Tootfinder

Using the Arc Browser is one of the strongest possible signals today that the user sees nothing of value or to respect in the open Internet. A tool based on stripping everything it finds to give you an expensive answer that's probably worse than what a normal web search would have given ya. An egocentric product that sees everything outside of the user as mere content

This https://arxiv.org/abs/2405.15461 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCE_…

Optimal market-neutral currency trading on the cryptocurrency platform
This research proposes a novel arbitrage approach with respect to multivariate pair trading called Optimal Trading Technique (OTT). We introduce the method to selectively form a "bucket" of fiat currencies anchored to cryptocurrency for simultaneously monitoring and exploiting trading opportunities. To handle the quantitative conflicts that arise when receiving multiple trading signals, a bi-objective convex optimization process is designed to cater to the investor's preference between profitab…

2024 Dallas Cowboys Mock Draft: Fixing Problem Areas https://www.yardbarker.com/nfl/articles/2024_dallas_cowboys_mock_draft_fixing_problem_areas/s1_16880_40169173

2024 Dallas Cowboys Mock Draft: Fixing Problem Areas
After yet another disappointing playoff performance, the Dallas Cowboys look to the 2024 NFL Draft in the hopes of improving. The Dallas Cowboys, as a team, and talented assembled, are too good to be this disappointing. As a matter of fact, leading the league in points score and fewest points allowed should mean something. Yet, Dallas finds themselves reaching for answers after leaving the postseason early. While the Cowboys do need an infusion of youthful talent at certain positions, the core …

#Turkey’s main opposition party retained its control over key cities and made huge gains elsewhere in Sunday’s #local #elections, in a major upset to President Recep Tayyip Erdogan, who had set his sights on retaking control of those ur…

Turkey local elections: Opposition makes huge gains in major upset to Erdogan
Turkey's main opposition party has retained its control over key cities and made huge gains in local elections. Preliminary results reported by state media Sunday showed the opposition mayors of Istanbul and Ankara retaining their seats. Their party was leading in 36 provinces. The vote was seen as a barometer of Turkish President Recep Tayyip Erdogan’s popularity as he sought to win back control of the key urban areas he lost to the opposition five years ago, amid a deep economic downturn an…

Dimension formulas for period spaces via motives and species
Annette Huber, Martin Kalck
https://arxiv.org/abs/2405.21053 https://arx…

Dimension formulas for period spaces via motives and species
We apply the structure theory of finite dimensional algebras in order to deduce dimension formulas for spaces of period numbers, i.e., complex numbers defined by integrals of algebraic nature. We get a complete and conceptually clear answer in the case of $1$-periods, generalising classical results like Baker's theorem on the logarithms of algebraic numbers and partial results in Huber--W{ü}stholz \cite{huber-wuestholz}. The application to the case of Mixed Tate Motives (i.e., Multiple Zeta …

Can Large Language Models put 2 and 2 together? Probing for Entailed Arithmetical Relationships
D. Panas, S. Seth, V. Belle
https://arxiv.org/abs/2404.19432 https://arxiv.org/pdf/2404.19432
arXiv:2404.19432v1 Announce Type: new
Abstract: Two major areas of interest in the era of Large Language Models regard questions of what do LLMs know, and if and how they may be able to reason (or rather, approximately reason). Since to date these lines of work progressed largely in parallel (with notable exceptions), we are interested in investigating the intersection: probing for reasoning about the implicitly-held knowledge. Suspecting the performance to be lacking in this area, we use a very simple set-up of comparisons between cardinalities associated with elements of various subjects (e.g. the number of legs a bird has versus the number of wheels on a tricycle). We empirically demonstrate that although LLMs make steady progress in knowledge acquisition and (pseudo)reasoning with each new GPT release, their capabilities are limited to statistical inference only. It is difficult to argue that pure statistical learning can cope with the combinatorial explosion inherent in many commonsense reasoning tasks, especially once arithmetical notions are involved. Further, we argue that bigger is not always better and chasing purely statistical improvements is flawed at the core, since it only exacerbates the dangerous conflation of the production of correct answers with genuine reasoning ability.

Explainable Automatic Grading with Neural Additive Models
Aubrey Condor, Zachary Pardos
https://arxiv.org/abs/2405.00489 https://arxi…

Explainable Automatic Grading with Neural Additive Models
The use of automatic short answer grading (ASAG) models may help alleviate the time burden of grading while encouraging educators to frequently incorporate open-ended items in their curriculum. However, current state-of-the-art ASAG models are large neural networks (NN) often described as "black box", providing no explanation for which characteristics of an input are important for the produced output. This inexplicable nature can be frustrating to teachers and students when trying to interpret,…

Söder ruft zur Hetzjagd gegenüber Schulen und Lehrer*innen auf
https://www.br.de/nachrichten/bayern/aerger-ueber-soeders-gender-aussage-aufruf-zum-anschwaerzen,U87J1Bc

Finite symmetric groups are strongly verbally closed
Olga K. Karimova, Anton A. Klyachko
https://arxiv.org/abs/2405.01179 https://arx…

Finite symmetric groups are strongly verbally closed
Answering a question of A. V. Vasil'ev, we show that each finite symmetric (or alternating) group $H$ is a retract of any group containing $H$ as a verbally closed subgroup.

Explainable Automatic Grading with Neural Additive Models
Aubrey Condor, Zachary Pardos
https://arxiv.org/abs/2405.00489 https://arxi…

Explainable Automatic Grading with Neural Additive Models
The use of automatic short answer grading (ASAG) models may help alleviate the time burden of grading while encouraging educators to frequently incorporate open-ended items in their curriculum. However, current state-of-the-art ASAG models are large neural networks (NN) often described as "black box", providing no explanation for which characteristics of an input are important for the produced output. This inexplicable nature can be frustrating to teachers and students when trying to interpret,…