}^4$
Defa Chen, Zhenan Sui, Letao Sun
https://arxiv.org/abs/2506.00565 https://
The maximum-average subtensor problem: equilibrium and out-of-equilibrium properties
Vittorio Erba, Nathan Malo Kupferschmid, Rodrigo P\'erez Ortiz, Lenka Zdeborov\'a
https://arxiv.org/abs/2506.15400
This https://arxiv.org/abs/1907.13457 has been replaced.
link: https://scholar.google.com/scholar?q=a
This https://arxiv.org/abs/2412.16740 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…
There’s exactly 1 narrow way that it’s true. Before widespread #WFH, attackers often had an insurmountable barrier: no way into the business network from the Internet. At the last gig (2008) where I had to visit a “workplace” regularly, inbound remote access was officially non-existent & outbound Internet access all went through restrictive web proxies.
I like @…’s analysis here in many respects, both its broad conclusion (when the hype dies down, the useful parts remain and we take them for granted as normal tools), and this gem here:
Machine learning is well-suited for ❝any problem where we don’t actually know the rules and where the cost of a wrong answer is significantly lower than the benefit of a right answer.❞
1/2 https://infosec.exchange/@david_chisnall/112716199046923540
Non-individuality and experience
Raoni Arroyo
https://arxiv.org/abs/2505.15627 https://arxiv.org/pdf/2505.15627
A Minkowski problem for $\alpha$-concave functions via optimal transport
Xiao Li, Nguyen Nguyen, Deping Ye
https://arxiv.org/abs/2506.14735 https://…
Free boundary regularity and well-posedness of physical solutions to the supercooled Stefan problem
Sebastian Munoz
https://arxiv.org/abs/2506.18741 https:…
Large grid subsets without many cospherical points
Zichao Dong, Zijian Xu
https://arxiv.org/abs/2506.18113 https://arxiv.org/pdf/2506…
A remarkable dynamical symmetry of the Landau problem
Tekin Dereli, Philippe Nounahon, Todor Popov
https://arxiv.org/abs/2506.11642 https://
Detection and Reconstruction of a Random Hypergraph from Noisy Graph Projection
Shuyang Gong, Zhangsong Li, Qiheng Xu
https://arxiv.org/abs/2506.17527 http…
Semirandom Planted Clique via 1-norm Isometry Property
Venkatesan Guruswami, Hsin-Po Wang
https://arxiv.org/abs/2506.17916 https://ar…
Physics-Informed Neural Networks for the Korteweg-de Vries Equation for Internal Solitary Wave Problem: Forward Simulation and Inverse Parameter Estimation
Ming Kang, Hang Li, Qiwen Tan, Zhan Wang, Ruipeng Li, Junfang Zhao, Hui Xiang, Dixia Fan
https://arxiv.org/abs/2506.14236
Isoperimetric Problem and Weierstrass Necessary Condition for Fractional Calculus of Variations
Shakir Sh. Yusubov, Shikhi Sh. Yusubov, Elimhan N. Mahmudov
https://arxiv.org/abs/2506.12926
Partial Domination in Some Geometric Intersection Graphs and Some Complexity Results
Madhura Dutta, Anil Maheshwari, Subhas C. Nandy, Bodhayan Roy
https://arxiv.org/abs/2505.15949
Witnessing PPT entanglement via rank analysis of (sub)matrices
Aabhas Gulati
https://arxiv.org/abs/2506.11346 https://arxiv.org/pdf/2…
Two Higgs Doublet Solutions to the Strong CP Problem
Quentin Bonnefoy, Lawrence J. Hall, Claudio Andrea Manzari, Bea Noether
https://arxiv.org/abs/2506.13853
Maximum Reachability Orientation of Mixed Graphs
Florian H\"orsch
https://arxiv.org/abs/2506.16171 https://arxiv.org/pdf/2506.16…
Low regularity well-posedness of nonlocal dispersive perturbations of Burgers' equation
Luc Molinet, Didier Pilod, St\'ephane Vento
https://arxiv.org/abs/2506.17801
Finite-Time Information-Theoretic Bounds in Queueing Control
Yujie Liu, Vincent Y. F. Tan, Yunbei Xu
https://arxiv.org/abs/2506.18278 https://
Generative model for optimal density estimation on unknown manifold
Arthur St\'ephanovitch
https://arxiv.org/abs/2506.19587 https://
Simultaneous recovery of corroded boundaries and admittance using the Kohn-Vogelius method
Moustapha Essahraoui, Elmehdi Cherrat, Lekbir Afraites, Julius Fergy Tiongson Rabago
https://arxiv.org/abs/2506.17938
Triangle-free subsets of the Hypercube
Padmini Mukkamala
https://arxiv.org/abs/2506.18782 https://arxiv.org/pdf/2506.18782
The Densest SWAMP problem: subhypergraphs with arbitrary monotonic partial edge rewards
Vedangi Bengali, Nikolaj Tatti, Iiro Kumpulainen, Florian Adriaens, Nate Veldt
https://arxiv.org/abs/2506.12998
An extension of Dembo-Hammer's reduction algorithm for the 0-1 knapsack problem
Yang Yang
https://arxiv.org/abs/2506.06138 https://
Analysis and conditional optimization of projection estimates for the distribution of random variable using Legendre polynomials
Tatyana A. Averina, Konstantin A. Rybakov
https://arxiv.org/abs/2506.14822
Accuracy and componentwise accuracy in multilinear PageRank
Mehdi Najafi Kalyani, Federico Poloni
https://arxiv.org/abs/2506.18356 https://
Large solutions to semilinear equations for subordinate Laplacians in $C^{1,1}$ bounded open sets
Indranil Chowdhury, Zoran Vondra\v{c}ek, Vanja Wagner
https://arxiv.org/abs/2506.13462
Optimal Convergence Rates of Deep Neural Network Classifiers
Zihan Zhang, Lei Shi, Ding-Xuan Zhou
https://arxiv.org/abs/2506.14899 https://
Quantum SAT Problems with Finite Sets of Projectors are Complete for a Plethora of Classes
Ricardo Rivera Cardoso, Alex Meiburg, Daniel Nagaj
https://arxiv.org/abs/2506.07244
Contextual Pattern Mining and Counting
Ling Li, Daniel Gibney, Sharma V. Thankachan, Solon P. Pissis, Grigorios Loukides
https://arxiv.org/abs/2506.17613 h…
Large solutions for subordinate spectral Laplacian
Ivan Bio\v{c}i\'c, Vanja Wagner
https://arxiv.org/abs/2506.16780 https://arxiv…
Spectral Tur\'{a}n problem of non-bipartite graphs: Forbidden books
Ruifang Liu, Lu Miao
https://arxiv.org/abs/2506.04884 https://
This https://arxiv.org/abs/2411.13348 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCC_…
Berezin-Li-Yau inequality for mixed local-nonlocal Dirichlet-Laplacian
Aidyn Kassymov, Berikbol T. Torebek
https://arxiv.org/abs/2506.17780 https://…
On Domination Exponents for Pairs of Graphs
Grigoriy Blekherman, Annie Raymond, Alexander Razborov, Fan Wei
https://arxiv.org/abs/2506.12151 https://
Cazenave-Dickstein-Weissler-type extension of Fujita's problem on Heisenberg groups
Mokhtar Kirane, Ahmad Z. Fino, Berikbol T. Torebek, Zineb Sabbagh
https://arxiv.org/abs/2506.10611
Algebraic aspects of the polynomial Littlewood-Offord problem
Zhihan Jin, Matthew Kwan, Lisa Sauermann, Yiting Wang
https://arxiv.org/abs/2505.23335 https:…
Generalized Poisson kernel and solution of the Dirichlet problem for the radial Schr\"odinger equation
V\'ictor A Vicente-Ben\'itez
https://arxiv.org/abs/2506.10273
Modica type estimates and curvature results for overdetermined $p$-Laplace problems
Yuanyuan Lian, Jing Wu
https://arxiv.org/abs/2506.14579 https://…
Melting and freezing rates of the radial interior Stefan problem in two dimension
Jeongheon Park
https://arxiv.org/abs/2506.13175 https://