Tootfinder

Tough Decisions Already Loom For New Raiders Regime Next Offseason https://raiderramble.com/2025/06/28/tough-decisions-already-loom-for-new-raiders-regime-next-offseason/

SCOTUS upholds a Texas law that requires porn websites to verify that their visitors are 18 or older, rejecting a First Amendment challenge to the law (Josh Gerstein/Politico)
https://www.politico.com/live-updates/2…

Yesterday's incredibly dunce-like decisions from SCOTUS reminded me once again why I am refusing to become a member of the US Supreme Court bar.
"I will not be joining the United States Supreme Court (SCOTUS) Bar"
https://www.cavebear.com/cavebear-blog/no-…

This https://arxiv.org/abs/2312.04827 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_eco…

Independence of Irrelevant Decisions in Stochastic Choice
We investigate stochasticity in choice behavior across diverse decisions. Each decision is modeled as a menu of actions with associated outcomes, and a stochastic choice rule assigns probabilities to actions based on the outcome profile. We characterize rules whose predictions are not affected by whether or not additional, irrelevant decisions are included in the model. Our main result is that such rules form the parametric family of mixed-logit rules.

Corporate Deal Making Made Easy: Just Give Donald Trump Personal Power To Approve All Strategic Decisions (Mike Masnick/Techdirt)
https://www.techdirt.com/2025/06/25/corporate-deal-making-made-easy-just-give-donald-trump-personal-power-to-approve-all-strategic-decisions/
http://www.memeorandum.com/250626/p4#a250626p4

“This ruling reaffirms that our laws matter, and that trade decisions can’t be made on the president’s whim.”
It's the 'Rule of Law', Donald!
https://www.theguardian.com/us-news/2025/may/28/us-court-blocks-trump-tariffs?…

'We have all the cards' - Trump says he is ending Canada trade talks
"The World as a Poker Game"
Drawing an overly tight relationship between results and decision quality affects our decisions every day potentially with far-reaching, catastrophic consequences.
- Annie Duke

Dangerous waters - According to Media Watch, "Austen Tayshus" has since last year received more than 90 minutes of airtime on ABC local radio over 11 segments,
https://www.

ABC chair Kim Williams denies interfering with editorial decisions over comedian's radio appearances
Kim Williams has denied interfering in editorial decision-making in order to secure airtime for an Australian comedian.

'History is the study of decisions, not of events' - love this, from Dan Davies 'Unaccountability Machine'. And as an instinctive systems thinker I love even more that he goes on to say 'many decisions are best understood as the outcome of larger systems rather than individual acts of will.'

Interesting interview re #AI:
https://www.sfexaminer.com/news/technology/how-openai-earl…

How OpenAI’s development changed AI’s course
New book: Early decisions had big consequences.

Interesting interview re #AI:
https://www.sfexaminer.com/news/technology/how-openai-earl…

How OpenAI’s development changed AI’s course
New book: Early decisions had big consequences.

The narrative that #AI will do all routine and we can just focus on important/strategic/big picture things works because it tell us that we are oh so smart and special. WE DO THE BIG STUFF.
Newsflash: If your big picture decisions are not grounded in real experience they are gonna end up bullshit.

Carbon-Aware Microservice Deployment for Optimal User Experience on a Budget
Kevin Kreutz, Philipp Wiesner, Monica Vitali
https://arxiv.org/abs/2506.21422 …

Carbon-Aware Microservice Deployment for Optimal User Experience on a Budget
The carbon footprint of data centers has recently become a critical concern. So far, most carbon-aware strategies have focused on leveraging the flexibility of scheduling decisions for batch processing by shifting the time and location of workload executions. However, such approaches cannot be applied to service-oriented cloud applications, since they have to be reachable at every point in time and often at low latencies. We propose a carbon-aware approach for operating microservices under hour…

Is the theory here is that if you let a child know that a particular other kind of person exists, even if there is no overlap between what defines that kind of person and religion, even if that kind of person is statistically likely to be the same religion as the child, then somehow that teaches the child a different religion?!?!?

Simultaneous estimation of the effective reproduction number and the time series of daily infections: Application to Covid-19
Hans R. K\"unsch, Fabio Sigrist
https://arxiv.org/abs/2506.21027

Simultaneous estimation of the effective reproduction number and the time series of daily infections: Application to Covid-19
The time varying effective reproduction number is an important parameter for communication and policy decisions during an epidemic. It is difficult to estimate because it depends on latent variables such as new infections and other characteristics of an epidemic which have to be inferred from available data. In this paper, we present new statistical methods for a popular model which defines the effective reproduction number based on self-exciting dynamics of new infections. Such a model is conc…

This https://arxiv.org/abs/2502.00874 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDL_…

Paper Copilot Position: The Artificial Intelligence and Machine Learning Community Should Adopt a More Transparent and Regulated Peer Review Process
The rapid growth of submissions to top-tier Artificial Intelligence (AI) and Machine Learning (ML) conferences has prompted many venues to transition from closed to open review platforms. Some have fully embraced open peer reviews, allowing public visibility throughout the process, while others adopt hybrid approaches, such as releasing reviews only after final decisions or keeping reviews private despite using open peer review systems. In this work, we analyze the strengths and limitations of …

Data Visualization for Improving Financial Literacy: A Systematic Review
Meng Du, Robert Amor, Kwan-Liu Ma, Burkhard C. W\"unsche
https://arxiv.org/abs/2506.20901

Data Visualization for Improving Financial Literacy: A Systematic Review
Financial literacy empowers individuals to make informed and effective financial decisions, improving their overall financial well-being and security. However, for many people understanding financial concepts can be daunting and only half of US adults are considered financially literate. Data visualization simplifies these concepts, making them accessible and engaging for learners of all ages. This systematic review analyzes 37 research papers exploring the use of data visualization and visual …

Stationary and Non-Stationary Transition Probabilities in Decision Making: Modeling COVID-19 Dynamics
Romario Gildas Foko Tiomela, Serges Love Teutu Talla, Samson Adekola Alagbe, Olawale Nasiru Lawal, Isabella Kemajou-Brown
https://arxiv.org/abs/2505.21519

Stationary and Non-Stationary Transition Probabilities in Decision Making: Modeling COVID-19 Dynamics
This study explores the complexities of stationary and non-stationary transition probabilities within the framework of a Markov Decision Process (MDP), specifically applied to COVID-19. The research highlights the critical role these probabilities play in accurately modeling disease dynamics and informing evidence-based decisions by policymakers and public health authorities. By incorporating both stationary transition probabilities (which assume constant rates of state changes) and non-station…

Beyond Reactive Safety: Risk-Aware LLM Alignment via Long-Horizon Simulation
Chenkai Sun, Denghui Zhang, ChengXiang Zhai, Heng Ji
https://arxiv.org/abs/2506.20949

Beyond Reactive Safety: Risk-Aware LLM Alignment via Long-Horizon Simulation
Given the growing influence of language model-based agents on high-stakes societal decisions, from public policy to healthcare, ensuring their beneficial impact requires understanding the far-reaching implications of their suggestions. We propose a proof-of-concept framework that projects how model-generated advice could propagate through societal systems on a macroscopic scale over time, enabling more robust alignment. To assess the long-term safety awareness of language models, we also introd…

Podcast ep 188: 12 ways to make decision-making easier (and why people who hoard find it so hard to make decisions in the first place!) https://www.overcomecompulsivehoarding.co.uk/podcast-ep-188-decision-making-hoarding-disorder/

Financial literacy, robo-advising, and the demand for human financial advice: Evidence from Italy
David Aristei, Manuela Gallo
https://arxiv.org/abs/2505.20527

Financial literacy, robo-advising, and the demand for human financial advice: Evidence from Italy
This paper investigates the impact of objective financial knowledge, confidence in one's financial skills, and digital financial literacy on individuals' decisions to seek financial advice from robo-advice platforms. Using microdata from the Bank of Italy's survey on adults' "Financial Literacy and Digital Financial Skills in Italy", we find that individuals with greater financial knowledge are less inclined to rely on online services for automated financial advice. On the contrary, confidence …

POLAR: A Pessimistic Model-based Policy Learning Algorithm for Dynamic Treatment Regimes
Ruijia Zhang, Zhengling Qi, Yue Wu, Xiangyu Zhang, Yanxun Xu
https://arxiv.org/abs/2506.20406

POLAR: A Pessimistic Model-based Policy Learning Algorithm for Dynamic Treatment Regimes
Dynamic treatment regimes (DTRs) provide a principled framework for optimizing sequential decision-making in domains where decisions must adapt over time in response to individual trajectories, such as healthcare, education, and digital interventions. However, existing statistical methods often rely on strong positivity assumptions and lack robustness under partial data coverage, while offline reinforcement learning approaches typically focus on average training performance, lack statistical gu…

Who will Raiders prioritize of their pending free agents? https://www.reviewjournal.com/sports/raiders/who-will-raiders-prioritize-of-their-pending-free-agents-3390235/

Evolution of boundedly rational learning in games
Marta C. Couto, Fernando P. Santos, Christian Hilbe
https://arxiv.org/abs/2506.21498 https://

Evolution of boundedly rational learning in games
People make strategic decisions multiple times a day. We act strategically in negotiations, when we coordinate our actions with others, or when we choose with whom to cooperate. The resulting dynamics can be studied with evolutionary game theory. This framework explores how people adapt their decisions over time, in light of how effective their strategies have proven to be. A crucial quantity in respective models is the strength of selection. This quantity regulates how likely individuals switc…

Smoothness Meets Autobidding: Tight Price of Anarchy Bounds for Simultaneous First-Price Auctions
Riccardo Colini-Baldeschi, Sophie Klumper, Twan Kroll, Stefano Leonardi, Guido Sch\"afer, Artem Tsikiridis
https://arxiv.org/abs/2506.20908

Smoothness Meets Autobidding: Tight Price of Anarchy Bounds for Simultaneous First-Price Auctions
Online advertising systems have recently transitioned to autobidding, enabling advertisers to delegate bidding decisions to automated agents. Each advertiser directs their agent to optimize a valuation-dependent objective subject to return-on-investment (ROI) or budget constraints. Given their relevance, there has been a surge in literature studying the liquid welfare price of anarchy (POA) of core auction formats in autobidding, among which simultaneous first-price auctions (FPA). These models…

from my link log —
Toxic Origins, Toxic Decisions: bias in CEO selection towards risk-taking, analysed using polluted Superfund sites.
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5270031
saved 2025-05-31

RFK Jr: People should be able to make their own decisions about vaccines
Sane people: Get covid vax, get MMR vax
RFKJ: Not like that!
#vaccines #InsaneRFK #rfk

An Anarchist Approach to the Undergraduate Mathematics Curriculum
Asia Matthews, Vincent Bouchard
https://arxiv.org/abs/2505.18811 https://

An Anarchist Approach to the Undergraduate Mathematics Curriculum
Contemporary anarchism centers around three tenets: (1) a constant challenge of and resistance to all forms of domination, (2) so-called "prefigurative politics", in which all decisions are made in a manner that is consistent with a set of non-hierarchical values such as equality, decentralization and voluntary cooperation, (3) a focus on diversity and open-endedness (Gordon, 2008). Within this philosophy the notion of end goals becomes moot; progress, then, is measured by process, in which the…

Cowboys' Zack Martin selection one of the greatest picks in past 25 years https://www.si.com/nfl/cowboys/news/dallas-cowboys-zack-martin-selection-one-greatest-picks-past-25-years

#TotalEnergies investiert 160 Mio. € in sechs neue #Batteriespeicherprojekte mit 221 MW in #Deutschland.
Die Anlagen, entwickelt von Tochterunternehmen

Germany: TotalEnergies Pursues Growth in Electricity by Launching Six New Battery Storage Projects
Paris, March 26, 2025 – On the occasion of Patrick Pouyanné’s participation in the Europe 2025 conference in Berlin, and in connection with the Company’s integrated development in the country’s electricity sector, TotalEnergies is announcing investment decisions for six battery storage projects.

Subtooting since people in the original thread wanted it to be over, but selfishly tagging @… and @… whose opinions I value...
I think that saying "we are not a supply chain" is exactly what open-source maintainers should be doing right now in response to "open source supply chain security" threads.
I can't claim to be an expert and don't maintain any important FOSS stuff, but I do release almost all of my code under open licenses, and I do use many open source libraries, and I have felt the pain of needing to replace an unmaintained library.
There's a certain small-to-mid-scale class of program, including many open-source libraries, which can be built/maintained by a single person, and which to my mind best operate on a "snake growth" model: incremental changes/fixes, punctuated by periodic "skin-shedding" phases where make rewrites or version updates happen. These projects aren't immortal either: as the whole tech landscape around them changes, they become unnecessary and/or people lose interest, so they go unmaintained and eventually break. Each time one of their dependencies breaks (or has a skin-shedding moment) there's a higher probability that they break or shed too, as maintenance needs shoot up at these junctures. Unless you're a company trying to make money from a single long-lived app, it's actually okay that software churns like this, and if you're a company trying to make money, your priorities absolutely should not factor into any decisions people making FOSS software make: we're trying (and to a huge extent succeeding) to make a better world (and/or just have fun with our own hobbies share that fun with others) that leaves behind the corrosive & planet-destroying plague which is capitalism, and you're trying to personally enrich yourself by embracing that plague. The fact that capitalism is *evil* is not an incidental thing in this discussion.
To make an imperfect analogy, imagine that the peasants of some domain have set up a really-free-market, where they provide each other with free stuff to help each other survive, sometimes doing some barter perhaps but mostly just everyone bringing their surplus. Now imagine the lord of the domain, who is the source of these peasants' immiseration, goes to this market secretly & takes some berries, which he uses as one ingredient in delicious tarts that he then sells for profit. But then the berry-bringer stops showing up to the free market, or starts bringing a different kind of fruit, or even ends up bringing rotten berries by accident. And the lord complains "I have a supply chain problem!" Like, fuck off dude! Your problem is that you *didn't* want to build a supply chain and instead thought you would build your profit-focused business in other people's free stuff. If you were paying the berry-picker, you'd have a supply chain problem, but you weren't, so you really have an "I want more free stuff" problem when you can't be arsed to give away your own stuff for free.
There can be all sorts of problems in the really-free-market, like maybe not enough people bring socks, so the peasants who can't afford socks are going barefoot, and having foot problems, and the peasants put their heads together and see if they can convince someone to start bringing socks, and maybe they can't and things are a bit sad, but the really-free-market was never supposed to solve everyone's problems 100% when they're all still being squeezed dry by their taxes: until they are able to get free of the lord & start building a lovely anarchist society, the really-free-market is a best-effort kind of deal that aims to make things better, and sometimes will fall short. When it becomes the main way goods in society are distributed, and when the people who contribute aren't constantly drained by the feudal yoke, at that point the availability of particular goods is a real problem that needs to be solved, but at that point, it's also much easier to solve. And at *no* point does someone coming into the market to take stuff only to turn around and sell it deserve anything from the market or those contributing to it. They are not a supply chain. They're trying to help each other out, but even then they're doing so freely and without obligation. They might discuss amongst themselves how to better coordinate their mutual aid, but they're not going to end up forcing anyone to bring anything or even expecting that a certain person contribute a certain amount, since the whole point is that the thing is voluntary & free, and they've all got changing life circumstances that affect their contributions. Celebrate whatever shows up at the market, express your desire for things that would be useful, but don't impose a burden on anyone else to bring a specific thing, because otherwise it's fair for them to oppose such a burden on you, and now you two are doing your own barter thing that's outside the parameters of the really-free-market.

All 17 fired vaccine advisors unite to blast RFK Jr.’s “destabilizing decisions” - Ars Technica
https://arstechnica.com/health/2025/06/all-17-fired-vaccine-advisors-unite-to-blast-rfk-jr-s-destabilizing-decisions/

When humans feel powerless, especially after traumatic events or retraumatization or ~ gestures generally at C-PTSD ~ what often helps is having an area of control over choices, decisions, and outcomes (especially outcomes that have positive side effects like humans liking the action/work/result)
And thus I flew to LA for a weekend and got a tattoo.
#BloomScrolling

Is this reality?
https://www.linkedin.com/feed/update/urn:li:activity:7341857033932914691/

I had the thrill of a lifetime, hosting dinner for Bill Gates, Linus Torvalds and David Cutler. | Mark Russinovich
I had the thrill of a lifetime, hosting dinner for Bill Gates, Linus Torvalds and David Cutler. Linus had never met Bill, and Dave had never met Linus. No major kernel decisions were made, but maybe next dinner 😉 | 619 comments on LinkedIn

Prestige in Numbers: How Test Scores and Choices Reveal School Rankings
Federico Echenique, Michael Olabisi
https://arxiv.org/abs/2505.21063 https://

Prestige in Numbers: How Test Scores and Choices Reveal School Rankings
This paper introduces a novel revealed-preference approach to ranking colleges and professional schools based on applicants' choices and standardized test scores. Unlike traditional rankings that rely on data supplied by institutions or expert opinions, our methodology leverages the decentralized beliefs of potential students, as revealed through their application decisions. We develop a theoretical model where students with higher test scores apply to more selective institutions, allowing us t…

Price equilibria with positive margins in loyal-strategic markets with discrete prices
Gurkirat Wadhwa, Akansh Verma, Veeraruna Kavitha, Priyank Sinha
https://arxiv.org/abs/2506.17239

Price equilibria with positive margins in loyal-strategic markets with discrete prices
In competitive supply chains (SCs), pricing decisions are crucial, as they directly impact market share and profitability. Traditional SC models often assume continuous pricing for mathematical convenience, overlooking the practical reality of discrete price increments driven by currency constraints. Additionally, customer behavior, influenced by loyalty and strategic considerations, plays a significant role in purchasing decisions. To address these gaps, this study examines a SC model involvin…

Saw on YouTube that the rest of T. Rump's cabinet is pissed off about Peter Hegseth.
Which raises the question: if you assemble a team of 10 morons to manage something, their collective decisions will be

When concept-based XAI is imprecise: Do people distinguish between generalisations and misrepresentations?
Romy M\"uller
https://arxiv.org/abs/2506.17936

When concept-based XAI is imprecise: Do people distinguish between generalisations and misrepresentations?
Concept-based explainable artificial intelligence (C-XAI) can help reveal the inner representations of AI models. Understanding these representations is particularly important in complex tasks like safety evaluation. Such tasks rely on high-level semantic information (e.g., about actions) to make decisions about abstract categories (e.g., whether a situation is dangerous). In this context, it may desirable for C-XAI concepts to show some variability, suggesting that the AI is capable of general…

at the very end of tulip season I allowed myself to cut a bouquet. having it on my desk might have been a mistake - I got utterly and completely hypnotized by the way how the wind in the tree outside my window that is filtering the sunlight coming in made them look differently from split second to split second. so hard to look away. so many pictures taken. so many decisions to make. but now tulip season is truly over.
which one do you like better, and why?

Wisdom of Crowds Through Myopic Self-Confidence Adaptation
Giacomo Como, Fabio Fagnani, Anton Proskurnikov
https://arxiv.org/abs/2506.18195 https://…

Wisdom of Crowds Through Myopic Self-Confidence Adaptation
The wisdom of crowds is an umbrella term for phenomena suggesting that the collective judgment or decision of a large group can be more accurate than the individual judgments or decisions of the group members. A well-known example illustrating this concept is the competition at a country fair described by Galton, where the median value of the individual guesses about the weight of an ox resulted in an astonishingly accurate estimate of the actual weight. This phenomenon resembles classical resu…

A Study of Dynamic Stock Relationship Modeling and S&P500 Price Forecasting Based on Differential Graph Transformer
Linyue Hu, Qi Wang
https://arxiv.org/abs/2506.18717

A Study of Dynamic Stock Relationship Modeling and S&P500 Price Forecasting Based on Differential Graph Transformer
Stock price prediction is vital for investment decisions and risk management, yet remains challenging due to markets' nonlinear dynamics and time-varying inter-stock correlations. Traditional static-correlation models fail to capture evolving stock relationships. To address this, we propose a Differential Graph Transformer (DGT) framework for dynamic relationship modeling and price prediction. Our DGT integrates sequential graph structure changes into multi-head self-attention via a differentia…

If groups of parents can band together when deciding on the right age for a smartphone for their younger children, they will stand a better chance to avoid making decisions based on peer pressure at school.
https://theprivacydad.com/how-parent-c

https://replaceyourboss.ai/

AI CEO – Replace Your Boss Before They Replace You
Stop working for humans. AI CEO delivers algorithmic thought leadership, with instant decisions, and zero ego. Replace your boss before they replace you.

A Conceptual Framework for AI Capability Evaluations
Mar\'ia Victoria Carro, Denise Alejandra Mester, Francisca Gauna Selasco, Luca Nicol\'as Forziati Gangi, Matheo Sandleris Musa, Lola Ramos Pereyra, Mario Leiva, Juan Gustavo Corvalan, Mar\'ia Vanina Martinez, Gerardo Simari
https://arxiv.org/abs/2506.18213

A Conceptual Framework for AI Capability Evaluations
As AI systems advance and integrate into society, well-designed and transparent evaluations are becoming essential tools in AI governance, informing decisions by providing evidence about system capabilities and risks. Yet there remains a lack of clarity on how to perform these assessments both comprehensively and reliably. To address this gap, we propose a conceptual framework for analyzing AI capability evaluations, offering a structured, descriptive approach that systematizes the analysis of …

It's exhausting to try and fix. There's a lot of work. There's a lot of thinking. There's a lot of decisions to make. There's a lot of emotional stuff to dredge through to try and get through it. https://www.

Loving the general “fuck you” treatment of Martin this year. Eurovision makes so many dogshit decisions year after year, but this one is solid. Keep him in the basement. No need to even cut to shots of him.

This https://arxiv.org/abs/2506.04047 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

On Support Samples of Next Word Prediction
Language models excel in various tasks by making complex decisions, yet understanding the rationale behind these decisions remains a challenge. This paper investigates \emph{data-centric interpretability} in language models, focusing on the next-word prediction task. Using representer theorem, we identify two types of \emph{support samples}-those that either promote or deter specific predictions. Our findings reveal that being a support sample is an intrinsic property, predictable even before t…

Angry dominant hegemony club gotta dominant hegemony :-)
https://climatejustice.social/@PeterRu/114687881102810320

A federal judge ruled on Thursday that Donald Trump illegally deployed the California national guard to suppress protests against immigration raids in Los Angeles
and ordered the force to be returned to the control of the state governor, Gavin Newsom.
The order by the US district judge Charles Breyer will not take effect until noon on Friday,
but it marked a stinging defeat for the Trump administration that is sure to touch off a pitched legal battle destined for the US supr…

Recognition through Reasoning: Reinforcing Image Geo-localization with Large Vision-Language Models
Ling Li, Yao Zhou, Yuxuan Liang, Fugee Tsung, Jiaheng Wei
https://arxiv.org/abs/2506.14674

Recognition through Reasoning: Reinforcing Image Geo-localization with Large Vision-Language Models
Previous methods for image geo-localization have typically treated the task as either classification or retrieval, often relying on black-box decisions that lack interpretability. The rise of large vision-language models (LVLMs) has enabled a rethinking of geo-localization as a reasoning-driven task grounded in visual cues. However, two major challenges persist. On the data side, existing reasoning-focused datasets are primarily based on street-view imagery, offering limited scene diversity and…

Convenience gives the illusion of freedom but is quite often the exact opposite.
Convenience creates "freedom from choice" and takes away the ability to make decisions on your own.

“CVE naming and assignment to software packages and versions are the foundation upon which the software vulnerability ecosystem is based. Without it, we can’t track newly discovered vulnerabilities. We can’t score their severity or predict their exploitation. And we certainly wouldn’t be able to make the best decisions regarding patching them.”

CVE program averts swift end after CISA executes 11-month contract extension
After DHS did not renew its funding contract for reasons unspecified, MITRE’s 25-year-old Common Vulnerabilities and Exposures (CVE) program was slated for an abrupt shutdown on April 16, which would have left security flaw tracking in limbo. CISA stepped in to provide a bridge.

Supporting Car-Following Behavior through V2V-Based Beyond-Visual-Range Information Display
Feiqi Gu, Zhixiong Wang, Zhenyu Wang, Dengbo He
https://arxiv.org/abs/2506.18308

Supporting Car-Following Behavior through V2V-Based Beyond-Visual-Range Information Display
Rear-end collisions constituted a large portion of crashes on the road, despite efforts to mitigate rear-end collisions, such as forward collision warnings. The chance of rear-end collisions is closely related to drivers' car-following (CF) behaviors in the traffic flow. Given that drivers may rely on more than the information of the direct lead vehicle (DLV) when making CF decisions, expanding drivers' perceptual range by providing beyond-visual-range (BVR) information based on vehicle-to-vehi…

‘The court now grants’: Judge finally agrees to toss Jan. 6 defendant’s gun case in light of Trump pardon and decisions on where the government’s ‘resources are best spent’
https://lawandcrime.com/high-profile/the-court-now-grants-judge-finally-agrees-to-toss-jan-6-defendants-gun-case-in-light-of-trump-pardon-and-decisions-on-where-the-governments-resources-are-best-spent/

This https://arxiv.org/abs/2505.07078 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qfi…

Can LLM-based Financial Investing Strategies Outperform the Market in Long Run?
Large Language Models (LLMs) have recently been leveraged for asset pricing tasks and stock trading applications, enabling AI agents to generate investment decisions from unstructured financial data. However, most evaluations of LLM timing-based investing strategies are conducted on narrow timeframes and limited stock universes, overstating effectiveness due to survivorship and data-snooping biases. We critically assess their generalizability and robustness by proposing FINSABER, a backtesting …

Perceptual Rationality: An Evolutionary Game Theory of Perceptually Rational Decision-Making
Mohammad Salahshour
https://arxiv.org/abs/2506.17724 https://

Perceptual Rationality: An Evolutionary Game Theory of Perceptually Rational Decision-Making
Understanding how biological organisms make decisions is of fundamental importance in understanding behavior. Such an understanding within evolutionary game theory so far has been sought by appealing to bounded rationality. Here, we present a perceptual rationality framework in the context of group cooperative interactions, where individuals make rational decisions based on their evolvable perception of the environment. We show that a simple public goods game accounts for power law distributed …

RAG has revolutionised AI by merging search and generation. Agentic behaviour takes this search to the next level by enabling LLMs to make decisions and call tools. At this year's Berlin Buzzwords, Bilge Yücel will discuss how agentic behaviour enhances pipelines, what it means for a system to act as an 'agent', and core concepts such as routing, tool calling and reasoning, along with a live demo.
Learn more:

Regular Tree Search for Simulation Optimization
Du-Yi Wang, Guo Liang, Guangwu Liu, Kun Zhang
https://arxiv.org/abs/2506.17696 https://

Regular Tree Search for Simulation Optimization
Tackling simulation optimization problems with non-convex objective functions remains a fundamental challenge in operations research. In this paper, we propose a class of random search algorithms, called Regular Tree Search, which integrates adaptive sampling with recursive partitioning of the search space. The algorithm concentrates simulations on increasingly promising regions by iteratively refining a tree structure. A tree search strategy guides sampling decisions, while partitioning is tri…

A Principled Approach to Randomized Selection under Uncertainty
Alexander Goldberg, Giulia Fanti, Nihar B. Shah
https://arxiv.org/abs/2506.19083 https://…

A Principled Approach to Randomized Selection under Uncertainty
Many decision-making processes involve evaluating and then selecting items; examples include scientific peer review, job hiring, school admissions, and investment decisions. The eventual selection is performed by applying rules or deliberations to the raw evaluations, and then deterministically selecting the items deemed to be the best. These domains feature error-prone evaluations and uncertainty about future outcomes, which undermine the reliability of such deterministic selection rules. As a…

Mobile Application Review Summarization using Chain of Density Prompting
Shristi Shrestha, Anas Mahmoud
https://arxiv.org/abs/2506.14192 https://

Mobile Application Review Summarization using Chain of Density Prompting
Mobile app users commonly rely on app store ratings and reviews to find apps that suit their needs. However, the sheer volume of reviews available on app stores can lead to information overload, thus impeding users' ability to make informed app selection decisions. To address this challenge, we leverage Large Language Models (LLMs) to summarize mobile app reviews. In particular, we use the Chain of Density (CoD) prompt to guide OpenAI GPT-4 to generate abstractive, semantically dense, and easil…

Evaluating Undergrounding Decisions for Wildfire Ignition Risk Mitigation across Multiple Hazards
Ryan Piansky, Daniel K. Molzahn, Nicole D. Jackson, J. Kyle Skolfield
https://arxiv.org/abs/2506.06575

Evaluating Undergrounding Decisions for Wildfire Ignition Risk Mitigation across Multiple Hazards
With electric power infrastructure increasingly susceptible to impacts from climate-driven natural disasters, there is an increasing need for optimization algorithms that determine where to harden the power grid. Prior work has primarily developed optimal hardening approaches for specific acute disaster scenarios. Given the extensive costs of hardening the grid, it is important to understand how a particular set of resilience investments will perform under multiple types of natural hazards. Usi…

Preparing for the Intelligence Explosion
William MacAskill, Fin Moorhouse
https://arxiv.org/abs/2506.14863 https://arxiv.org/pdf/2506…

Preparing for the Intelligence Explosion
AI that can accelerate research could drive a century of technological progress over just a few years. During such a period, new technological or political developments will raise consequential and hard-to-reverse decisions, in rapid succession. We call these developments grand challenges. These challenges include new weapons of mass destruction, AI-enabled autocracies, races to grab offworld resources, and digital beings worthy of moral consideration, as well as opportunities to dramatically i…

OceanGate? More like Heaven's Gate
https://www.theguardian.com/film/2025/jun/11/titan-sub-disaster-netflix-documentary

What Will Raiders' RB Depth Look like? https://www.si.com/nfl/raiders/las-vegas-pete-carroll-sincere-mccormick-zamir-white-asthon-jeanty

Dallas Cowboys selection for Defensive Player of the Year Candidate is a no-brainer https://www.si.com/nfl/cowboys/news/dallas-cowboys-selection-defensive-player-year-candidate-no-brainer

The fundamental problem of risk prediction for individuals: health AI, uncertainty, and personalized medicine
Lasai Barre\~nada, Ewout W Steyerberg, Dirk Timmerman, Doranne Thomassen, Laure Wynants, Ben Van Calster
https://arxiv.org/abs/2506.17141

The fundamental problem of risk prediction for individuals: health AI, uncertainty, and personalized medicine
Background: Clinical prediction models for a health condition are commonly evaluated regarding performance for a population, although decisions are made for individuals. The classic view relates uncertainty in risk estimates for individuals to sample size (estimation uncertainty) but uncertainty can also be caused by model uncertainty (variability in modeling choices) and applicability uncertainty (variability in measurement procedures and between populations). Methods: We used real and synthet…

A Machine Learning Framework for Climate-Resilient Insurance and Real Estate Decisions
Lang Qin, Yuejin Xie, Daili Hua, Xuhui Meng
https://arxiv.org/abs/2506.14638

A Machine Learning Framework for Climate-Resilient Insurance and Real Estate Decisions
Extreme weather events increasingly threaten the insurance and real estate industries, creating conflicts between profitability and homeowner burdens. To address this, we propose the SSC-Insurance Model, which integrates SMOTE, SVM, and C-D-C algorithms to evaluate weather impacts on policies and investments. Our model achieves 88.3% accuracy in Zhejiang and 79.6% in Ireland, identifying a critical threshold (43% weather increase) for insurance viability. Additionally, we develop the TOA-Preser…

Watch as the Supreme Court’s newly elevated “major questions doctrine” suddenly melts away in the next round of SCOTUS decisions. Just watch. https://mastodon.social/@thejapantimes/114606283686912236

Let this be a lesson: my point about editing above goes deep. It's not just about writing words and editing words.
It's about decisions of any kind.
While deliberative paralysis is a thing, when you make "do" easier than "deliberate" (and increasingly tip the balance toward "do"), what happens is what's easy, not what's good. It is an accelerator for all kinds of things, a great many of them bad, and even more suboptimal.

Agent-based Condition Monitoring Assistance with Multimodal Industrial Database Retrieval Augmented Generation
Karl L\"owenmark, Daniel Str\"ombergsson, Chang Liu, Marcus Liwicki, Fredrik Sandin
https://arxiv.org/abs/2506.09247

Agent-based Condition Monitoring Assistance with Multimodal Industrial Database Retrieval Augmented Generation
Condition monitoring (CM) plays a crucial role in ensuring reliability and efficiency in the process industry. Although computerised maintenance systems effectively detect and classify faults, tasks like fault severity estimation, and maintenance decisions still largely depend on human expert analysis. The analysis and decision making automatically performed by current systems typically exhibit considerable uncertainty and high false alarm rates, leading to increased workload and reduced effici…

I see no Constitutional reason why SCOTUS is precluded from revisiting a prior decision and amending it.
We issue updates for software, why not for decisions?
Yes, it could lead to uncertainties if used more than rarely.
But imagine if the court could re-open the Dred Scott or Korematsu decisions and change the original?
Git hubs could accommodate this.

Making the Right Thing: Bridging HCI and Responsible AI in Early-Stage AI Concept Selection
Ji-Youn Jung, Devansh Saxena, Minjung Park, Jini Kim, Jodi Forlizzi, Kenneth Holstein, John Zimmerman
https://arxiv.org/abs/2506.17494

Making the Right Thing: Bridging HCI and Responsible AI in Early-Stage AI Concept Selection
AI projects often fail due to financial, technical, ethical, or user acceptance challenges -- failures frequently rooted in early-stage decisions. While HCI and Responsible AI (RAI) research emphasize this, practical approaches for identifying promising concepts early remain limited. Drawing on Research through Design, this paper investigates how early-stage AI concept sorting in commercial settings can reflect RAI principles. Through three design experiments -- including a probe study with ind…

Agentic Markets: Game Dynamics and Equilibrium in Markets with Learning Agents
Martin Bichler, Julius Durmann, Matthias Oberlechner
https://arxiv.org/abs/2506.18571

Agentic Markets: Game Dynamics and Equilibrium in Markets with Learning Agents
Autonomous and learning agents increasingly participate in markets - setting prices, placing bids, ordering inventory. Such agents are not just aiming to optimize in an uncertain environment; they are making decisions in a game-theoretical environment where the decision of one agent influences the profit of other agents. While game theory usually predicts outcomes of strategic interaction as an equilibrium, it does not capture how repeated interaction of learning agents arrives at a certain out…

Modeling society with a responsible elite
Yana Tsodikova, Pavel Chebotarev
https://arxiv.org/abs/2506.15877 https://arxiv.org/pdf/250…

Modeling society with a responsible elite
Within the framework of the ViSE (Voting in a Stochastic Environment) model, we examine the dynamics in a society, part of which can be considered an elite. The model allows us to analyze the influence of social attitudes, such as collectivism, individualism, altruism on the well-being of agents. The dynamics is determined by collective decisions and changes in the structure of society, in particular, by the formation of groups of cooperating agents. It is found that the presence of a "responsi…

I can't believe it, but the Trump regime is actually using its abusive legal practices to do the right thing, for once!
https://www.irishstar.com/news/us-news/breaking-trump-doj-launches-criminal-35260670

Trump DOJ launches criminal probe into Andrew Cuomo over 'COVID cover-up'
The Trump DOJ has launched a criminal probe into former New York governor and NYC mayoral front-runner Andrew Cuomo over allegations he lied to Congress about decisions made during the COVID-19 pandemic

Dallas Cowboys selection for Defensive Player of the Year Candidate is a no-brainer https://www.si.com/nfl/cowboys/news/dallas-cowboys-selection-defensive-player-year-candidate-no-brainer

Zero-Shot Scene Understanding with Multimodal Large Language Models for Automated Vehicles
Mohammed Elhenawy, Shadi Jaradat, Taqwa I. Alhadidi, Huthaifa I. Ashqar, Ahmed Jaber, Andry Rakotonirainy, Mohammad Abu Tami
https://arxiv.org/abs/2506.12232

Zero-Shot Scene Understanding with Multimodal Large Language Models for Automated Vehicles
Scene understanding is critical for various downstream tasks in autonomous driving, including facilitating driver-agent communication and enhancing human-centered explainability of autonomous vehicle (AV) decisions. This paper evaluates the capability of four multimodal large language models (MLLMs), including relatively small models, to understand scenes in a zero-shot, in-context learning setting. Additionally, we explore whether combining these models using an ensemble approach with majority…

Enhancing Traffic Accident Classifications: Application of NLP Methods for City Safety
Enes \"Ozeren, Alexander Ulbrich, Sascha Filimon, David R\"ugamer, Andreas Bender
https://arxiv.org/abs/2506.12092

Enhancing Traffic Accident Classifications: Application of NLP Methods for City Safety
A comprehensive understanding of traffic accidents is essential for improving city safety and informing policy decisions. In this study, we analyze traffic incidents in Munich to identify patterns and characteristics that distinguish different types of accidents. The dataset consists of both structured tabular features, such as location, time, and weather conditions, as well as unstructured free-text descriptions detailing the circumstances of each accident. Each incident is categorized into on…

With fewer than 900 American students in China at a time of unprecedented bilateral tensions,
Chinese classmates continually ask her to explain President Donald Trump’s decisions,
while American friends and family ask her to translate the intricacies of Chinese politics.
https://www.

American students in China face a barrage of questions about Trump
The number of U.S. students in China has plummeted, but those who are there now say it’s more important than ever for Americans to understand the country.

Q&A with Airbnb CEO Brian Chesky on Airbnb Experiences, its push into services, OpenAI, AI agents, making decisions at Airbnb, cutting PMs, Jony Ive, and more (Nilay Patel/The Verge)
https://www.theverge.com/decoder-podcast-w

Airbnb CEO Brian Chesky wants to build the everything app
The head of Airbnb on expanding beyond travel, AI and design, and the future of real-world experiences.

Dependent Randomized Rounding for Budget Constrained Experimental Design
Khurram Yamin, Edward Kennedy, Bryan Wilder
https://arxiv.org/abs/2506.12677 https…

Dependent Randomized Rounding for Budget Constrained Experimental Design
Policymakers in resource-constrained settings require experimental designs that satisfy strict budget limits while ensuring precise estimation of treatment effects. We propose a framework that applies a dependent randomized rounding procedure to convert assignment probabilities into binary treatment decisions. Our proposed solution preserves the marginal treatment probabilities while inducing negative correlations among assignments, leading to improved estimator precision through variance reduc…

Understanding API Usage and Testing: An Empirical Study of C Libraries
Ahmed Zaki, Cristian Cadar
https://arxiv.org/abs/2506.11598 https://

Understanding API Usage and Testing: An Empirical Study of C Libraries
For library developers, understanding how their Application Programming Interfaces (APIs) are used in the field can be invaluable. Knowing how clients are using their APIs allows for data-driven decisions on prioritising bug reports, feature requests, and testing activities. For example, the priority of a bug report concerning an API can be partly determined by how widely that API is used. In this paper, we present an empirical study in which we analyse API usage across 21 popular open-source…

Biden calls claims he wasn't making decisions in White House 'ridiculous and false' (Brett Samuels/The Hill)
https://thehill.com/homenews/administration/5333855-biden-trump-claims-ridiculous-false/
http://www.memeorandum.com/250605/p5#a250605p5

Fragile Preferences: A Deep Dive Into Order Effects in Large Language Models
Haonan Yin, Shai Vardi, Vidyanand Choudhary
https://arxiv.org/abs/2506.14092 h…

Fragile Preferences: A Deep Dive Into Order Effects in Large Language Models
Large language models (LLMs) are increasingly used in decision-support systems across high-stakes domains such as hiring and university admissions, where decisions often involve selecting among competing alternatives. While prior work has noted positional order biases in LLM-driven comparisons, these biases have not been systematically dissected or linked to underlying preference structures. We provide the first comprehensive investigation of positional biases across multiple LLM architectures …

Advances in LLMs with Focus on Reasoning, Adaptability, Efficiency and Ethics
Asifullah khan, Muhammad Zaeem Khan, Saleha Jamshed, Sadia Ahmad, Aleesha Zainab, Kaynat Khatib, Faria Bibi, Abdul Rehman
https://arxiv.org/abs/2506.12365

Advances in LLMs with Focus on Reasoning, Adaptability, Efficiency and Ethics
This survey paper outlines the key developments in the field of Large Language Models (LLMs), such as enhancing their reasoning skills, adaptability to various tasks, increased computational efficiency, and ability to make ethical decisions. The techniques that have been most effective in bridging the gap between human and machine communications include the Chain-of-Thought prompting, Instruction Tuning, and Reinforcement Learning from Human Feedback. The improvements in multimodal learning and…

Marines are highly trained in combat and crisis response, with time in conflict zones like Syria and Afghanistan.
But that is starkly different from the role they will face now:
They could potentially be hit by L A hipsters carrying gas canisters and have to quickly decide how to respond
or face decisions about protecting an immigration enforcement agent from crowds.

Pentagon draws up rules for Marines deployed to LA protests
The Pentagon is scrambling to establish rules to guide U.S. Marines who could be faced with the rare and difficult prospect of using force against citizens on American soil, now that the Trump administration is deploying active duty troops to the immigration raid protests in Los Angeles. U.S. Northern Command said Monday that it's sending 700 Marines into the Los Angeles area to protect federal property and personnel. A U.S. official says troops will be armed with their normal service weapons b…

Efficient Online Mirror Descent Stochastic Approximation for Multi-Stage Stochastic Programming
Junhui Zhang, Patrick Jaillet
https://arxiv.org/abs/2506.15392

Efficient Online Mirror Descent Stochastic Approximation for Multi-Stage Stochastic Programming
We study the unconstrained and the minimax saddle point variants of the convex multi-stage stochastic programming problem, where consecutive decisions are coupled through the objective functions, rather than through the constraints. Based on the analysis of deterministic mirror descent algorithms with inexact gradients, we introduce the idea of \textit{stochastic conditional gradient oracles}, a multi-stage analog of the stochastic gradient oracles used in (classical) stochastic programming. We…

We don’t trust ourselves to make decisions. We second-guess ourselves constantly. We’re constantly doubting ourselves https://www.overcomecompulsivehoarding.co.uk/podcast-ep-188-decision-making-hoarding-disorder/

A Tale of Two Systems: Characterizing Architectural Complexity on Machine Learning-Enabled Systems
Renato Cordeiro Ferreira (University of S\~ao Paulo, Jheronimus Academy of Data Science, Technical University of Eindhoven, Tilburg University)
https://arxiv.org/abs/2506.11295

A Tale of Two Systems: Characterizing Architectural Complexity on Machine Learning-Enabled Systems
How can the complexity of ML-enabled systems be managed effectively? The goal of this research is to investigate how complexity affects ML-Enabled Systems (MLES). To address this question, this research aims to introduce a metrics-based architectural model to characterize the complexity of MLES. The goal is to support architectural decisions, providing a guideline for the inception and growth of these systems. This paper brings, side-by-side, the architecture representation of two systems that …

See What I Mean? CUE: A Cognitive Model of Understanding Explanations
Tobias Labarta, Nhi Hoang, Katharina Weitz, Wojciech Samek, Sebastian Lapuschkin, Leander Weber
https://arxiv.org/abs/2506.14775

See What I Mean? CUE: A Cognitive Model of Understanding Explanations
As machine learning systems increasingly inform critical decisions, the need for human-understandable explanations grows. Current evaluations of Explainable AI (XAI) often prioritize technical fidelity over cognitive accessibility which critically affects users, in particular those with visual impairments. We propose CUE, a model for Cognitive Understanding of Explanations, linking explanation properties to cognitive sub-processes: legibility (perception), readability (comprehension), and inter…

Toward Safety-First Human-Like Decision Making for Autonomous Vehicles in Time-Varying Traffic Flow
Xiao Wang, Junru Yu, Jun Huang, Qiong Wu, Ljubo Vacic, Changyin Sun
https://arxiv.org/abs/2506.14502

Toward Safety-First Human-Like Decision Making for Autonomous Vehicles in Time-Varying Traffic Flow
Despite the recent advancements in artificial intelligence technologies have shown great potential in improving transport efficiency and safety, autonomous vehicles(AVs) still face great challenge of driving in time-varying traffic flow, especially in dense and interactive situations. Meanwhile, human have free wills and usually do not make the same decisions even situate in the exactly same scenarios, leading to the data-driven methods suffer from poor migratability and high search cost proble…

Penalised spline estimation of covariate-specific time-dependent ROC curves
Mar\'ia Xos\'e Rodr\'iguez-\'Alvarez, Vanda In\'acio
https://arxiv.org/abs/2506.13604

Penalised spline estimation of covariate-specific time-dependent ROC curves
The identification of biomarkers with high predictive accuracy is a crucial task in medical research, as it can aid clinicians in making early decisions, thereby reducing morbidity and mortality in high-risk populations. Time-dependent receiver operating characteristic (ROC) curves are the main tool used to assess the accuracy of prognostic biomarkers for outcomes that evolve over time. Recognising the need to account for patient heterogeneity when evaluating the accuracy of a prognostic biomar…

On the Effectiveness of Classical Regression Methods for Optimal Switching Problems
Martin Andersson, Benny Avelin, Marcus Olofsson
https://arxiv.org/abs/2506.15436

On the Effectiveness of Classical Regression Methods for Optimal Switching Problems
Simple regression methods provide robust, near-optimal solutions for optimal switching problems in dimensions ranging from 1 to 50. While the theory requires solving intractable PDE systems, the Longstaff-Schwartz algorithm with classical approaches like $k$-NN achieves excellent switching decisions without extensive hyperparameter tuning. Testing eight regression approaches on four benchmark problems, we find that simple methods maintain stable performance across diverse problem characteristic…

Pete Carroll Made Smart Decisions With Raiders' Staff https://www.si.com/nfl/raiders/chip-kelly-geno-smith-pete-carroll-las-vegas-notre-dame

Game Theory in Social Media: A Stackelberg Model of Collaboration, Conflict, and Algorithmic Incentives
Arjan Khadka
https://arxiv.org/abs/2506.05373 https…

Game Theory in Social Media: A Stackelberg Model of Collaboration, Conflict, and Algorithmic Incentives
Social media platforms are ecosystems in which many decisions are constantly made for the benefit of the creators in order to maximize engagement, which leads to a maximization of income. The decisions, ranging from collaboration to public conflict or ``beefing,'' are heavily influenced by social media algorithms, viewer preferences, and sponsor risk. This paper models this interaction as a Stackelberg game in which the algorithm is the leader, setting exposure and reward rules, and the content…

3 Dallas Cowboys players entering training camp on the chopping block https://www.si.com/nfl/cowboys/news/3-dallas-cowboys-players-entering-training-camp-on-the-chopping-block

Aspect-Based Opinion Summarization with Argumentation Schemes
Wendi Zhou, Ameer Saadat-Yazd, Nadin Kokciyan
https://arxiv.org/abs/2506.09917 https://

Aspect-Based Opinion Summarization with Argumentation Schemes
Reviews are valuable resources for customers making purchase decisions in online shopping. However, it is impractical for customers to go over the vast number of reviews and manually conclude the prominent opinions, which prompts the need for automated opinion summarization systems. Previous approaches, either extractive or abstractive, face challenges in automatically producing grounded aspect-centric summaries. In this paper, we propose a novel summarization system that not only captures pred…

Structured Moral Reasoning in Language Models: A Value-Grounded Evaluation Framework
Mohna Chakraborty, Lu Wang, David Jurgens
https://arxiv.org/abs/2506.14948

Structured Moral Reasoning in Language Models: A Value-Grounded Evaluation Framework
Large language models (LLMs) are increasingly deployed in domains requiring moral understanding, yet their reasoning often remains shallow, and misaligned with human reasoning. Unlike humans, whose moral reasoning integrates contextual trade-offs, value systems, and ethical theories, LLMs often rely on surface patterns, leading to biased decisions in morally and ethically complex scenarios. To address this gap, we present a value-grounded framework for evaluating and distilling structured moral…

Don’t start with your most emotionally charged items. Don’t start with your difficult items or your most expensive items to make decisions about. Start with low stakes things. https://www.overcomecompulsivehoarding.co.uk/podcast-ep-188-decision-making…