Trump stuns 60 Minutes' Norah O'Donnell as he breaks terrifying news about China and Russia nukes Justin Baldoni's bombshell $400M case against Blake Lively and Ryan Reynolds is'formally ended by a judge' Thomas Massie remarries 16 months after losing wife of 31 years... as Trump ally launches sick attack Sex aids and poppers... the sordid discoveries made by royal aides after party Andrew threw for Epstein and Ghislaine Maxwell - and the truth about those massages: ROBERT JOBSON I learned the horrifying risks of'miracle' ADHD drugs and stopped taking them... but it was too late George Clooney gives rare insight into life with wife Amal and their twins - as he details his relationship with his kids, lauds his'beautiful' family and brands himself'very lucky' Astonishing new evidence of Atlantis reveals advanced civilization preserved by Ancient Egypt's priests... before disaster hit Three Americans among seven killed when avalanche obliterates Himalayan climbers' base camp Trump's secret plan to deploy US troops to Mexico revealed with drone strikes in the works Jayden Daniels' X-ray results revealed in huge moment for the Commanders' season after QB's horror elbow injury Top Democrat lawmaker becomes international fugitive after she was freed on bail'for stealing thousands from vulnerable man, 83' I won't ever forget what I saw at Andy Cohen's party. He may admit he's hooking up with guys on every dating app but this is the truth about men like him: KENNEDY Ex-CIA spy shares an easy way to tell if someone is lying... and the tactic he uses to strengthen his love life Shohei Ohtani's wife makes rare appearance to celebrate Dodgers star's World Series win Deborra-Lee Furness' bold move after split from Hugh Jackman - and why the actor is not happy about it So many single men are taking this new drug cocktail before dates. The results in the bedroom are startling... as I discovered during one marathon session: JANA HOCKING Devastating impact of Mamdani's election will be FAR WORSE than first thought: Exclusive poll finds America's greatest city facing'historic' population wipeout Moment'knifeman who hurt 11 people in Huntingdon train rampage storms barber shop moments after stabbing 14-year-old boy' Meghan is mocked for her new Christmas recipe... boiled water! The most common passwords are revealed - with '123456' topping the list yet again It's something we're all regularly warned against, but it seems that many of us are still using passwords that are incredibly easy to guess. Experts from Peec AI have analysed 100 million passwords from data breaches over the last six years to reveal the most common words, phrases, and values.

Devastating impact of Mamdani's election will be FAR WORSE than first thought: Exclusive poll finds America's greatest city facing'historic' population wipeout Trump reveals devastating plan for NYC if'communist' Mamdani gets elected while rejecting comparisons: 'I'm a much better looking person' I won't ever forget what I saw at Andy Cohen's party. He may admit he's hooking up with guys on every dating app but this is the truth about men like him: KENNEDY So many single men are taking this new drug cocktail before dates. The results in the bedroom are startling... as I discovered during one marathon session: JANA HOCKING Putin unveils terrifying new nuclear submarine built to carry'doomsday' weapon capable of unleashing radioactive tidal wave'Trump has lost it with Steve Bannon': Insiders claim third term'plan' has sparked furious MAGA rift... and name group of'irritants' wreaking havoc How Jennifer Aniston found her happy ever after with Hollywood hypnotist and'love guru' Jim Curtis after string of failed romances, 'love triangle' scandal and IVF struggles Meghan Markle'wants to become a billionaire', says royal expert, after Duchess was seen cosying up to brains behind Kardashian brands amid speculation she'could launch a beauty empire' William and Kate throw party for builders and staff who helped them leave'cursed' cottage early Deborra-Lee Furness' bold move after split from Hugh Jackman - and why the actor is not happy about it Trump responds after Dilbert creator makes last-ditch plea to save his life as he'declines rapidly' from cancer Kimberly Guilfoyle's steamy Greek debut sparks envious whispers of a'storm' coming for Trump We've never been so sure of an imminent financial crash: Industry leaders across ALL sectors come together to say these signs of US economic meltdown are undeniable Ladies, it could be time to get the straighteners out - as a new study reveals women with smooth, shiny hair are judged as being younger, healthier and more attractive. Researchers have discovered that the way you style your hair can have a significant impact on how you're perceived by strangers. Even subtle variations in thickness, density and style can make a difference, they found.

Things to Do in L.A. Tap to enable a layout that focuses on the article. KitKat was friendly with many customers of Randa's Market in San Francisco's Mission District. This is read by an automated voice. Please report any issues or inconsistencies here . San Francisco has been mourning the death of KitKat, a beloved corner-store cat who died after being struck by a Waymo robotaxi last week.

Devastating impact of Mamdani's election will be FAR WORSE than first thought: Exclusive poll finds America's greatest city facing'historic' population wipeout Trump reveals devastating plan for NYC if'communist' Mamdani gets elected while rejecting comparisons: 'I'm a much better looking person' I won't ever forget what I saw at Andy Cohen's party. He may admit he's hooking up with guys on every dating app but this is the truth about men like him: KENNEDY So many single men are taking this new drug cocktail before dates. The results in the bedroom are startling... as I discovered during one marathon session: JANA HOCKING Putin unveils terrifying new nuclear submarine built to carry'doomsday' weapon capable of unleashing radioactive tidal wave'Trump has lost it with Steve Bannon': Insiders claim third term'plan' has sparked furious MAGA rift... and name group of'irritants' wreaking havoc How Jennifer Aniston found her happy ever after with Hollywood hypnotist and'love guru' Jim Curtis after string of failed romances, 'love triangle' scandal and IVF struggles Meghan Markle'wants to become a billionaire', says royal expert, after Duchess was seen cosying up to brains behind Kardashian brands amid speculation she'could launch a beauty empire' William and Kate throw party for builders and staff who helped them leave'cursed' cottage early Deborra-Lee Furness' bold move after split from Hugh Jackman - and why the actor is not happy about it Trump responds after Dilbert creator makes last-ditch plea to save his life as he'declines rapidly' from cancer Kimberly Guilfoyle's steamy Greek debut sparks envious whispers of a'storm' coming for Trump We've never been so sure of an imminent financial crash: Industry leaders across ALL sectors come together to say these signs of US economic meltdown are undeniable Now THAT'S what you call a cold one! A rare bottle of Arctic beer will be opened to revive the ancient ale, 150 years after it was bottled. Douglas Gunn Sharp, founder of Edinburgh's Innis & Gunn brewery, will open his precious bottle of Allsopp's Arctic Ale - after splashing out £3,000 for it.

The Vanguard live up to the Oakley name with a rock-solid fit and lenses built for sport. The Vanguard live up to the Oakley name with a rock-solid fit and lenses built for sport. The Guardian's journalism is independent. We will earn a commission if you buy something through an affiliate link. T he Oakley Meta Vanguard are new displayless AI glasses designed for running, cycling and action sports with deep Garmin and Strava integration, which may make them the first smart glasses for sport that actually work. The Guardian's journalism is independent.

Language models (LMs) are increasingly being deployed to perform autonomous data analyses. However, their data awareness -- the ability to recognize, reason over, and appropriately handle data artifacts such as missing values, outliers, and logical inconsistencies -- remains underexplored. These artifacts are especially common in real-world tabular data and, if mishandled, can significantly compromise the validity of analytical conclusions. To address this gap, we present RADAR, a benchmark for systematically evaluating data-aware reasoning on tabular data. We develop a framework to simulate data artifacts via programmatic perturbations to enable targeted evaluation of model behavior. RADAR comprises 2980 table query pairs, grounded in real-world data spanning 9 domains and 5 data artifact types. In addition to evaluating artifact handling, RADAR systematically varies table size to study how reasoning performance holds when increasing table size. Our evaluation reveals that, despite decent performance on tables without data artifacts, frontier models degrade significantly when data artifacts are introduced, exposing critical gaps in their capacity for robust, data-aware analysis. Designed to be flexible and extensible, RADAR supports diverse perturbation types and controllable table sizes, offering a valuable resource for advancing tabular reasoning.

Understanding the structural and cognitive underpinnings of musical compositions remains a key challenge in music theory and computational musicology. While traditional methods focus on harmony and rhythm, cognitive models such as the Implication-Realization (I-R) model and Temporal Gestalt theory offer insight into how listeners perceive and anticipate musical structure. This study presents a graph-based computational approach that operationalizes these models by segmenting melodies into perceptual units and annotating them with I-R patterns. These segments are compared using Dynamic Time Warping and organized into k-nearest neighbors graphs to model intra- and inter-segment relationships. Each segment is represented as a node in the graph, and nodes are further labeled with melodic expectancy values derived from Schellenberg's two-factor I-R model-quantifying pitch proximity and pitch reversal at the segment level. This labeling enables the graphs to encode both structural and cognitive information, reflecting how listeners experience musical tension and resolution. To evaluate the expressiveness of these graphs, we apply the Weisfeiler-Lehman graph kernel to measure similarity between and within compositions. Results reveal statistically significant distinctions between intra- and inter-graph structures. Segment-level analysis via multidimensional scaling confirms that structural similarity at the graph level reflects perceptual similarity at the segment level. Graph2vec embeddings and clustering demonstrate that these representations capture stylistic and structural features that extend beyond composer identity. These findings highlight the potential of graph-based methods as a structured, cognitively informed framework for computational music analysis, enabling a more nuanced understanding of musical structure and style through the lens of listener perception.

We present a practical pipeline for fine-tuning open-source video diffusion transformers to synthesize cinematic scenes for television and film production from small datasets. The proposed two-stage process decouples visual style learning from motion generation. In the first stage, Low-Rank Adaptation (LoRA) modules are integrated into the cross-attention layers of the Wan2.1 I2V-14B model to adapt its visual representations using a compact dataset of short clips from Ay Yapim's historical television film El Turco. This enables efficient domain transfer within hours on a single GPU. In the second stage, the fine-tuned model produces stylistically consistent keyframes that preserve costume, lighting, and color grading, which are then temporally expanded into coherent 720p sequences through the model's video decoder. We further apply lightweight parallelization and sequence partitioning strategies to accelerate inference without quality degradation. Quantitative and qualitative evaluations using FVD, CLIP-SIM, and LPIPS metrics, supported by a small expert user study, demonstrate measurable improvements in cinematic fidelity and temporal stability over the base model. The complete training and inference pipeline is released to support reproducibility and adaptation across cinematic domains.

Evaluating the abilities of large language models (LLMs) for tasks that require long-term memory and thus long-context reasoning, for example in conversational settings, is hampered by the existing benchmarks, which often lack narrative coherence, cover narrow domains, and only test simple recall-oriented tasks. This paper introduces a comprehensive solution to these challenges. First, we present a novel framework for automatically generating long (up to 10M tokens), coherent, and topically diverse conversations, accompanied by probing questions targeting a wide range of memory abilities. From this, we construct BEAM, a new benchmark comprising 100 conversations and 2,000 validated questions. Second, to enhance model performance, we propose LIGHT-a framework inspired by human cognition that equips LLMs with three complementary memory systems: a long-term episodic memory, a short-term working memory, and a scratchpad for accumulating salient facts. Our experiments on BEAM reveal that even LLMs with 1M token context windows (with and without retrieval-augmentation) struggle as dialogues lengthen. In contrast, LIGHT consistently improves performance across various models, achieving an average improvement of 3.5%-12.69% over the strongest baselines, depending on the backbone LLM. An ablation study further confirms the contribution of each memory component.

The connection between texts is referred to as intertextuality in literary theory, which served as an important theoretical basis in many digital humanities studies. Over the past decade, advancements in natural language processing have ushered intertextuality studies into the quantitative age. Large-scale intertextuality research based on cutting-edge methods has continuously emerged. This paper provides a roadmap for quantitative intertextuality studies, summarizing their data, methods, and applications. Drawing on data from multiple languages and topics, this survey reviews methods from statistics to deep learning. It also summarizes their applications in humanities and social sciences research and the associated platform tools. Driven by advances in computer technology, more precise, diverse, and large-scale intertext studies can be anticipated. Intertextuality holds promise for broader application in interdisciplinary research bridging AI and the humanities.