Tootfinder

Sen. Murkowski, feeling 'cheated' by Trump actions against wind and solar, says she'll go to bat for Alaska projects (Alex DeMarban/Anchorage Daily News)
https://www.adn.com/business-economy/energy/2025/07/18/sen-murkowski-feeling-cheated-by-trump-actions-against-wind-and-solar-says-shell-go-to-bat-for-alaska-projects/
http://www.memeorandum.com/250719/p31#a250719p31

Will Rashee Rice be suspended? Here's how many games Chiefs WR could miss following hit-and-run sentencing

https://www.cbssports.com/nfl/news/will-ra

Ashton Jeanty has two words following strong preseason performance https://www.sportingnews.com/us/nfl/las-vegas-raiders/news/ashton-jeanty-has-two-words-following-strong-preseason-performance/32…

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Raiders 2025 Training Camp Preview: Storylines worth following, dates to know and more https://www.raiders.com/news/raiders-2025-training-camp-preview-storylines-dates-to-know-geno-smith-maxx-crosby-ashton-jeanty

HeroBench: A Benchmark for Long-Horizon Planning and Structured Reasoning in Virtual Worlds
Petr Anokhin, Roman Khalikov, Stefan Rebrikov, Viktor Volkov, Artyom Sorokin, Vincent Bissonnette
https://arxiv.org/abs/2508.12782

HeroBench: A Benchmark for Long-Horizon Planning and Structured Reasoning in Virtual Worlds
Large language models (LLMs) have shown remarkable capabilities in isolated step-by-step reasoning tasks such as mathematics and programming, but their proficiency in long-horizon planning, where solutions require extended, structured sequences of interdependent actions, remains underexplored. Existing benchmarks typically assess LLMs through abstract or low-dimensional algorithmic tasks, failing to capture the complexity of realistic planning environments. We introduce HeroBench, a novel bench…

from my link log —
Rain of Fire Falling: The crash of American Airlines flight 191.
https://admiralcloudberg.medium.com/rain-of-fire-falling-the-crash-of-american-airlines-flight-191-e17ffc5369e5

Rain of Fire Falling: The crash of American Airlines flight 191
Note: this accident was previously featured in episode 8 of the plane crash series on October 28th, 2017, prior to the series’ arrival on Medium. This article is written without reference to and…

Many people are detained at U.S. airports for reasons they find arbitrary and mysterious.
I got lucky—when I was stopped by Customs and Border Protection last week, after flying to Los Angeles from Melbourne, a border agent told me, explicitly and proudly, why I’d been pulled out of the customs line.
“Look, we both know why you are here,” the agent told me.
He identified himself to me as Adam, though his colleagues referred to him as Officer Martinez.
When I said that…

How My Reporting on the Columbia Protests Led to My Deportation
Alistair Kitchen on being detained at Los Angeles International Airport and sent back to Australia because of his reporting on the protests at Columbia University criticizing Israel’s actions in Gaza.

The Tech DEI Backlash -- The Changing Landscape of Diversity, Equity, and Inclusion in Software Engineering
Sonja M. Hyrynsalmi, Mary Sanchez-Gordon, Anna Szlavi, Letizia Jaccheri
https://arxiv.org/abs/2506.14232

The Tech DEI Backlash -- The Changing Landscape of Diversity, Equity, and Inclusion in Software Engineering
Not long ago, Diversity, Equity, and Inclusion (DEI) initiatives were a top priority for leading software companies. However, in a short period, a wave of backlash has led many firms to re-assess their DEI strategies. Responding to this DEI backlash is crucial in academic research, especially because, currently, little scholarly research has been done on it. In this paper, therefore, we have set forth the following research question (RQ): "How have leading software companies changed their DEI s…

GALA: Can Graph-Augmented Large Language Model Agentic Workflows Elevate Root Cause Analysis?
Yifang Tian, Yaming Liu, Zichun Chong, Zihang Huang, Hans-Arno Jacobsen
https://arxiv.org/abs/2508.12472

GALA: Can Graph-Augmented Large Language Model Agentic Workflows Elevate Root Cause Analysis?
Root cause analysis (RCA) in microservice systems is challenging, requiring on-call engineers to rapidly diagnose failures across heterogeneous telemetry such as metrics, logs, and traces. Traditional RCA methods often focus on single modalities or merely rank suspect services, falling short of providing actionable diagnostic insights with remediation guidance. This paper introduces GALA, a novel multi-modal framework that combines statistical causal inference with LLM-driven iterative reasonin…