OpenAI outlines its public policy agenda for AI, including safety, youth protection, workforce transition, and global standards to ensure AI benefits society.

OpenAI outlines a blueprint for U.S. governance of frontier AI, proposing a federal framework for safety, resilience, and national security.

Several real estate listings in the San Francisco Bay Area are offering to exchange a home for a piece of the AI startup.

Walmart has reportedly begun limiting employees’ use of an internal AI assistant called Code Puppy after demands placed on the LLM backing the tool were higher than expected. Employees of Walmart were encouraged to use Code Puppy without any stricture or stipulations as to the limits of use, but Walmart is now assigning employees a […] The post Walmart’s AI workflows meet the realities of the balance sheet appeared first on AI News.

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Microsoft’s Majorana 2 quantum chiparrived this week, with numbers that are genuinely difficult to contextualise: qubits 1,000 times more reliable than those of the first generation models, a mean qubit lifetime of 20 seconds against an industry norm measured in microseconds, and a revised roadmap targeting a commercially scalable quantum computer by 2029. Behind those […] The post Microsoft’s Majorana 2 quantum chip is also a case study for agentic AI in R&D appeared first on AI News.

Soccer fans on r/WorldCup2026Tickets are using Claude to build DIY ticketing software, exchanging on back channels, and leaving scalpers scrambling.

PLUS: Legendary Hollywood director opens the door to AI

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Meta is spending at hyperscaler scale on artificial intelligence infrastructure, $125 billion to $145 billion in … Meta’s Cloud Computing Signal: How AI Data Center Spending Could Become A Hyperscaler BusinessRead more The post Meta’s Cloud Computing Signal: How AI Data Center Spending Could Become A Hyperscaler Business appeared first on .

The Morrigan is being used to bombard Russia's R280 logistics highway, the Nemesis Brigade said. 412 Nemesis Brigade Ukraine has a new mid-range drone called the Morrigan that's hitting areas Russia once deemed safe. The 412th said it used the drone to attack the R-280 highway, about 50 to 75 miles from the front. Ukraine has been increasingly using these types of drones to push Russia's supply lines back. Ukrainian troops released new details of the secretive mid-range drone they're using to batter Russia's R-280 logistics highway far behind the southern front lines. The 412th Nemesis Brigade, of the Unmanned Systems Forces, published close-up and pre-launch footage on Saturday of the strike aircraft, dubbed the Morrigan. The fixed-wing drone, sporting a single-propeller engine on its nose, is locally produced and "designed to operate behind enemy lines," the brigade said in a statement. "With the permission of the manufacturer, we are lifting the curtain: What kind of secret drone is this?" it wrote, calling the Morrigan its "secret weapon" at mid-range. A clip of the Morrigan being readied for flight shows it to be roughly 4 to 5 feet long, with swept wings and two tail fins. The drone appears to be launched from a rail or slingshot platform, allowing it to take off without a runway. The Morrigan is one entry in an emerging drone class that Ukraine is using more frequently this year to attack Russian forces and logistics about 20 to 300 kilometers, or 12 to 186 miles, behind the front lines. They're usually lighter than the long-range drones that strike Russia's defense and oil industries. But they use a fixed-wing design instead of the first-person-view quadcopters dominating the battlefield. The goal with these mid-range drones, analysts and Ukrainian officials have said, has been to slow Russia's advance by forcing it to pull back from what it deems safe areas for supply routes. That's what the 412th did with the Morrigan, attacking a 370-mile route called the R280 "Novorossiya" highway used by Russia to supply its southern front. "This aircraft has already operated in Crimea on several occasions and destroyed top Russian air defense and support targets," the 412th wrote. "And right now, it is conducting a logistical hunt from Mariupol to Crimea." The R280 runs from Rostov-on-Don to Crimea, spanning all the occupied Ukrainian territory in the south. It's typically about 50 to 75 miles from the front lines, following the coast of the Sea of Azov and passing through cities such as Mariupol and Melitopol. Last week, the 412th uploaded clips of several drone attacks on supply and fuel convoys driving along a highway, saying it had destroyed "dozens" of Russian trucks and gas stations. The unit didn't reveal the Morrigan's name at the time, referring to it as a "secret wing" specifically built for the attack mission. Meanwhile, Russian-backed officials in the occupied territories said on Monday that they were working on alternative routes for the R280 highway, citing intensified Ukrainian attacks since mid-May. The route is also used by civilian motorists and commercial transport. Russian state media outlet TASS highlighted at least five Ukrainian attacks on the R280 last week, with at least three involving supply or fuel trucks. On May 21, the Russian-backed governor of the Kherson region, Vladimir Saldo, ordered a temporary closure of part of the highway to non-essential civilian traffic. Read the original article on Business Insider

Block CEO Jack Dorsey, Salesforce CEO Marc Benioff, IBM CEO Arvind Krishna (left to right). Joe Raedle/Getty Images, AP Photo/Markus Schreiber, Sajjad Hussain/Getty Images Companies like Snap, Block, and Wix cited AI as a factor in recent layoffs. In early June, GitLab said it would cut 350 employees in an overhaul to meet the "agentic era." Cisco announced about 4,000 layoffs on May 13, citing intensifying competition in the AI era. Worries about AI one day replacing human workers have intensified recently — and as it turns out, that future may be here. A number of companies have recently announced staff cuts and cited AI efficiencies as a major rationale. A March report from career transition firm Challenger, Gray, and Christmas found that, so far this year, AI has been cited in 8% of job-cut plans. Amid this rash of layoffs, some have asked whether AI is replacing so many roles once held by humans or whether some degree of "AI washing" is at work. OpenAI's Sam Altman said some companies are blaming AI for layoffs that would've happened regardless. An MIT study released last year said that 95% of corporate AI investments have generated "zero return" so far. As some companies replace human workers with the technology, they may end up hiring more people because of it — or rehiring at least some of the roles they eliminated. A 2025 survey conducted by consulting firm Robert Half found that 29% of 2,000 hiring managers said they reopened positions that had been previously got rid of after implementing AI. Here's a list of companies that have done AI-related layoffs: Angi Bloomberg/Getty Images Angi, the popular contractor listing site previously known as Angie's List, said in January that it was cutting roughly 350 jobs in part because of "AI-driven efficiency improvements." The company added that the cuts were part of a plan "to reduce operating expenses and optimize the organizational structure in support of long-term growth." Atlassian Last year, Atlassian CEO Mike Cannon-Brookes said that his company would have more engineers working for it in five years than it did then. Brendan McDermid/Reuters Atlassian announced cuts of 1,600 jobs in March, totaling about 10% of its global workforce. The move comes as the Australian-American software company says it is restructuring to focus on AI and enterprise growth. In a filing with the US Securities and Exchange Commission, the company said the reduction was part of a broader effort to reposition the business for what CEO Mike Cannon-Brookes described as the "AI era." "It would be disingenuous to pretend AI doesn't change the mix of skills we need or the number of roles required in certain areas. It does," Cannon-Brookes wrote in a message to employees. On the "20VC" podcast in October last year, prior to the cuts, Cannon-Brookes said he planned to have more engineers at the company in five years. "They will be more efficient, but technology creation is not output-bound," Cannon-Brookes said. Block Joe Raedle/Getty Images In a post on X in February, billionaire and Block CEO Jack Dorsey said he was slashing nearly half of Block's workforce, cutting its over 10,000-person staff to under 6,000. The move came as he said business was strong and profits were growing, but a new way of working was emerging. "We're already seeing that the intelligence tools we're creating and using, paired with smaller and flatter teams, are enabling a new way of working which fundamentally changes what it means to build and run a company," Dorsey said in his memo on X. In the company's earnings call following the memo, Dorsey said that more companies will follow suit by using AI to drive efficiency gains. Block is already ahead of the trend that "all companies will eventually" adopt, the CEO said. Cisco Cisco CEO Chuck Robbins on May 13 announced that the company would be laying off about 4,000 staff. Kent NISHIMURA / AFP via Getty Images Cisco said on May 13 that it would cut "fewer than 4,000 jobs" as the networking company reorganizes around artificial intelligence, according to a memo CEO Chuck Robbins sent to employees. "The companies that will win in the AI era will be those with focus, urgency, and the discipline to continuously shift investment toward the areas where demand and long-term value creation are strongest," Robbins said in the memo. "This means making hard decisions — about where we invest, how we're organized, and how our cost structure reflects the opportunity in front of us." The layoffs, which account for less than 5% of Cisco's workforce, were announced alongside a stronger-than-expected third-quarter earnings report in which the company raised its revenue outlook amid surging demand for AI infrastructure. In the memo, Robbins said Cisco is redirecting investments toward areas "where demand and long-term value creation are strongest," including silicon, optics, security, and employees' use of AI across the company. Cloudflare IMF Cloudflare announced on May 7 that it will be slashing more than 1,100 roles as it reorganizes for the "agentic AI era." The cybersecurity company said in a memo that its AI usage has increased by over 600% in the last three months, and employees across departments run thousands of agent sessions each day. "That means we have to be intentional in how we architect our company for the agentic AI era in order to supercharge the value we deliver to our customers," the company said in the memo to staff. Cloudflare CEO Matthew Prince responded to a critical post on X, saying that "very few engineers or customer-facing sales people impacted by our layoff." He wrote that the company will continue to hire "like crazy in those roles," as it did as a startup. Cloudflare employed 5,483 people as of the end of March, meaning the cuts affected about 20% of its workforce. Coinbase Coinbase CEO Brian Armstrong. Bloomberg/Getty Coinbase CEO Brian Armstrong announced that the company will be slashing 14% of its workforce, or about 700 workers. In a post on X on May 5, Armstrong shared an email that he said he sent to workers earlier that day. In the post, he cited two factors: a volatile market and AI changing the way people work. "Over the past year, I've watched engineers use AI to ship in days what used to take a team weeks," Armstrong said, adding that, "the pace of what's possible with a small, focused team has changed dramatically." Armstrong said the company isn't just reducing head count and cutting costs, but "fundamentally changing" the way it operates. The CEO said Coinbase is rebuilding itself "as an intelligence, with humans around the edge aligning it." He shared plans to concentrate the workforce around AI-native pods that will manage fleets of agents. Armstrong said the company will also experiment with "one person teams" of engineers, designers, and product managers. Crypto.com Marco Bello/Reuters Crypto.com announced on March 19 that it would cut 12% of its staff. The CEO, Kris Marszalek, wrote in a post on X that those impacted were in "roles that do not adapt in our new world." "We are joining the list of companies integrating enterprise-wide AI," Marszalek wrote on X. "Companies that move immediately and pair the best AI tools with top-performers will achieve a level of scale and precision that was previously impossible. This is where we must go." The company previously cut jobs in 2022 during a cryptocurrency slump and another 20% of its workforce in 2023, following the collapse of FTX. GitLab Joan Cros/NurPhoto via Getty Images On a June 2 earnings call, GitLab said it is cutting 350 employees, or about 14% of its workforce, as part of an overhaul it announced last month. The coding software company, which had 2,580 employees as of January, said in May that it was restructuring to meet the "agentic era." GitLab added that it wanted to remove up to three layers of management and reinvest savings from the restructuring into internal AI resources. The company said it also expects to exit 22 countries and reduce its team members' geographic footprint by about 37%, opting for customers in those regions to be served by partners. In June 2025, GitLab's chief financial officer, Brian Robins, said that AI coding has been good for its business, as customers added more employees to their subscriptions and produced more code, which GitLab's services help manage. HP Lores ends each day with reflection about HP's present and future. HP Inc. HP said it's reducing the size of its corporate workforce due to AI initiatives. In an earnings report last November, the company said it plans to cut between 4,000 and 6,000 jobs by the end of 2028, estimating the changes would save around $1 billion. HP's earnings presentation at the time said part of its strategy was to cut costs through "workforce reductions, platform simplification, programs consolidation, and productivity measures" and to increase customer satisfaction, innovation, and productivity with "artificial intelligence adoption and enablement." IBM Arvind Krishna has been spent his entire career at IBM. He was made CEO of the company in 2020. Sajjad Hussain/Getty Images Arvind Krishna, CEO of IBM, told The Wall Street Journal last year that it had replaced hundreds of human resources employees with AI. More recently, the company announced last November that it would cut thousands of workers in the fourth quarter of 2025, affecting a "single-digit percentage of its global workforce." Its CEO, Arvind Krishna, said the company is shifting priorities to hire more people around AI and quantum. He also said the company plans to increase hiring among recent college graduates over the next year. Krishna has also said that AI adoption has led the company to hire more employees in programming and sales. In 2023, Krishna told Bloomberg that IBM had halted or slowed hiring for back-office roles, like in human resources, that could be replaced by AI. "I could easily see 30% of that getting replaced by AI and automation over a five-year period," he told the outlet at the time. Salesforce Salesforce CEO Marc Benioff says Gemini 3 is so advanced that he has stopped using ChatGPT. AP Photo/Markus Schreiber Salesforce cut fewer than 1,000 workers in February, including employees from marketing, product management, data analytics, and its Agentforce AI product. In an episode of "The Logan Bartlett Show" released last August, Salesforce CEO Marc Benioff said the company was using AI agents in its customer support division to replace humans and handle more sales leads. "I was able to rebalance my head count on my support," he said in the interview. "I've reduced it from 9,000 heads to about 5,000 because I need less heads." A Salesforce spokesperson previously told Business Insider that Benioff was referring to an organizational transformation that took place over several months to reshape its customer support function. After deploying Agentforce, the company no longer needed to "actively backfill support engineer roles," the spokesperson said, adding that it successfully redeployed hundreds of employees into other areas of the company, like professional services, sales, and customer success. Snap Bloomberg/Getty Images In a memo to employees released in a regulatory filing on April 15, Snap CEO Evan Spiegel said the company would cut 1,000 employees, or about 16% of its global workforce. The CEO cited "rapid advancements" in AI and "small squads" using it to become more efficient. Spiegel said Snap would also close more than 300 open roles, and that US-based employees would receive four months of severance, healthcare coverage, and equity vesting. In an investor update included in the company's filing, it said the layoffs would result in roughly $500 million in annualized cost savings. Standard Chartered Bill Winters is the CEO of Standard Chartered. Bloomberg/Getty Images Global bank Standard Chartered announced plans on May 19 to slash 15% of its staff by 2030. CEO Bill Winters said in a media briefing in Hong Kong that the move isn't a cost-cutting effort, but rather, "replacing, in some cases, lower-value human capital with the financial capital and the investment capital that we are putting in," Bloomberg reported. "We don't have job losses, but we do have job role reductions in favor of the machines, and that will accelerate as we go forward into AI," he said at the briefing. The company added in a statement: "We are combining the best human talent with AI, investing to support our people into higher-value roles." Wisetech Wisetech is cutting 2,000 jobs. Illustration by Thomas Fuller/SOPA Images/LightRocket via Getty Images Zubin Appoo, the CEO of Wisetech, said the logistics software maker is cutting 2,000 jobs, or 30% of its staff, because of AI-led efficiency. In a conference call on February 25, Appoo said that AI enables greater productivity in less time and with fewer employees. The Sydney-based company employed about 7,000 people, according to an annual report released in October. "I am prepared to say this clearly: the era of manually writing code as the core act of engineering is over," Appoo said. The technology is "unlocking levels of efficiency gains across WiseTech that were previously out of reach." In some parts of the workforce, such as customer service, one in two workers will disappear, he added. Wix Wix; BI Wix announced it would be cutting 20% of its workforce, citing currency challenges and AI. In a post on X on May 28, Wix CEO Avishai Abrahami shared the layoff memo he sent to the team, saying that the first reason for the cuts was that the "exchange rate between the Shekel and the US dollar has shifted significantly." He also cited "the fast evolution of AI capabilities." "This is not just about adopting new tools - it is about rewiring how companies are built, how they think, how they manage and how they operate," Abrahami wrote in the post. Abrahami said the company will operate leaner and flatter, and will continue to take steps toward an AI-native way of working. The company previously employed just under 5,300 workers, meaning roughly 1,000 roles will be affected. Correction: May 19, 2026 — An earlier version of this story included Klarna. The company says it has not done AI-related layoffs. Read the original article on Business Insider

Australia’s economy grew by 0.3% in the first three months of 2026, slowing from 0.9% growth at the end of 2025, according to the latest Australian Bureau of Statistics figures. Over the year to March, gross domestic product (GDP) rose 2.5%. But GDP per person – our total GDP, divided by our population – actually fell 0.1% in the quarter. This shows Australians were not necessarily feeling better off, despite the economy still growing overall. The weaker-than-expected growth result is likely to reinforce the likelihood of the Reserve Bank leaving interest rates unchanged at its June meeting, after lifting rates in February, March and and May. While inflation remains a concern, today’s figures suggest those rate rises were already beginning to weigh on household spending and economic activity. Higher fuel prices took a toll The Middle East war, which began on February 28, had a clear effect on Australia’s economy through higher fuel and fertiliser prices. The Australian Bureau of Statistics (ABS) noted automotive fuel prices rose sharply towards the end of the March quarter. The federal government’s fuel discounts only started on April 1. Households responded by spending more on essentials and cutting back elsewhere. Discretionary spending was very weak, suggesting many consumers were becoming more cautious. Spending on electricity, gas and other fuels also rose sharply after energy rebates ended, while spending on operating vehicles increased amid concerns about petrol and diesel supplies. Which parts of the economy grew? The strongest part of the economy was investment. Private investment rose strongly, led by a large jump in machinery and equipment investment. The ABS said this reflected increased business investment in data centres in New South Wales and Victoria. That investment boom highlights one important theme: businesses are continuing to invest heavily in digital infrastructure and artificial intelligence, despite a challenging economic environment. The GDP figures suggest Australia’s economy is becoming increasingly split in two. Sectors linked to data centres, engineering services, IT consulting and construction are expanding rapidly, while many consumer-facing industries remain under pressure. Household consumption also grew – but the increase was concentrated in essentials, rather than discretionary spending. That is not a sign of strong consumer confidence. It suggests households were spending more because some necessary items became more expensive, or they may have been worried about supply chain shortages. How reducing ‘just in case’ purchases can help avoid empty shelves and fuel bowsers Which parts of the economy shrank? Net trade was the main drag on growth. Exports fell while imports rose. The fall in exports was driven by coal and iron ore, with bad weather disrupting port operations. Imports rose partly because of record imports of automatic data processing equipment, linked to data centre investment. Government spending also fell, partly because energy bill relief ended. Mining saw the largest industry decline, with coal production hit by Cyclone Koji. Consumer-facing services were weak. Retail trade, accommodation and food services, and arts and recreation all reflected subdued discretionary spending. Watching for a per person recession The key question is whether this is just a temporary slowdown, or the start of a more worrying loss of momentum. The economy is still growing, but GDP per person has fallen. This happens when a country’s population is growing faster than its economy. And that matters because GDP per person is a better guide to living standards than headline GDP. Households are also saving less, which suggests many are absorbing higher costs by dipping into their savings. If GDP per person falls again in the June quarter, Australia would enter a per capita recession. That would not mean the whole economy is in recession, but it would mean the average Australian is going backwards. The June quarter will therefore be important to watch. It will show more clearly how households are responding to higher fuel prices, higher interest rates and weaker confidence. What does it mean for interest rates? The Reserve Bank board meets on June 15–16. Growth has slowed, GDP per person has fallen, and discretionary spending is weak. These are all signs that higher interest rates are already weighing on households and the broader economy. At the same time, the Reserve Bank cannot ignore inflation risks. Fuel prices rose sharply late in the quarter, construction prices are still rising, and the end of energy rebates has lifted household out-of-pocket costs. The Reserve Bank’s own forecasts suggest headline inflation is likely to peak in the June quarter. Just after the Reserve Bank published those forecasts, Treasury released its own as part of the May federal budget. Treasury expected inflation to peak at around 5%. If the Middle East conflict ends soon, it expects inflation to fall back within the Reserve Bank’s 2–3% target band by this time next year. But if the war goes on longer, it could climb much higher. This week’s wage rise for low-paid workers, as well as the latest inflation data and unemployment figures, will all be part of the board’s discussion. That is why each interest rate decision is so difficult. As Reserve Bank board member Ian Harper acknowledged this week, it’s always harder to sleep the night before the board makes a rate decision: Maybe not a sleepless night […but] you have to make a decision which, as you well know, affects every single person in this economy. And that bears on you in the middle of the night, usually about 2.30 in my case. On balance, this GDP data strengthens the case for the Reserve Bank to hold rates in June and wait for more evidence, before deciding whether another increase is needed in August. The Reserve Bank’s challenge is now even harder: bringing inflation back under control, without pushing an already slowing economy into a deeper downturn. Interest rates look set to hold, after inflation and fuel costs fell in April. But it’s unlikely to last Stella Huangfu does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

Nicola Prentis is raising her two kids abroad and trying to look after her mother back home. Provided by Nicola Prentis Nicola Prentis is a single mom raising her kids in Spain. These days, she juggles her mom's care back home with raising her own kids, often feeling pulled in two directions. She worries about the example she's setting for her children. When my cellphone rings as I'm wrangling my boisterous 8- and 11-year-olds into bed in Spain, I answer immediately. I know I'm adding another hour to the bedtime routine. It's my mother in the UK, calling for the third time that day. I don't know whether it's an actual emergency or the kind where she can't remember how the TV channels work. When I moved away from home at 24, my mother was in my hometown raising my teenage brother. It never occurred to me that if I ever had children, my mother would get old enough to need taking care of at the same time. I never thought it would be me Back then, like most 24-year-olds, I couldn't have told you what I'd be doing in a year's time, let alone decades. As it turned out, I would live in various countries, ticking them off a constantly evolving wish list, finally settling in Spain in 2012 and having children of my own three years later. Even then, the idea that my mother might not be independent forever never crossed my mind. Are you paying for your own or your loved one's long-term care? To share your story with a reporter, please fill out this quick form. Not even in the last few years, as a trickle of my expat friends started moving back home to look after aging parents, did I think care responsibilities would fall to me. After all, I have two siblings in England who live closer, and I can't move my children as I co-parent with their father, who lives in Spain. Now that my mother is 80 and has a variety of significant health conditions, the buck often stops with me. My sister, who lives in the same town, has her own health issues, and my brother and mother don't have the kind of relationship where he can help her in any practical sense. My remote caring duties are 24/7 Some days I feel like a 24/7 remote-carer-stroke-personal-assistant. Our conversations increasingly sound as if I am the worst customer service worker ever, and my working day is constantly interrupted as I can no longer have my phone on silent in case it's my mother or a caretaker. I accompany her to doctor's appointments virtually via WhatsApp, coordinate with home caretakers, and book taxis using a subscription service that lets me call local phone numbers. Last June, I flew home for the weekend to accompany my mother to a concert my sister had bought tickets for and planned to take her to, but she was undergoing treatment and couldn't. I field multiple calls a day from my mother when she can't remember how to use the microwave or has forgotten her bank PIN. Sometimes, it means missing half my kids' football games or losing the chance to help them with homework. Once, while my date drove me home at 11 p.m., I had to explain transactions on my mother's bank statement over the phone. At least I managed to sound patient in front of him — it was the third time I'd explained the same thing that weekend. On a practical level, there are things I wish I had realized sooner. My sister and I had at least organized a Power of Attorney, but it's not as simple to use it from abroad as I expected. I had to physically return to the UK in March to access the bank accounts and set up online banking. The thing that's hardest for me as Gen X(pat) sandwich My mother is fairly unaware of all the logistics involved, though she is grateful for the help. Sometimes, when we're both having a good day, we can just enjoy a nice conversation without me feeling guilty or irritated. One of the hardest things about being part of the sandwich generation — a situation that could go on for years — is knowing my kids are learning how to care for me one day by watching how I care for my mother. Every impatient tone in my voice is teaching them something, and my youngest once said after overhearing me on the phone, "Don't be mean to Nanna." I hope I learn how to manage it better because, in truth, it's only going to get harder. Read the original article on Business Insider

arXiv:2606.02753v1 Announce Type: new Abstract: Video world models are a foundational generative technology for embodied AI and the Metaverse, yet existing approaches are inherently limited to a single agent observing from a single perspective. Extending these models to multi-agent settings introduces two critical challenges: data scarcity (coordinated multi-view recordings are prohibitively expensive to collect for general open-domain scenarios) and world state alignment (independently generated video streams cannot ensure that shared physical environments and events evolve consistently across views). To address these challenges, we propose MetaWorld, a novel framework that scales multi-agent video world models to open-domain environments directly from single-view videos. First, we introduce Monocular World-State Unrolling (MWSU) to explicitly decompose monocular footage into the camera operator's ego-motion and the visible subject's spatial trajectory. This camera-trajectory decomposition naturally extracts synchronized multi-agent motion data within a shared 3D space, completely bypassing the need for multi-camera setups. Second, for precise visual control, we develop the Subject-Aware World Generator to enable appearance-driven simulation conditioned on per-agent identity images. Finally, to ensure both views are grounded in the identical physical reality, we propose World-State Alignment, a per-frame inter-branch cross-attention mechanism inserted at every transformer layer of the video DiT. By jointly synchronizing the denoising process, WSA enforces both static geometric consistency and dynamic motion consistency, encouraging that the shared 3D environment and physical events remain well-aligned across both egocentric views. Extensive experiments demonstrate that MetaWorld achieves superior cross-view consistency and identity fidelity, establishing a highly scalable, physics-driven paradigm for multi-agent video world modeling.

arXiv:2606.02747v1 Announce Type: new Abstract: Planning records define restrictions over geographic areas, but their source documents often provide only indirect spatial evidence rather than machine-readable boundaries. We introduce Plan2Map, a 208-case multimodal benchmark for document-grounded geospatial boundary reconstruction from UK planning records. Given only a source planning document, systems must reconstruct a valid geospatial boundary from notice text, schedules, map plates, map labels, and boundary annotations; the reference GeoJSON is held out for scoring. We propose GeoPlanAgent, a document-grounded, geospatial-tool-in-the-loop system that decomposes the task into evidence extraction, localisation, map registration, boundary segmentation, projection, and verification. On Plan2Map, GeoPlanAgent achieves 0.736 mean IoU and 0.904 median IoU, with 67.8\% of predictions at or above 0.8 IoU, substantially outperforming direct VLM-to-GeoJSON baselines. Diagnostic analysis shows that direct VLM prediction remains unreliable, while remaining errors are concentrated in localisation and map registration, and supervised boundary segmentation substantially improves pixel-level mask quality. Plan2Map provides a concrete testbed for multimodal geospatial reconstruction from public planning records. Project page: https://odeb1.github.io/Plan2Map_Project_Page/.

arXiv:2606.02597v1 Announce Type: new Abstract: The development of brain-computer interfaces (BCIs) based on electroencephalograms (EEGs) has advanced significantly mainly to machine learning. Although the majority of earlier research has been on increasing classification accuracy, relatively little focus has been placed on security and robustness. According to recent research, EEG-based BCIs are susceptible to adversarial attacks, which can cause misdiagnosis due to minute, well-crafted disturbances. Evaluating model robustness against such perturbations is therefore critical for ensuring reliable deployment. In this study, we propose a lightweight custom Convolutional Neural Network (CNN) architecture to investigate adversarial robustness in EEG-based BCIs. The suggested method is assessed using two EEG datasets and contrasted with three novel CNN models tailored to EEG, namely EEGNet, DeepConvNet, and SleepEEGNet, under gradient-based adversarial attack scenarios. According to experimental findings, the suggested model continuously performs better in classification under adversarial perturbations compared to baseline models, indicating improved robustness. These findings highlight the potential of lightweight architectures for enhancing the reliability of EEG-based BCI systems under adversarial conditions.

arXiv:2606.02605v1 Announce Type: new Abstract: Coronary artery stenosis is a common cardiovascular disease, with severe, untreated cases posing significant risks of heart attack. Although coronary (X-ray) angiograms remain the standard for stenosis diagnosis, they are invasive, time- and resource-intensive, and therefore only performed on patients with a high probability of disease based on symptoms and prior clinical tests. However, a subset of patients, especially those without symptoms, may remain undiagnosed. Detecting indications of stenosis from ECGs, which are fast, cheap, non-invasive, and thus routinely acquired even in asymptomatic patients, would support early diagnosis. However, as no reliable stenosis-specific signal has been identified in ECGs, they can not currently be used for stenosis risk stratification. To address this, we introduce StenCE, a pretraining framework, allowing stratification of patients based on features derived directly from ECGs. Evaluations across varying stenosis severity thresholds and additional ECG disease classification tasks demonstrate consistent performance improvements across different ECG encoders, outperforming previous work. The obtained models successfully detect signals for stenosis diagnosis in ECGs and are the first to achieve high performance in severe stenosis classification. The source code is available at https://github.com/NikolaCenic/ecg-stenosis-cls.

arXiv:2606.02741v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in sustainability-related decision support, reporting, and public communication, yet little systematic evidence exists on the environmental attitudes embedded in their outputs. This paper develops a benchmark for evaluating environmental cognition, affect, and behavioural recommendations in LLMs and applies it to 31 widely used proprietary and open-weight models. Drawing on questions from established environmental awareness surveys and additional sustainability-related behavioural measures, we compare LLM responses 1) among models and 2) between models and human survey benchmarks from Germany. We assess their robustness across prompting conditions. We find that many LLMs align more closely with environmentally progressive attitudes than the average survey respondent, exhibiting higher levels of environmental affect and cognition and recommending behaviours associated with substantial potential CO2 reductions. At the same time, we observe no systematic relationship between sustainability-oriented responses and model origin, size, or release context. However, models exhibit contextual sensitivity, controlled by persona-based prompting and show sycophantic shifts mirroring user-specified ideological positions, which raises concerns about steerability and normative reliability in real-world deployments. Our findings provide a reusable evaluation framework for assessing sustainability-related value alignment in LLMs and highlight the importance of governance, transparency, and critical oversight as AI systems become increasingly embedded in sustainability transformations and public decision-making.