Tootfinder

Week in wildlife: an ostrich on the lam, a tortoise crossing a road and surfing seals
https://www.theguardian.com/environment/gallery/2026/apr/10/week-in-wildlife-an-ostric…

Coming face to face with a probable psychopath was enough to make Dr Leanne ten Brinke rethink her career choices.
Early in her 20s, while studying forensic psychology in Halifax, in the Canadian province of Nova Scotia,
Ten Brinke was volunteering at a parole office, which would hold weekly group meetings for released sex offenders.
“Most of the men showed contrition,” says Ten Brinke.
“They really seemed to recognise the damage that they had done.”
Except f…

Texans agree to $7M extension with Trent Brown, shoring up offensive line after recent trades https://www.foxsports.com/articles/nfl/texans-agree-to-7m-extension-with-trent-brown-shoring-up-offensive-line-after-rece…

Replaced article(s) found for cs.OS. https://arxiv.org/list/cs.OS/new
[1/1]:
- Flare: Anomaly Diagnostics for Divergent LLM Training in GPU Clusters of Thousand-Plus Scale
Weihao Cui, Ji Zhang, Han Zhao, Chao Liu, Jian Sha, Bingsheng He, Minyi Guo, Quan Chen
https://arxiv.org/abs/2502.05413 https://mastoxiv.page/@arXiv_csOS_bot/113983966659919298
- Towards High-Goodput LLM Serving with Prefill-decode Multiplexing
Chen, Cui, Zhao, Xu, Fan, Chen, Zhou, Sun, He, Chen
https://arxiv.org/abs/2504.14489 https://mastoxiv.page/@arXiv_csOS_bot/114380402335312857
- Scaling Data Center TCP to Terabits with Laminar
Rajath Shashidhara, Antoine Kaufmann, Simon Peter
https://arxiv.org/abs/2504.19058 https://mastoxiv.page/@arXiv_csNI_bot/114420037697903281
toXiv_bot_toot

Great Britain has only two days of fossil gas stored
after a decline in energy reserves,
as more tankers carrying liquefied natural gas (LNG) are diverted from their course to Europe towards Asia because of the Iran war.
https://www.

I am so sorry for those who cannot find anything to eat better than the dogshit in Fascist boot treads. @… https://types.pl/@krismicinski/116189695831443587

Robust Multiagent Collaboration Through Weighted Max-Min T-Joins
Sharareh Alipour
https://arxiv.org/abs/2602.07720 https://arxiv.org/pdf/2602.07720 https://arxiv.org/html/2602.07720
arXiv:2602.07720v1 Announce Type: new
Abstract: Many multiagent tasks -- such as reviewer assignment, coalition formation, or fair resource allocation -- require selecting a group of agents such that collaboration remains effective even in the worst case. The \emph{weighted max-min $T$-join problem} formalizes this challenge by seeking a subset of vertices whose minimum-weight matching is maximized, thereby ensuring robust outcomes against unfavorable pairings.
We advance the study of this problem in several directions. First, we design an algorithm that computes an upper bound for the \emph{weighted max-min $2k$-matching problem}, where the chosen set must contain exactly $2k$ vertices. Building on this bound, we develop a general algorithm with a \emph{$2 \ln n$-approximation guarantee} that runs in $O(n^4)$ time. Second, using ear decompositions, we propose another upper bound for the weighted max-min $T$-join cost. We also show that the problem can be solved exactly when edge weights belong to $\{1,2\}$.
Finally, we evaluate our methods on real collaboration datasets. Experiments show that the lower bounds from our approximation algorithm and the upper bounds from the ear decomposition method are consistently close, yielding empirically small constant-factor approximations. Overall, our results highlight both the theoretical significance and practical value of weighted max-min $T$-joins as a framework for fair and robust group formation in multiagent systems.
toXiv_bot_toot

It is 2037.
You are being paid $7250/hour for your services. (Before you get too excited, a can of cola costs $129, and so does 15 seconds of LLM tokens.)
There are not many left who can do what you do. You are the tradesperson of your time. It's messy work unclogging these metaphorical pipes, but someone's got to do it.
A decade of nothing-but-vibecoding (artisanal “acoustic" performances aside) has left the world in tatters. The Y2K38 problem looms.
The…

Dear everyone
Ghada Elkhalili is an orphan, the eldest surviving member of her family. She is supporting six other family members in a tent close to the yellow line in northern #Gaza. I have been in touch with her for some months; other people in Gaza whom I'm in touch with and who know her have verified her story.
She is receiving very little support; in the past month she's had …

Help Ghada Survive
Hello, I am Amir Hartt from America and I am raising funds for Ghada Elkhalili from the Gaza Strip, whom I connected with through her sisters Shireen and Angham. She has suffered much loss of loved ones and property in this genocide, and funds are urgently needed to rebuild her life to a self-sustaining level. These funds will go towards food, medical treatment, an emergency evacuation fund, firewood, and securing and reparing shelter. Funds will be sent via SWIFT transfer to Ghada's IBAN with …

A last and vital lesson of the conflict is that mowing the grass
— using blunt force against immediate threats with no long-term plan for success
— has only seeded the lawn with wider problems.
The list is long:
The Iranian regime is battered but intact, weaker in many respects but even nastier and more hard-line in its instincts.
The Strait of Hormuz, geography’s strategic gift to Iran, is now a more potent source of influence for Tehran than its nuclear progra…

Opinion | Here’s How Trump Can Get Us Out of the Mess in Iran
To salvage a decent peace with Iran, President Trump must learn the lessons of his war.