Every emotional moment from the Gilgo Beach killer's sentencing: Rex Heuermann's shocking first words... and the chilling exchange that silenced the room Don Trump Jr. says Ted Cruz is'lying through his teeth' as GOP infighting over Iran deal continues to spiral LIZ JONES: The cracks in Harry and Meghan's perfect facade have started to show. It's so obvious he's tiring of her tone-deaf approach... and I predict there's serious trouble in store All my friends are suddenly getting divorced. Mid-life wives share taboo sex confessions about why they really leave... including common position that made one hate her husband: JANA HOCKING Trump says'fools who think I haven't been tough enough on Iran' are'jealous or stupid' after signing widely-criticised deal that includes giving Tehran $300billion Taylor Swift's bottomless thirst for attention, her greed and sheer tackiness are now truly unbearable... this latest stunt has shown her true colors: MAUREEN CALLAHAN The Ring star Daveigh Chase's friends searched for her on LA's Skid Row in months before her shock death at 35 Horrific new videos blow Texas woman's mystery death wide open: Her agonizing'final gasp'... unthinkably vile corpse claims... and sick past of man who saw her last'I can still see you': Princess of Wales shares adorable moment with shy little girl at Royal Ascot Brooklyn Beckham is savaged by fans for yet another'classless' swipe at his estranged family as new DoorDash ad is branded a'giant PR mess' Sensational REAL reason Jelly Roll is divorcing Bunnie XO: Insiders reveal'preacher's wife' bombshell that's the talk of Nashville... truth about legendary rocker cuckolding rumor... and G-string mishap Watch horrifying drone video that follows woman's plunge to death after bungee team threw her from bridge without rope Kylie Jenner and Timothee Chalamet put on VERY affectionate display during NYC bike ride... as it's revealed how the relationship has'changed' the actor Luxury fashion tycoon beloved by the stars hangs her head in shame as she's indicted for allegedly exploiting her workers and stealing $50k from their wages NBA star's fiancee breaks her silence after friend, 26, mysteriously dropped dead at her luxury bachelorette party in St Barts Tragedy as 8-year-old dies during World Cup watch party with cops blaming'accidental drowning' Instead, I lost a stone and dropped a dress size in one MONTH with a meal plan that's not even a diet. It's packed with carbs and so simple - anyone can do it in time for summer Gen Z are scared of ringing the DOORBELL: One in three youngsters now text or call when they arrive at someone's door because they think it's less awkward It's something most people do without thinking twice about it. But a new survey has revealed how ringing the doorbell is leaving many Gen Z petrified.

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Simulating collective decision-making involves more than aggregating individual behaviors; it emerges from dynamic interactions among individuals. While large language models (LLMs) offer strong potential for social simulation, achieving quantitative alignment with real-world data remains a key challenge. To bridge this gap, we propose the Mean-Field LLM (MF-LLM) framework, the first to incorporate mean field theory into LLM-based social simulation. MF-LLM models bidirectional interactions between individuals and the population through an iterative process, generating population signals to guide individual decisions, which in turn update the signals. This interplay produces coherent trajectories of collective behavior. To improve alignment with real-world data, we introduce IB-Tune, a novel fine-tuning method inspired by the Information Bottleneck principle, which retains population signals most predictive of future actions while filtering redundant history. Evaluated on a real-world social dataset, MF-LLM reduces KL divergence to human population distributions by 47% compared to nonmean-field baselines, enabling accurate trend forecasting and effective intervention planning. Generalizing across 7 domains and 4 LLM backbones, MF-LLM provides a scalable, high-fidelity foundation for social simulation.

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We introduce IntrinsiX, a novel method that generates high-quality intrinsic images from text description. In contrast to existing text-to-image models whose outputs contain baked-in scene lighting, our approach predicts physically-based rendering (PBR) maps. This enables the generated outputs to be used for content creation scenarios in core graphics applications that facilitate re-lighting, editing, and texture generation tasks. In order to train our generator, we exploit strong image priors, and pre-train separate models for each PBR material component (albedo, roughness, metallic, normals). We then align these models with a new cross-intrinsic attention formulation that concatenates key and value features in a consistent fashion.

Why do AI models struggle with online hate speech detection? Hate speech that once circulated in person now travels farther and faster via anonymous online accounts behind a screen. As the United Nations marks the International Day for Countering Hate Speech on June 18, UN Secretary-General Antonio Guterres has warned that social platforms are amplifying the threat. With artificial intelligence (AI) increasingly tasked with detecting and removing hate speech online, Al Jazeera looks at where these systems fall short compared with human judgement. How is hate speech defined?

'There's no evidence that jobs go away, but there is a lot of evidence that as soon as you can dismantle full-time employment, companies will do that.' 'There's no evidence that jobs go away, but there is a lot of evidence that as soon as you can dismantle full-time employment, companies will do that.' Gig workers are endlessly exploited. As companies integrate AI and hire fewer employees, a shift toward a'gig economy' will commence The Guardian's journalism is independent. We will earn a commission if you buy something through an affiliate link.

Recent advances in video diffusion models have driven rapid progress in video editing techniques. However, video object removal, a critical subtask of video editing, remains challenging due to issues such as hallucinated objects and visual artifacts. Furthermore, existing methods often rely on computationally expensive sampling procedures and classifier-free guidance (CFG), resulting in slow inference.

The scale and quality of datasets are crucial for training robust perception models. However, obtaining large-scale annotated data is both costly and time-consuming. Generative models have emerged as a powerful tool for data augmentation by synthesizing samples that adhere to desired distributions. However, current generative approaches often rely on complex post-processing or extensive fine-tuning on massive datasets to achieve satisfactory results, and they remain prone to content-position mismatches and semantic leakage. To overcome these limitations, we introduce ReCon, a novel augmentation framework that enhances the capacity of structure-controllable generative models for object detection.

To quantify this stagnation, we introduce LIVEVQA, the first-of-its-kind dataset featuring 107,143 samples and 12 categories data specifically designed to support research in both seeking and updating with live visual knowledge. Drawing from recent news articles, video platforms, and academic publications in April 2024-May 2025, LIVEVQA enables evaluation of how models handle latest visual information beyond their knowledge boundaries and how current methods help to update them. Our comprehensive benchmarking of 17 state-of-the-art MLLMs reveals significant performance gaps on content beyond knowledge cutoff, and tool-use or agentic visual seeking framework drastically gain an average of 327% improvement. Furthermore, we explore parameter-efficient fine-tuning (PEFT) methods to update MLLMs with new visual knowledge. We dive deeply to the critical balance between adapter capacity and model capability when updating MLLMs with new visual knowledge. All the experimental dataset and source code are publicly available at: https://livevqa.github.io.