Outside OpenAI's headquarters, a handful of people gathered on Monday holding pieces of colorful chalk. They got down on their knees and started writing messages on the sidewalk. Please no legal mass surveillance. At issue was a business deal that the company recently signed with the Department of Defense, following the Pentagon's sudden turn against Anthropic . OpenAI will now supply its technology to the military for use in classified settings, the sorts that may involve wartime decisions and intelligence-gathering--an agreement, many legal experts told me, that could give the government wide-ranging powers.

We used the CRC-100K dataset to construct the CRC-MIL dataset with different positive instance ratios.

Our responses are below with the reviewers' comments in italics. "The paper needs more details on the experiments..." "Give a clearer motivation for how embeddings were constrained in 4.1...the authors do not show why this We make no claim that this particular solution subset is optimal (or even at all good). "Fig 2 (a,b), the red lines do not match when "Fig 3, results for upper triangular ...have better performance than diagonal ones...[Intuition?]...What are red's craving in answering the "meta question" of why embeddings work. To our knowledge we are the first to do this. "Previous methodologies...implicity address [non-identifiability] already, as they place implicit constraints (like But U and V are non-square so cannot be symmetric.

Kyiv, Ukraine – Heavy thuds that resemble fast hip-hop beats fill the night air when MIM-104 Patriots, air defence systems made in the United States, get to work. Each Patriot surface-to-air launcher can shoot up to 32 missiles within seconds – and hit Russian ballistic missiles closing in on their targets. The missiles fly at supersonic speeds, and the collision triggers a bright, split-second blast followed by a thunderous shock-wave. "That's the kind of explosion that makes me feel safe," Ihor Lysenko, a 17-year-old in the capital Kyiv told Al Jazeera. He believes that the "technology is pretty reliable".

Conversational agents have made significant progress since ELIZA, expanding their role across various domains, including healthcare, education, and customer service. As these agents become increasingly integrated into daily human interactions, the need for emotional intelligence, particularly empathetic listening, becomes increasingly essential. In this study, we explore how Large Language Models (LLMs) respond when tasked with generating emotionally rich interactions. Starting from a small dataset manually crafted by an expert to reflect empathic behavior, we extended the conversations using two LLMs: ChatGPT and Gemini. We analyzed the emotional progression of the dialogues using both sentiment analysis (via VADER) and expert assessments. While the generated conversations often mirrored the intended emotional structure, human evaluation revealed important differences in the perceived empathy and coherence of the responses. These findings suggest that emotion modeling in dialogues requires not only structural alignment in the expressed emotions but also qualitative depth, highlighting the importance of combining automated and humancentered methods in the development of emotionally competent agents.

Islamabad, Pakistan – On Wednesday evening, as Pakistan grappled with the aftermath of a wave of missile strikes from India that hit at least six cities, killing 31 people, the country's military spokesperson took to a microphone with a chilling warning. "When Pakistan strikes India, it will come at a time and place of its own choosing," Lieutenant General Ahmed Sharif Chaudhry said in a media briefing. "The whole world will come to know, and its reverberation will be heard everywhere." Two days later, India and Pakistan have moved even closer to the brink of war. On Thursday, May 8, Pakistan accused India of flooding its airspace with kamikaze drones that were brought down over major cities, including Lahore and Karachi.

Ensuring adherence to traffic sign regulations is essential for both human and autonomous vehicle navigation. While current online mapping solutions often prioritize the construction of the geometric and connectivity layers of HD maps, overlooking the construction of the traffic regulation layer within HD maps. Addressing this gap, we introduce MapDR, a novel dataset designed for the extraction of Driving Rules from traffic signs and their association with vectorized, locally perceived HD Maps. MapDR features over $10,000$ annotated video clips that capture the intricate correlation between traffic sign regulations and lanes. Built upon this benchmark and the newly defined task of integrating traffic regulations into online HD maps, we provide modular and end-to-end solutions: VLE-MEE and RuleVLM, offering a strong baseline for advancing autonomous driving technology. It fills a critical gap in the integration of traffic sign rules, contributing to the development of reliable autonomous driving systems.

His hands-off approach to the production of his famous balloon dogs and stainless steel rabbits has been criticised in the past but Jeff Koons, the world's most expensive artist, has drawn a red-line: "I wouldn't – for my own base work – be looking at AI to be developing my work." The potential and the risks of artificial intelligence is perhaps the hottest topic in the artistic world, with deep-learning models now able to replicate styles and produce unique compositions on request. It would appear to be a heaven-sent development for Koons, who was speaking to the Guardian at the launch of Reflections, a joint exhibition of his works alongside those of Pablo Picasso at the Alhambra in Granada. Koons's reliance on teams of craftspeople and cutting-edge technology in the making of his pieces prompted the Collector magazine last year to ask: "Is Jeff Koons an actual artist?" Exploiting technological advances is what he does.