Tootfinder

Genuinely torn about this. Keeping people safe from a roving right-wing murderer does seem prudent. But I don’t want to send out the message that this is a way to get a protest cancelled.
❝The No Kings coalition that organized protests across the US today is cancelling all demonstrations in Minnesota that have not already started after two lawmakers were shot, Reuters reports.
Indivisible said on Bluesky: “Governor Walz has recommended that we cancel No Kings events across Minnesota because the individual who assassinated a Democratic lawmaker is still at large.”❞
https://www.theguardian.com/us-news/live/2025/jun/14/trump-birthday-military-parade-no-kings-protest-live-updates

""Thousands of demonstrators turned out to protest the trump Administration in St.Paul on Saturday, even as dozens of other "No Kings" events across Minnesota were canceled after two lawmakers and their spouses were shot overnight in what Gov. Tim Waltz called "targeted political violence."

‘No Kings’ rally held in St. Paul; other MN events canceled after lawmaker shootings
The event at the State Capitol in St. Paul appeared to be going ahead as planned.

Protesters crowd into streets, parks, and plazas at anti-Trump 'No Kings' demonstrations across US. Follow live updates. (The Boston Globe)
https://www.bostonglobe.com/2025/06/14/nation/trump-military-parade-protests-live-updates/
http://www.memeorandum.com/250614/p78#a250614p78

I'll say this for #Trump, he gets the bigliest turn out for demonstrations. Nobody ever got biglier! #NoKings

»Brot und Spiele – Tech-Konzerne sponsern heimlich Trumps umstrittene Militärparade:
Donald Trump droht Demonstranten mit "sehr großer Gewalt", Datenschützer warnen vor Überwachung und Repressalien durch die Behörden«
Kein weiteren Kommentar dazu, denn es ist so wie schon lange vorhergesehen und wie seit je-und-eh!
😠

Tech-Konzerne sponsern heimlich Trumps umstrittene Militärparade
Donald Trump droht Demonstranten mit "sehr großer Gewalt", Datenschützer warnen vor Überwachung und Repressalien durch die Behörden

🚀 Demonstrates practical #AI agent development without complex abstractions or extensive engineering overhead
https://ampcode.com/how-to-build-an-agent

Mitigating Spurious Correlations in LLMs via Causality-Aware Post-Training
Shurui Gui, Shuiwang Ji
https://arxiv.org/abs/2506.09433 https://

Mitigating Spurious Correlations in LLMs via Causality-Aware Post-Training
While large language models (LLMs) have demonstrated remarkable capabilities in language modeling, recent studies reveal that they often fail on out-of-distribution (OOD) samples due to spurious correlations acquired during pre-training. Here, we aim to mitigate such spurious correlations through causality-aware post-training (CAPT). By decomposing a biased prediction into two unbiased steps, known as \textit{event estimation} and \textit{event intervention}, we reduce LLMs' pre-training biases…

Soeben eröffnet der newsroom der #nytimes den nachrichten-stream zu den #nokings -protesten. In den AP-News wird schon von einem überwältigenden Zulauf berichtet. Wir befinden uns mitten in der größten Massendemo der #USA

No Kings Protests Across the U.S. Oppose Trump Policies: Live Updates
Demonstrators gathered in roughly 2,000 communities large and small, with few reports of unrest. Many protests on the East Coast have wound down, but demonstrations were just beginning in Los Angeles, the epicenter of anger over the Trump administration’s immigration crackdown.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems
Val Andrei Fajardo, David B. Emerson, Amandeep Singh, Veronica Chatrath, Marcelo Lotif, Ravi Theja, Alex Cheung, Izuki Matsubi
https://arxiv.org/abs/2506.09200

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems
Retrieval-augmented generation (RAG) systems have been shown to be effective in addressing many of the drawbacks of relying solely on the parametric memory of large language models. Recent work has demonstrated that RAG systems can be improved via fine-tuning of their retriever and generator models. In this work, we introduce FedRAG, a framework for fine-tuning RAG systems across centralized and federated architectures. FedRAG supports state-of-the-art fine-tuning methods, offering a simple and…

Beyond Overconfidence: Foundation Models Redefine Calibration in Deep Neural Networks
Achim Hekler, Lukas Kuhn, Florian Buettner
https://arxiv.org/abs/2506.09593

Beyond Overconfidence: Foundation Models Redefine Calibration in Deep Neural Networks
Reliable uncertainty calibration is essential for safely deploying deep neural networks in high-stakes applications. Deep neural networks are known to exhibit systematic overconfidence, especially under distribution shifts. Although foundation models such as ConvNeXt, EVA and BEiT have demonstrated significant improvements in predictive performance, their calibration properties remain underexplored. This paper presents a comprehensive investigation into the calibration behavior of foundation mo…