Tootfinder

Trevon Diggs 'happy to be' at Cowboys training camp, explains offseason training decision https://www.dallascowboys.com/news/trevon-diggs-happy-to-be-at-cowboys-training-camp-explains-offseason-training-decision

Inside Trump's Decision (New York Times)
https://www.nytimes.com/2025/06/23/briefing/inside-trumps-decision.html
http://www.memeorandum.com/250623/p23#a250623p23

North Dakota urges Supreme Court to leave in place decision that could limit the power of the Voting Rights Act - SCOTUSblog
https://www.scotusblog.com/2025/07/north-dakota-urges-supreme-court-to-leave-in-place-decision-that-could-weaken-vra/

CoMoCAVs: Cohesive Decision-Guided Motion Planning for Connected and Autonomous Vehicles with Multi-Policy Reinforcement Learning
Pan Hu
https://arxiv.org/abs/2507.14903

CoMoCAVs: Cohesive Decision-Guided Motion Planning for Connected and Autonomous Vehicles with Multi-Policy Reinforcement Learning
Autonomous driving demands reliable and efficient solutions to closely related problems such as decision-making and motion planning. In this work, decision-making refers specifically to highway lane selection, while motion planning involves generating control commands (such as speed and steering) to reach the chosen lane. In the context of Connected Autonomous Vehicles (CAVs), achieving both flexible and safe lane selection alongside precise trajectory execution remains a significant challenge.…

'I'm ready to fight' — Ukraine's rejected nominee for economic crimes bureau calls government decision 'unlawful': https://benborges.xyz/2025/07/21/im-ready-to-fight-ukraines.html

Trump’s “two weeks” statement was just one aspect of a broader effort at political and military misdirection that took place over eight chaotic days,
from the first Israeli strikes against Iran to the moment when a fleet of B-2 stealth bombers took off
Trump seemed almost gleeful in telling reporters that he could make a decision “one second before it’s due,
because things change, especially with war.”
All the while, Trump was making blustery statements indicating he…

How Trump Decided to Strike Iran
When Israel began its assault on Iran, President Trump kept his distance. But within days he was on a path that led to an extensive bombing mission aided by political and military ruses.

Revolutionizing Validation and Verification: Explainable Testing Methodologies for Intelligent Automotive Decision-Making Systems
Halit Eris, Stefan Wagner
https://arxiv.org/abs/2506.16876

Revolutionizing Validation and Verification: Explainable Testing Methodologies for Intelligent Automotive Decision-Making Systems
Autonomous Driving Systems (ADS) use complex decision-making (DM) models with multimodal sensory inputs, making rigorous validation and verification (V&V) essential for safety and reliability. These models pose challenges in diagnosing failures, tracing anomalies, and maintaining transparency, with current manual testing methods being inefficient and labor-intensive. This vision paper presents a methodology that integrates explainability, transparency, and interpretability into V&V processes. W…

Trevon Diggs 'happy to be' at Cowboys training camp, explains offseason training decision https://www.dallascowboys.com/news/trevon-diggs-happy-to-be-at-cowboys-training-camp-explains-offseason-training-decision

Asymptotic Optimality in Data-driven Decision Making
Radek Sala\v{c}, Michael Kupper, Tobias Sutter
https://arxiv.org/abs/2507.15215 https://

Asymptotic Optimality in Data-driven Decision Making
Given data generated by an abstract stochastic process, we study how to construct statistically optimal decisions for general stochastic optimization problems. Our setting encompasses non-standard data structures, including data originating from heterogeneous sources or from processes with randomly evolving data-generating mechanisms. We propose a decision-making approach that identifies optimal decisions for which a specific notion of shifted regret risk, evaluated with respect to the underlyi…

The board decision that sent the MLB, NFL unions into controversy https://www.nytimes.com/athletic/6442699/2025/06/22/nflpa-mlbpa-investigation-one-team-partners-equity-controversy/

Towards Emergency Scenarios: An Integrated Decision-making Framework of Multi-lane Platoon Reorganization
Aijing Kong, Chengkai Xu, Xian Wu, Xinbo Chen, Peng Hang
https://arxiv.org/abs/2506.16311

Towards Emergency Scenarios: An Integrated Decision-making Framework of Multi-lane Platoon Reorganization
To enhance the ability for vehicle platoons to respond to emergency scenarios, a platoon distribution reorganization decision-making framework is proposed. This framework contains platoon distribution layer, vehicle cooperative decision-making layer and vehicle planning and control layer. Firstly, a reinforcement-learning-based platoon distribution model is presented, where a risk potential field is established to quantitatively assess driving risks, and a reward function tailored to the platoo…

I made a decision a while back to try to go see certain old musicians before they were gone. Scratched two of them off my list last night at #outlawfestival.
Bob Dylan was, unfortunately, incomprehensible even for him. Lethargic and uninspired. He also made the poor decision to not play his well known material, with the exception of All Along the Watchtower. I understand as a mus…

Bayesian implementation of Targeted Maximum Likelihood Estimation for uncertainty quantification in causal effect estimation
Saideep Nannapaneni, Joseph Sakaya, Kyle Caron, Pedro HM Albuquerque, Zaid Tashman
https://arxiv.org/abs/2507.15909

Bayesian implementation of Targeted Maximum Likelihood Estimation for uncertainty quantification in causal effect estimation
Robust decision making involves making decisions in the presence of uncertainty and is often used in critical domains such as healthcare, supply chains, and finance. Causality plays a crucial role in decision-making as it predicts the change in an outcome (usually a key performance indicator) due to a treatment (also called an intervention). To facilitate robust decision making using causality, this paper proposes three Bayesian approaches of the popular Targeted Maximum Likelihood Estimation (…

From Bits to Boardrooms: A Cutting-Edge Multi-Agent LLM Framework for Business Excellence
Zihao Wang, Junming Zhang
https://arxiv.org/abs/2508.15447 https://

From Bits to Boardrooms: A Cutting-Edge Multi-Agent LLM Framework for Business Excellence
Large Language Models (LLMs) have shown promising potential in business applications, particularly in enterprise decision support and strategic planning, yet current approaches often struggle to reconcile intricate operational analyses with overarching strategic goals across diverse market environments, leading to fragmented workflows and reduced collaboration across organizational levels. This paper introduces BusiAgent, a novel multi-agent framework leveraging LLMs for advanced decision-makin…

Learning in Random Utility Models Via Online Decision Problems
Emerson Melo
https://arxiv.org/abs/2506.16030 https://arxiv.org/pdf/25…

Learning in Random Utility Models Via Online Decision Problems
This paper examines the Random Utility Model (RUM) in repeated stochastic choice settings where decision-makers lack full information about payoffs. We propose a gradient-based learning algorithm that embeds RUM into an online decision-making framework. Our analysis establishes Hannan consistency for a broad class of RUMs, meaning the average regret relative to the best fixed action in hindsight vanishes over time. We also show that our algorithm is equivalent to the Follow-The-Regularized-Lead…

How One Offseason Decision Changed Everything for the Raiders https://www.si.com/nfl/raiders/las-vegas-chip-kelly-ben-johnson-geno-smith-pete-carroll

Time for a #FieldDiary update. We made it to #Qaanaaq, 1000 km north of Ilulissat it's a wonderful sunny "evening". The ice has started to break in big flakes close to town, so we made decision to do sea ice programme tomorrow as probably a last chance.

Every company is undergoing an invisible reorg. You report to your boss but your boss reports to an #AI, offloading the job of management entirely onto a bot and then merely communicating its wishes back to the team.
This is the Nothing Manager, surrounded by #LLM tools to avoid having to interact with…

AI is not an assistant – it's your new boss (The Everything App part 2)
As managers continue to outsource data-gathering and decision-making to LLMs, the person above you on the org chart is transforming into a chatbot's clerk – and leaving product teams with the consequences.

A full US Court of Appeals keeps in place a June 6 decision that let Trump bar the AP from the Oval Office; a Supreme Court appeal is possible (Mike Scarcella/Reuters)
https://www.reuters.com/legal/government/us-a…

LLMs and Agentic AI in Insurance Decision-Making: Opportunities and Challenges For Africa
Graham Hill, JingYuan Gong, Thulani Babeli, Moseli Mots'oehli, James Gachomo Wanjiku
https://arxiv.org/abs/2508.15110

LLMs and Agentic AI in Insurance Decision-Making: Opportunities and Challenges For Africa
In this work, we highlight the transformative potential of Artificial Intelligence (AI), particularly Large Language Models (LLMs) and agentic AI, in the insurance sector. We consider and emphasize the unique opportunities, challenges, and potential pathways in insurance amid rapid performance improvements, increased open-source access, decreasing deployment costs, and the complexity of LLM or agentic AI frameworks. To bring it closer to home, we identify critical gaps in the African insurance …

Alison Downes, director of pressure group Stop Sizewell C, said: "This much-delayed final investment decision has only crawled over the line thanks to guarantees that the public purse, not private investors, will carry the can for the inevitable cost overruns."
#Sizewell C nuclear project cost rises to £38bn - BBC News

Sizewell C nuclear project cost rises to £38bn
Households will pay £1 a month towards the construction of the UK's second new nuclear power plant.

VLM-UDMC: VLM-Enhanced Unified Decision-Making and Motion Control for Urban Autonomous Driving
Haichao Liu, Haoren Guo, Pei Liu, Benshan Ma, Yuxiang Zhang, Jun Ma, Tong Heng Lee
https://arxiv.org/abs/2507.15266

VLM-UDMC: VLM-Enhanced Unified Decision-Making and Motion Control for Urban Autonomous Driving
Scene understanding and risk-aware attentions are crucial for human drivers to make safe and effective driving decisions. To imitate this cognitive ability in urban autonomous driving while ensuring the transparency and interpretability, we propose a vision-language model (VLM)-enhanced unified decision-making and motion control framework, named VLM-UDMC. This framework incorporates scene reasoning and risk-aware insights into an upper-level slow system, which dynamically reconfigures the optim…

Puh. #HomeAssistant wirft native Installationen und 32Bit-Systeme (incl. ARM) ausm Support. Sehr schade. Jetzt geht nur noch VM oder Container, also noch mehr Abstraktion und Rumpaketiere zwischen HA und dem System, was kaputt gehen kann. Alles sehr unschön, da HAOS viele Geräte nicht sauber unterstützt und Container viele Einschränkungen bei Netzwerk und Sicherheit hat. :/

Modeling the Monty Hall Decision Problem with Reaction Kinetics
Oliver Steinbock, Wen Zhu
https://arxiv.org/abs/2505.15824 https://ar…

Modeling the Monty Hall Decision Problem with Reaction Kinetics
Using the Monty Hall probability problem as a model system, we ask whether simple chemical reaction mechanisms can implement optimal strategies for non-trivial decision making. In this puzzle, a contestant chooses one of three doors (only one hides a prize), the host, knowing the content, opens another door revealing no prize, and finally the contestant must decide whether to stay with the original choice or switch to the remaining closed door. Assigning distinct molecular species to the player…

"This isn’t to say that AI is uniformly bad—it’s clearly not—but that we must not fall into the trap of mistaking the outputs of writing (…) from the value of the cognitive process of writing (…).
It would be a catastrophically unwise decision for humanity to abandon a key step in training young brains simply because they can now clack a few keys and produce something that sounds intelligent even as they never become intelligent."

The Death of the Student Essay—and the Future of Cognition
One professor's reflections on the end of an era, as AI tools such as ChatGPT have murdered the student essay (RIP). Here's why that threatens the future of human cognition—and how to save ourselves.

UN Climate Conference Serves Mostly Vegan and Vegetarian Food https://vegconomist.com/fairs-events/un-climate-conference-serves-mostly-vegan-and-vegetarian-food/

UN Climate Conference Serves Mostly Vegan and Vegetarian Food - vegconomist - the vegan business magazine
Caterers at the United Nations' June Climate Meetings have made the decision to serve mainly vegan and vegetarian food this year to reduce the environmental

🧑‍🚒 California wood pellet plants canceled amid market decline & public pushback
https://news.mongabay.com/short-article/2025/07/california-wood-pellet-plants-canceled-amid-market-decline-public-pushback/

California wood pellet plants canceled amid market decline & public pushback
Golden State Natural Resources (GSNR), a California nonprofit that focuses on rural economic development, has canceled plans to build two industrial-scale wood pellet plants in the state. The organization cited weakening market conditions and pushback from locals as the drivers of their decision. Conservation groups are hailing the move as a win for forests and […]

Minimizing Surrogate Losses for Decision-Focused Learning using Differentiable Optimization
Jayanta Mandi, Ali \.Irfan Mahmuto\u{g}ullar{\i}, Senne Berden, Tias Guns
https://arxiv.org/abs/2508.11365

Minimizing Surrogate Losses for Decision-Focused Learning using Differentiable Optimization
Decision-focused learning (DFL) trains a machine learning (ML) model to predict parameters of an optimization problem, to directly minimize decision regret, i.e., maximize decision quality. Gradient-based DFL requires computing the derivative of the solution to the optimization problem with respect to the predicted parameters. However, for many optimization problems, such as linear programs (LPs), the gradient of the regret with respect to the predicted parameters is zero almost everywhere. Exi…

Josh Allen to miss all of preseason for the first time: Bills coach explains decision amid team's struggles

https://www.cbssports.com/nfl/news/josh-al

Towards AI Search Paradigm
Yuchen Li, Hengyi Cai, Rui Kong, Xinran Chen, Jiamin Chen, Jun Yang, Haojie Zhang, Jiayi Li, Jiayi Wu, Yiqun Chen, Changle Qu, Keyi Kong, Wenwen Ye, Lixin Su, Xinyu Ma, Long Xia, Daiting Shi, Jiashu Zhao, Haoyi Xiong, Shuaiqiang Wang, Dawei Yin
https://arxiv.org/abs/2506.17188

Towards AI Search Paradigm
In this paper, we introduce the AI Search Paradigm, a comprehensive blueprint for next-generation search systems capable of emulating human information processing and decision-making. The paradigm employs a modular architecture of four LLM-powered agents (Master, Planner, Executor and Writer) that dynamically adapt to the full spectrum of information needs, from simple factual queries to complex multi-stage reasoning tasks. These agents collaborate dynamically through coordinated workflows to e…

Quantum Artificial Intelligence for Secure Autonomous Vehicle Navigation: An Architectural Proposal
Hemanth Kannamarlapudi, Sowmya Chintalapudi
https://arxiv.org/abs/2506.16000

Quantum Artificial Intelligence for Secure Autonomous Vehicle Navigation: An Architectural Proposal
Navigation is a very crucial aspect of autonomous vehicle ecosystem which heavily relies on collecting and processing large amounts of data in various states and taking a confident and safe decision to define the next vehicle maneuver. In this paper, we propose a novel architecture based on Quantum Artificial Intelligence by enabling quantum and AI at various levels of navigation decision making and communication process in Autonomous vehicles : Quantum Neural Networks for multimodal sensor fus…

Backpropagation-Free Test-Time Adaptation via Probabilistic Gaussian Alignment
Youjia Zhang, Youngeun Kim, Young-Geun Choi, Hongyeob Kim, Huiling Liu, Sungeun Hong
https://arxiv.org/abs/2508.15568

Backpropagation-Free Test-Time Adaptation via Probabilistic Gaussian Alignment
Test-time adaptation (TTA) enhances the zero-shot robustness under distribution shifts by leveraging unlabeled test data during inference. Despite notable advances, several challenges still limit its broader applicability. First, most methods rely on backpropagation or iterative optimization, which limits scalability and hinders real-time deployment. Second, they lack explicit modeling of class-conditional feature distributions. This modeling is crucial for producing reliable decision boundarie…

Trump gambles his presidency on war
If Iran does not agree to peace on Trump’s terms,
the president’s vow that
“there are many targets left”
opened the door to a much deeper and potentially longer conflict.
Already, that prospect is angering some members of his political base.
…

With fateful decision, Trump gambles his presidency on war
Trump rose to power criticizing Middle East wars. Now he may have his own.

On Vanishing of Gromov--Witten Invariants
Igor Pak, Colleen Robichaux, Weihong Xu
https://arxiv.org/abs/2508.15715 https://arxiv.org/pdf/2508.15715

On Vanishing of Gromov--Witten Invariants
We consider the decision problem of whether a particular Gromov--Witten invariant on a partial flag variety is zero. We prove that for the $3$-pointed, genus zero invariants, this problem is in the complexity class ${\sf AM}$ assuming the Generalized Riemann Hypothesis (GRH), and therefore lies in the second level of polynomial hierarchy ${\sf PH}$. For the proof, we construct an explicit system of polynomial equations through a translation of the defining equations. We also need to prove an …

Raiders Urged to Make ‘Important’ Contract Decision on Key Starter https://heavy.com/sports/nfl/las-vegas-raiders/kolton-miller-contract-extension-br/?adt_ei=[email]

'We know how to stand up for our rights' — Ukrainians protest law threatening anti-corruption institutions: https://benborges.xyz/2025/07/23/we-know-how-to-stand.html

Tree-like Pairwise Interaction Networks
Ronald Richman, Salvatore Scognamiglio, Mario V. W\"uthrich
https://arxiv.org/abs/2508.15678 https://arxiv.org…

Tree-like Pairwise Interaction Networks
Modeling feature interactions in tabular data remains a key challenge in predictive modeling, for example, as used for insurance pricing. This paper proposes the Tree-like Pairwise Interaction Network (PIN), a novel neural network architecture that explicitly captures pairwise feature interactions through a shared feed-forward neural network architecture that mimics the structure of decision trees. PIN enables intrinsic interpretability by design, allowing for direct inspection of interaction e…

Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/2]:
- Case Law Grounding: Using Precedents to Align Decision-Making for Humans and AI
Quan Ze Chen, Amy X. Zhang

Walmart Makes Sudden Self-Checkout Decision After Alarming Police Data
https://www.yahoo.com/news/walmart-makes-sudden-self-checkout-075754868.html

EndoControlMag: Robust Endoscopic Vascular Motion Magnification with Periodic Reference Resetting and Hierarchical Tissue-aware Dual-Mask Contro
An Wanga, Rulin Zhou, Mengya Xu, Yiru Ye, Longfei Gou, Yiting Chang, Hao Chen, Chwee Ming Lim, Jiankun Wang, Hongliang Ren
https://arxiv.org/abs/2507.15292

EndoControlMag: Robust Endoscopic Vascular Motion Magnification with Periodic Reference Resetting and Hierarchical Tissue-aware Dual-Mask Contro
Visualizing subtle vascular motions in endoscopic surgery is crucial for surgical precision and decision-making, yet remains challenging due to the complex and dynamic nature of surgical scenes. To address this, we introduce EndoControlMag, a training-free, Lagrangian-based framework with mask-conditioned vascular motion magnification tailored to endoscopic environments. Our approach features two key modules: a Periodic Reference Resetting (PRR) scheme that divides videos into short overlapping…

‘I’m proud to have made this stand’: over-60s arrested at Palestine Action ban protest explain their decision https://www.theguardian.com/world/ng-inter

Global climate action is at stake in the UN top court's biggest ever decision (Molly Quell/Associated Press)
https://apnews.com/article/un-court-opinion-climate-change-1ac84a94a5aaffd63518ef1da3502a9e
http://www.memeorandum.com/250723/p27#a250723p27

Self-Supervised Distillation of Legacy Rule-Based Methods for Enhanced EEG-Based Decision-Making
Yipeng Zhang, Yuanyi Ding, Chenda Duan, Atsuro Daida, Hiroki Nariai, Vwani Roychowdhury
https://arxiv.org/abs/2507.14542

Self-Supervised Distillation of Legacy Rule-Based Methods for Enhanced EEG-Based Decision-Making
High-frequency oscillations (HFOs) in intracranial Electroencephalography (iEEG) are critical biomarkers for localizing the epileptogenic zone in epilepsy treatment. However, traditional rule-based detectors for HFOs suffer from unsatisfactory precision, producing false positives that require time-consuming manual review. Supervised machine learning approaches have been used to classify the detection results, yet they typically depend on labeled datasets, which are difficult to acquire due to t…

M-$LLM^3$REC: A Motivation-Aware User-Item Interaction Framework for Enhancing Recommendation Accuracy with LLMs
Lining Chen, Qingwen Zeng, Huaming Chen
https://arxiv.org/abs/2508.15262

M-$LLM^3$REC: A Motivation-Aware User-Item Interaction Framework for Enhancing Recommendation Accuracy with LLMs
Recommendation systems have been essential for both user experience and platform efficiency by alleviating information overload and supporting decision-making. Traditional methods, i.e., content-based filtering, collaborative filtering, and deep learning, have achieved impressive results in recommendation systems. However, the cold-start and sparse-data scenarios are still challenging to deal with. Existing solutions either generate pseudo-interaction sequence, which often introduces redundant …

Developers criticize Google for its decision to hide raw reasoning tokens, essential for debugging complex AI workflows, of its flagship model Gemini 2.5 Pro (Ben Dickson/VentureBeat)
https://venturebeat.com/ai/googles-gemin…

LLM-Based Community Surveys for Operational Decision Making in Interconnected Utility Infrastructures
Adaeze Okeukwu-Ogbonnaya, Rahul Amatapu, Jason Bergtold, George Amariucai
https://arxiv.org/abs/2507.13577

LLM-Based Community Surveys for Operational Decision Making in Interconnected Utility Infrastructures
We represent interdependent infrastructure systems and communities alike with a hetero-functional graph (HFG) that encodes the dependencies between functionalities. This graph naturally imposes a partial order of functionalities that can inform the sequence of repair decisions to be made during a disaster across affected communities. However, using such technical criteria alone provides limited guidance at the point where the functionalities directly impact the communities, since these can be r…

I understand why people are outraged, but actually it’s just a little bit more obvious what #Microsoft has been doing all along. What I don’t understand is the surprise and the naïveté: from its founding in 1975, Microsoft was literally built on lies. “But they promised!”—right, as if they had ever honored any of their “promises.”

Solving Zero-Sum Convex Markov Games
Fivos Kalogiannis, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Ian Gemp, Georgios Piliouras
https://arxiv.org/abs/2506.16120

Solving Zero-Sum Convex Markov Games
We contribute the first provable guarantees of global convergence to Nash equilibria (NE) in two-player zero-sum convex Markov games (cMGs) by using independent policy gradient methods. Convex Markov games, recently defined by Gemp et al. (2024), extend Markov decision processes to multi-agent settings with preferences that are convex over occupancy measures, offering a broad framework for modeling generic strategic interactions. However, even the fundamental min-max case of cMGs presents signi…

That's it, that’s the main statement describing Trump’s politics:
“I may do it. I may not do it. I mean, nobody knows what I'm going to do.” https://www.cbsnews.com/news/trump-attack-plans-iran-no-final-decision/

Data-Driven Abstraction and Synthesis for Stochastic Systems with Unknown Dynamics
Mahdi Nazeri, Thom Badings, Anne-Kathrin Schmuck, Sadegh Soudjani, Alessandro Abate
https://arxiv.org/abs/2508.15543

Data-Driven Abstraction and Synthesis for Stochastic Systems with Unknown Dynamics
We study the automated abstraction-based synthesis of correct-by-construction control policies for stochastic dynamical systems with unknown dynamics. Our approach is to learn an abstraction from sampled data, which is represented in the form of a finite Markov decision process (MDP). In this paper, we present a data-driven technique for constructing finite-state interval MDP (IMDP) abstractions of stochastic systems with unknown nonlinear dynamics. As a distinguishing and novel feature, our te…

Je moet echt dapper zijn als rechter bij het ICC
Trump administration sanctions Canadian judge who sits on International Criminal Court | CBC News
https://www.cbc.ca/news/world/canadian-judge-icc-trump-1.7613704

Defending Colts starting Daniel Jones at QB: Projection model loves decision to bench Anthony Richardson

https://www.cbssports.com/nfl/news/defendi

Robust Dynamic Material Handling via Adaptive Constrained Evolutionary Reinforcement Learning
Chengpeng Hu, Ziming Wang, Bo Yuan, Jialin Liu, Chengqi Zhang, Xin Yao
https://arxiv.org/abs/2506.16795

Robust Dynamic Material Handling via Adaptive Constrained Evolutionary Reinforcement Learning
Dynamic material handling (DMH) involves the assignment of dynamically arriving material transporting tasks to suitable vehicles in real time for minimising makespan and tardiness. In real-world scenarios, historical task records are usually available, which enables the training of a decision policy on multiple instances consisting of historical records. Recently, reinforcement learning has been applied to solve DMH. Due to the occurrence of dynamic events such as new tasks, adaptability is hig…

Officials in a large North Texas county decided this week to cut more than 100 Election Day polling sites -- and reduce the number of early voting locations,
amid growing concern about GOP efforts to limit voting access ahead of next year’s midterm elections.
The 3-2 vote on Tuesday by commissioners in Tarrant County, 💥which includes Fort Worth,
came one day after Donald Trump vowed to end the use of mail-in ballots.
The president lacks the unilateral power to decid…

A Texas County Cuts Over 100 Polling Sites as Trump Attacks Mail-In Voting Nationally
The decision by commissioners in Tarrant County, which includes Fort Worth, comes amid growing concern about GOP efforts to limit voting access ahead of next year’s midterm elections.

Expertise-aware Multi-LLM Recruitment and Collaboration for Medical Decision-Making
Liuxin Bao, Zhihao Peng, Xiaofei Zhou, Runmin Cong, Jiyong Zhang, Yixuan Yuan
https://arxiv.org/abs/2508.13754

Expertise-aware Multi-LLM Recruitment and Collaboration for Medical Decision-Making
Medical Decision-Making (MDM) is a complex process requiring substantial domain-specific expertise to effectively synthesize heterogeneous and complicated clinical information. While recent advancements in Large Language Models (LLMs) show promise in supporting MDM, single-LLM approaches are limited by their parametric knowledge constraints and static training corpora, failing to robustly integrate the clinical information. To address this challenge, we propose the Expertise-aware Multi-LLM Rec…

Micah Parsons Makes Decision on Cowboys’ Training Camp Amid Contract Dispute https://heavy.com/sports/nfl/dallas-cowboys/micah-parsons-decision-training-camp-contract-dispute/?adt_ei=[email]

The Judge Variable: Challenging Judge-Agnostic Legal Judgment Prediction
Guillaume Zambrano
https://arxiv.org/abs/2507.13732 https://…

The Judge Variable: Challenging Judge-Agnostic Legal Judgment Prediction
This study examines the role of human judges in legal decision-making by using machine learning to predict child physical custody outcomes in French appellate courts. Building on the legal realism-formalism debate, we test whether individual judges' decision-making patterns significantly influence case outcomes, challenging the assumption that judges are neutral variables that apply the law uniformly. To ensure compliance with French privacy laws, we implement a strict pseudonymization process.…

Major decision maker at Ukraine's central bank resigns after decade in key role: https://benborges.xyz/2025/08/15/major-decision-maker-at-ukraines.html

An Efficient Algorithm for Generating Minimal Unique-Cause MC/DC Test cases for Singular Boolean Expressions
Robin Lee, Youngho Nam
https://arxiv.org/abs/2507.14687

An Efficient Algorithm for Generating Minimal Unique-Cause MC/DC Test cases for Singular Boolean Expressions
Modified Condition/Decision Coverage (MC/DC) is a mandatory structural coverage criterion for ensuring the reliability and safety of critical systems. While its strictest form, Unique-Cause MC/DC, offers the highest assurance, research on its efficient test generation has been lacking. This gap is particularly significant, as an analysis of large-scale avionics systems shows that 99.7% of all conditional decisions are, in fact, Singular Boolean Expressions (SBEs) the ideal structure for applyin…

The Iranian Parliament has voted in support of closing the Strait of Hormuz,
one of the world's most critical oil transit chokepoints
Any final decision on retaliation will rest with the country's Supreme National Security Council and leader Ayatollah Ali Khamenei.
The parliament vote merely advises him of the option to pursue.

Iran's Parliament Votes To Close Straits of Hormuz After US Attacks
The vote took place Sunday after the U.S. on Saturday evening hit three Iranian nuclear sites and significantly damaged the country's capabilities.

Toward Deployable Multi-Robot Collaboration via a Symbolically-Guided Decision Transformer
Rathnam Vidushika Rasanji, Jin Wei-Kocsis, Jiansong Zhang, Dongming Gan, Ragu Athinarayanan, Paul Asunda
https://arxiv.org/abs/2508.13877

Toward Deployable Multi-Robot Collaboration via a Symbolically-Guided Decision Transformer
Reinforcement learning (RL) has demonstrated great potential in robotic operations. However, its data-intensive nature and reliance on the Markov Decision Process (MDP) assumption limit its practical deployment in real-world scenarios involving complex dynamics and long-term temporal dependencies, such as multi-robot manipulation. Decision Transformers (DTs) have emerged as a promising offline alternative by leveraging causal transformers for sequence modeling in RL tasks. However, their applic…

Dynamic Transmission Line Switching Amidst Wildfire-Prone Weather Under Decision-Dependent Uncertainty
Juan-Alberto Estrada-Garcia, Ruiwei Jiang, Alexandre Moreira
https://arxiv.org/abs/2507.13611

Dynamic Transmission Line Switching Amidst Wildfire-Prone Weather Under Decision-Dependent Uncertainty
During dry and windy seasons, environmental conditions significantly increase the risk of wildfires, exposing power grids to disruptions caused by transmission line failures. Wildfire propagation exacerbates grid vulnerability, potentially leading to prolonged power outages. To address this challenge, we propose a multi-stage optimization model that dynamically adjusts transmission grid topology in response to wildfire propagation, aiming to develop an optimal response policy. By accounting for…

In-Context Decision Making for Optimizing Complex AutoML Pipelines
Amir Rezaei Balef, Katharina Eggensperger
https://arxiv.org/abs/2508.13657 https://arxiv…

In-Context Decision Making for Optimizing Complex AutoML Pipelines
Combined Algorithm Selection and Hyperparameter Optimization (CASH) has been fundamental to traditional AutoML systems. However, with the advancements of pre-trained models, modern ML workflows go beyond hyperparameter optimization and often require fine-tuning, ensembling, and other adaptation techniques. While the core challenge of identifying the best-performing model for a downstream task remains, the increasing heterogeneity of ML pipelines demands novel AutoML approaches. This work extend…

Dallas Cowboys Making Major Decision on Star Cornerback https://www.newsweek.com/sports/nfl/dallas-cowboys-making-major-decision-star-cornerback-2101225

Understanding the Impact of Physicians' Legal Considerations on XAI Systems
Gennie Mansi, Mark Riedl
https://arxiv.org/abs/2507.15996 https://

Understanding the Impact of Physicians' Legal Considerations on XAI Systems
Physicians are--and feel--ethically, professionally, and legally responsible for patient outcomes, buffering patients from harmful AI determinations from medical AI systems. Many have called for explainable AI (XAI) systems to help physicians incorporate medical AI recommendations into their workflows in a way that reduces the potential of harms to patients. While prior work has demonstrated how physicians' legal concerns impact their medical decision making, little work has explored how XAI sy…

Diffusion-based Counterfactual Augmentation: Towards Robust and Interpretable Knee Osteoarthritis Grading
Zhe Wang, Yuhua Ru, Aladine Chetouani, Tina Shiang, Fang Chen, Fabian Bauer, Liping Zhang, Didier Hans, Rachid Jennane, William Ewing Palmer, Mohamed Jarraya, Yung Hsin Chen
https://arxiv.org/abs/2506.15748

Diffusion-based Counterfactual Augmentation: Towards Robust and Interpretable Knee Osteoarthritis Grading
Automated grading of Knee Osteoarthritis (KOA) from radiographs is challenged by significant inter-observer variability and the limited robustness of deep learning models, particularly near critical decision boundaries. To address these limitations, this paper proposes a novel framework, Diffusion-based Counterfactual Augmentation (DCA), which enhances model robustness and interpretability by generating targeted counterfactual examples. The method navigates the latent space of a diffusion model…

Georgia Bulldogs football legend Brock Bowers reveals Raiders’ draft decision shocked his agent https://www.sportingnews.com/us/ncaa-football/news/georgia-bulldogs-football-legend…

Testing the variety hypothesis
A. Lerario, P. Roos Hoefgeest, M. Scolamiero, A. Tamai
https://arxiv.org/abs/2507.16705 https://arxiv.…

Testing the variety hypothesis
Given a probability measure on the unit disk, we study the problem of deciding whether, for some threshold probability, this measure is supported near a real algebraic variety of given dimension and bounded degree. We call this "testing the variety hypothesis". We prove an upper bound on the so-called "sample complexity" of this problem and show how it can be reduced to a semialgebraic decision problem. This is done by studying in a quantitative way the Hausdorff geometry of the space of real a…

NFL stars back in action, plus ranking the top 10 WR duos and trying to make sense of the Colts' QB decision

https://www.cbssports.com/nfl/news/nfl-st…

Distributed Kaplan-Meier Analysis via the Influence Function with Application to COVID-19 and COVID-19 Vaccine Adverse Events
Malcolm Risk, Xu Shi, Lili Zhao
https://arxiv.org/abs/2507.14351

Distributed Kaplan-Meier Analysis via the Influence Function with Application to COVID-19 and COVID-19 Vaccine Adverse Events
During the COVID-19 pandemic, regulatory decision-making was hampered by a lack of timely and high-quality data on rare outcomes. Studying rare outcomes following infection and vaccination requires conducting multi-center observational studies, where sharing individual-level data is a privacy concern. In this paper, we conduct a multi-center observational study of thromboembolic events following COVID-19 and COVID-19 vaccination without sharing individual-level data. We accomplish this by devel…

ADRD: LLM-Driven Autonomous Driving Based on Rule-based Decision Systems
Fanzhi Zeng, Siqi Wang, Chuzhao Zhu, Li Li
https://arxiv.org/abs/2506.14299 https:…

ADRD: LLM-Driven Autonomous Driving Based on Rule-based Decision Systems
How to construct an interpretable autonomous driving decision-making system has become a focal point in academic research. In this study, we propose a novel approach that leverages large language models (LLMs) to generate executable, rule-based decision systems to address this challenge. Specifically, harnessing the strong reasoning and programming capabilities of LLMs, we introduce the ADRD(LLM-Driven Autonomous Driving Based on Rule-based Decision Systems) framework, which integrates three co…

Language Models Change Facts Based on the Way You Talk
Matthew Kearney, Reuben Binns, Yarin Gal
https://arxiv.org/abs/2507.14238 https://

Language Models Change Facts Based on the Way You Talk
Large language models (LLMs) are increasingly being used in user-facing applications, from providing medical consultations to job interview advice. Recent research suggests that these models are becoming increasingly proficient at inferring identity information about the author of a piece of text from linguistic patterns as subtle as the choice of a few words. However, little is known about how LLMs use this information in their decision-making in real-world applications. We perform the first c…

CBS to Cancel 'Late Show With Stephen Colbert' Citing 'Financial Decision' (Brian Steinberg/Variety)
https://variety.com/2025/tv/news/cbs-cancel-late-show-stephen-colbert-financial-decision-1236464356/
http://www.memeorandum.com/250717/p140#a250717p140

Patrick Mahomes says he didn't talk to Travis Kelce about retirement decision prior to upcoming season

https://www.cbssports.com/nfl/news/patric…

Mobile-Agent-v3: Foundamental Agents for GUI Automation
Jiabo Ye, Xi Zhang, Haiyang Xu, Haowei Liu, Junyang Wang, Zhaoqing Zhu, Ziwei Zheng, Feiyu Gao, Junjie Cao, Zhengxi Lu, Jitong Liao, Qi Zheng, Fei Huang, Jingren Zhou, Ming Yan
https://arxiv.org/abs/2508.15144

Mobile-Agent-v3: Foundamental Agents for GUI Automation
This paper introduces GUI-Owl, a foundational GUI agent model that achieves state-of-the-art performance among open-source end-to-end models on ten GUI benchmarks across desktop and mobile environments, covering grounding, question answering, planning, decision-making, and procedural knowledge. GUI-Owl-7B achieves 66.4 on AndroidWorld and 29.4 on OSWorld. Building on this, we propose Mobile-Agent-v3, a general-purpose GUI agent framework that further improves performance to 73.3 on AndroidWorld…

Systematic Evaluation of Wavelet-Based Denoising for MRI Brain Images: Optimal Configurations and Performance Benchmarks
Asadullah Bin Rahman, Masud Ibn Afjal, Md. Abdulla Al Mamun
https://arxiv.org/abs/2508.15011

Systematic Evaluation of Wavelet-Based Denoising for MRI Brain Images: Optimal Configurations and Performance Benchmarks
Medical imaging modalities including magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound are essential for accurate diagnosis and treatment planning in modern healthcare. However, noise contamination during image acquisition and processing frequently degrades image quality, obscuring critical diagnostic details and compromising clinical decision-making. Additionally, enhancement techniques such as histogram equalization may inadvertently amplify existing noise artifacts, …

Event-Triggered Resilient Consensus of Networked Euler-Lagrange Systems Under Byzantine Attacks
Yuliang Fu, Guanghui Wen, Dan Zhao, Wei Xing Zheng, Xiaolei Li
https://arxiv.org/abs/2507.15283

Event-Triggered Resilient Consensus of Networked Euler-Lagrange Systems Under Byzantine Attacks
The resilient consensus problem is investigated in this paper for a class of networked Euler-Lagrange systems with event-triggered communication in the presence of Byzantine attacks. One challenge that we face in addressing the considered problem is the inapplicability of existing resilient decision algorithms designed for one-dimensional multi-agent systems. This is because the networked Euler-Lagrange systems fall into the category of multi-dimensional multi-agent systems with coupling among …

DiCriTest: Testing Scenario Generation for Decision-Making Agents Considering Diversity and Criticality
Qitong Chu, Yufeng Yue, Danya Yao, Huaxin Pei
https://arxiv.org/abs/2508.11514

DiCriTest: Testing Scenario Generation for Decision-Making Agents Considering Diversity and Criticality
The growing deployment of decision-making agents in dynamic environments increases the demand for safety verification. While critical testing scenario generation has emerged as an appealing verification methodology, effectively balancing diversity and criticality remains a key challenge for existing methods, particularly due to local optima entrapment in high-dimensional scenario spaces. To address this limitation, we propose a dual-space guided testing framework that coordinates scenario param…

Chiefs' Travis Kelce says returning for 2025 season 'wasn't that hard of a decision' https://www.nfl.com/news/chiefs-travis-kelce-says-returning-for-2025-season-wasn-t-that-hard-of-a-decision

Court’s gender-affirming care ruling will impair all sex-based rights, say critics | US supreme court | The Guardian
https://www.theguardian.com/us-news/2025/jun/18/supreme-court-gender-affirming-care-decision

Effect Identification and Unit Categorization in the Multi-Score Regression Discontinuity Design with Application to LED Manufacturing
Philipp Alexander Schwarz, Oliver Schacht, Sven Klaassen, Johannes Oberpriller, Martin Spindler
https://arxiv.org/abs/2508.15692

Effect Identification and Unit Categorization in the Multi-Score Regression Discontinuity Design with Application to LED Manufacturing
The RDD (regression discontinuity design) is a widely used framework for identification and estimation of causal effects at a cutoff of a single running variable. Practical settings, in particular those encountered in production systems, often involve decision-making defined by multiple thresholds and criteria. Common MRD (multi-score RDD) approaches transform these to a one-dimensional design, to employ identification and estimation results. However, this practice can introduce non-compliant b…

An Online A/B Testing Decision Support System for Web Usability Assessment Based on a Linguistic Decision-making Methodology: Case of Study a Virtual Learning Environment
Noe Zerme\~no, Cristina Zuheros, Lucas Daniel Del Rosso Calache, Francisco Herrera, Rosana Montes
https://arxiv.org/abs/2507.12118

An Online A/B Testing Decision Support System for Web Usability Assessment Based on a Linguistic Decision-making Methodology: Case of Study a Virtual Learning Environment
In recent years, attention has increasingly focused on enhancing user satisfaction with user interfaces, spanning both mobile applications and websites. One fundamental aspect of human-machine interaction is the concept of web usability. In order to assess web usability, the A/B testing technique enables the comparison of data between two designs. Expanding the scope of tests to include the designs being evaluated, in conjunction with the involvement of both real and fictional users, presents a…

See What I Mean? Expressiveness and Clarity in Robot Display Design
Matthew Ebisu, Hang Yu, Reuben Aronson, Elaine Short
https://arxiv.org/abs/2506.16643 h…

See What I Mean? Expressiveness and Clarity in Robot Display Design
Nonverbal visual symbols and displays play an important role in communication when humans and robots work collaboratively. However, few studies have investigated how different types of non-verbal cues affect objective task performance, especially in a dynamic environment that requires real time decision-making. In this work, we designed a collaborative navigation task where the user and the robot only had partial information about the map on each end and thus the users were forced to communicat…

Cowboys Final Decision at RB Looks ‘Inevitable’ https://heavy.com/sports/nfl/dallas-cowboys/decision-rb-looks-inevitable/?adt_ei=[email]

MAGA star Steve Bannon plays outsized role in Trump's Iran decision: Sources (ABC News)
https://abcnews.go.com/Politics/maga-star-steve-bannon-plays-outsized-role-trumps/story?id=123054297
http://www.memeorandum.com/250621/p33#a250621p33

EEG-MedRAG: Enhancing EEG-based Clinical Decision-Making via Hierarchical Hypergraph Retrieval-Augmented Generation
Yi Wang, Haoran Luo, Lu Meng
https://arxiv.org/abs/2508.13735

EEG-MedRAG: Enhancing EEG-based Clinical Decision-Making via Hierarchical Hypergraph Retrieval-Augmented Generation
With the widespread application of electroencephalography (EEG) in neuroscience and clinical practice, efficiently retrieving and semantically interpreting large-scale, multi-source, heterogeneous EEG data has become a pressing challenge. We propose EEG-MedRAG, a three-layer hypergraph-based retrieval-augmented generation framework that unifies EEG domain knowledge, individual patient cases, and a large-scale repository into a traversable n-ary relational hypergraph, enabling joint semantic-tem…

AIM-Bench: Evaluating Decision-making Biases of Agentic LLM as Inventory Manager
Xuhua Zhao, Yuxuan Xie, Caihua Chen, Yuxiang Sun
https://arxiv.org/abs/2508.11416 https://

AIM-Bench: Evaluating Decision-making Biases of Agentic LLM as Inventory Manager
Recent advances in mathematical reasoning and the long-term planning capabilities of large language models (LLMs) have precipitated the development of agents, which are being increasingly leveraged in business operations processes. Decision models to optimize inventory levels are one of the core elements of operations management. However, the capabilities of the LLM agent in making inventory decisions in uncertain contexts, as well as the decision-making biases (e.g. framing effect, etc.) of th…

Steichen 'very close' to decision in Colts' QB race https://www.espn.com/nfl/story/_/id/45996656/colts-steichen-nears-decision-jones-richardson-qb-race

TRUST: Transparent, Robust and Ultra-Sparse Trees
Albert Dorador
https://arxiv.org/abs/2506.15791 https://arxiv.org/pdf/2506.15791

TRUST: Transparent, Robust and Ultra-Sparse Trees
Piecewise-constant regression trees remain popular for their interpretability, yet often lag behind black-box models like Random Forest in predictive accuracy. In this work, we introduce TRUST (Transparent, Robust, and Ultra-Sparse Trees), a novel regression tree model that combines the accuracy of Random Forests with the interpretability of shallow decision trees and sparse linear models. TRUST further enhances transparency by leveraging Large Language Models to generate tailored, user-friendl…

A young female bear caused a stir after wandering out of the forest and into the leafy suburbs of the Lithuanian capital.
For two days, the brown bear ambled through the neighborhoods of Vilnius,
trotted across highways and explored backyards
— all while being chased by onlookers with smartphones and, eventually, drones.
The government then issued a permit for the bear to be shot and killed.
That did not go down well with Lithuania’s hunters who refused, aware …

Lithuanian hunters refuse government request to shoot a wild bear in the capital
Lithuanian hunters have refused to shoot a wild bear that was spotted roaming around the Lithuanian capital of Vilnius and criticized the government for issuing a permit to kill a member of the protected species. The Lithuanian Association of Hunters and Fishermen says in a statement it is shocked by the decision of the Environment Ministry to shoot the bear. The bear now seems to be out of danger as it was spotted on Wednesday walking through forested areas well outside the city. A government …

NFL writer urges Cowboys to make big decision on Micah Parsons's contract https://www.sportingnews.com/us/nfl/dallas-cowboys/news/nfl-writer-urges-cowboys-make-big-decision-micah-pars…

Did the Raiders Make the Right Decision? https://www.si.com/nfl/raiders/news/josh-jacobs-green-bay-packers-ashton-jeanty-matt-lafleur-jordan-love-john-spytek

Colts HC Shane Steichen 'very close' to QB1 decision between Anthony Richardson, Daniel Jones https://www.nfl.com/news/colts-hc-shane-steichen-very-close-to-qb1-decision-between-anthony-richardson-daniel-jones…

Cowboys 'will regret' crucial yet under-the-radar offseason decision https://www.sportingnews.com/us/nfl/dallas-cowboys/news/cowboys-will-regret-crucial-yet-under-radar-offseason-decision/8f86b7…

Uncertainty-Informed Scheduling of Decision Points for Intelligent Mobile Health Interventions
Asim H. Gazi, Bhanu T. Gullapalli, Daiqi Gao, Benjamin M. Marlin, Vivek Shetty, Susan A. Murphy
https://arxiv.org/abs/2507.10798

Uncertainty-Informed Scheduling of Decision Points for Intelligent Mobile Health Interventions
Timely decision making is critical to the effectiveness of mobile health (mHealth) interventions. At predefined timepoints called "decision points," intelligent mHealth systems such as just-in-time adaptive interventions (JITAIs) estimate an individual's biobehavioral context from sensor or survey data and determine whether and how to intervene. For interventions targeting habitual behavior (e.g., oral hygiene), effectiveness often hinges on delivering support shortly before the target behavior…

NFL Makes Final Decision on CeeDee Lamb Punishment for Preseason Penalty https://heavy.com/sports/nfl/dallas-cowboys/nfl-final-decision-ceedee-lamb-punishment/?adt_ei=[email]

Colts QB Anthony Richardson says he 'respects' the decision made to name Daniel Jones starting QB

https://www.cbssports.com/nfl/news/colts-q

NFL writer thinks Cowboys could make QB decision that could impact Dak Prescott https://www.sportingnews.com/us/nfl/dallas-cowboys/news/nfl-writer-thinks-cowboys-could-make-qb-dec…

ESPN Makes Shocking Decision On Injured $5 Million Cowboys LB https://heavy.com/sports/nfl/dallas-cowboys/shocking-decision-linebacker-demarvion-overshown/?adt_ei=[email]