Bed-bound Lindsey Vonn reveals pain is'hard to manage' as she speaks out for the first time after FIFTH surgery on her broken leg'Fergie might end up having to tell her story to the police': 'Toxic' Sarah Ferguson is'broke and in a bad way' after Andrew's arrest...and looking to UAE for cash because'everyone is out to get her' The tide of sleaze rolling over Beatrice, Eugenie and Fergie is going to capsize them all. Moment Kate and William revealed their'true feelings' towards Andrew and Fergie: Princess'ignoring' Sarah and Prince'secretly scolding' his uncle... how Duchess of Kent's funeral said it all Kurt Cobain's uncle insists Nirvana legend was murdered and calls on cops to investigate clues that haunt him Kristi Noem's secret escape plan to ditch DHS revealed amid ICE raid fallout and'culture of fear' rumors Winter Olympics chiefs reach verdict on Jutta Leerdam's '$1m underwear-flashing gesture' after Jake Paul's fiancée faced covert marketing claims Country singer Conner Smith's charges DROPPED after he hit and killed a woman, 77, with his truck I ditched weight-loss shots for the new Wegovy pill and am astonished by the difference. The pounds are falling off, I have no side effects and it's cheaper The subtle early warning sign that revealed Eric Dane's illness - as Grey's Anatomy star dies of motor neurone disease Johnny Depp let Eric Dane live'rent-free in one of his LA homes' as he tried to ease Grey's Anatomy star's financial worries in the months before his death from ALS aged 53 Uproar as NYC's'communist' mayor announces crippling tax for ALL homeowners after promising to only go after billionaires Wall Street panics as America's growth stalls while everyday prices refuse to fall I stumbled across my wife's Pornhub search history and it's broken me. She told me it's'just a fantasy lots of women have' but now I fear I'll never be enough Non-binary activist wins compensation after taking year-and-a-half off work with stress because hair salon's online booking form only offered male or female cuts Courtney Love caught on camera fleeing shocking car collision... days after bombshell Kurt Cobain'homicide investigation' Trump-bashing Winter Olympics star Hunter Hess whines about'hardest weeks of his life' after being called a'real loser' by the president In a viral post on X, user @ShishirShelke1 shared their strange discovery about the clock app icon. Normally, the icon on the home screen shows the second hand smoothly gliding around the clock face.

Accurate and efficient seismic response prediction is essential for the design of resilient structures. While the Finite Element Method (FEM) remains the standard for nonlinear seismic analysis, its high computational demands limit its scalability and real time applicability. Recent developments in deep learning, particularly Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Long Short Term Memory (LSTM) models, have shown promise in reducing the computational cost of nonlinear seismic analysis of structures. However, these data driven models often struggle to generalize and capture the underlying physics, leading to reduced reliability. We propose a novel Physics Informed U Net LSTM framework that integrates physical laws with deep learning to enhance both accuracy and efficiency. By embedding domain specific constraints into the learning process, the proposed model achieves improved predictive performance over conventional Machine Learning architectures. This hybrid approach bridges the gap between purely data driven methods and physics based modeling, offering a robust and computationally efficient alternative for seismic response prediction of structures.

We retrieve top 10 passages and use them as input to mGEN. Gettysburg College, where he was a member of the Lambda Chi Alpha fraternity. We further subsample 50% of the synthetically generated questions. For our multilingual retriever, we split each article into 100-token chunks (Karpukhin et al., 2020), The original passage text file is 29GB, and the total index size is around 129 GB. Both two datasets are under the MIT licence.

The dynamic structural load identification capabilities of the gated recurrent unit, long short-term memory, and convolutional neural networks are examined herein. The examination is on realistic small dataset training conditions and on a comparative view to the physics-based residual Kalman filter (RKF). The dynamic load identification suffers from the uncertainty related to obtaining poor predictions when in civil engineering applications only a low number of tests are performed or are available, or when the structural model is unidentifiable. In considering the methods, first, a simulated structure is investigated under a shaker excitation at the top floor. Second, a building in California is investigated under seismic base excitation, which results in loading for all degrees of freedom. Finally, the International Association for Structural Control-American Society of Civil Engineers (IASC-ASCE) structural health monitoring benchmark problem is examined for impact and instant loading conditions. Importantly, the methods are shown to outperform each other on different loading scenarios, while the RKF is shown to outperform the networks in physically parametrized identifiable cases.

Self-correction of large language models (LLMs) emerges as a critical component for enhancing their reasoning performance. Although various self-correction methods have been proposed, a comprehensive evaluation of these methods remains largely unexplored, and the question of whether LLMs can truly correct themselves is a matter of significant interest and concern. In this study, we introduce CorrectBench, a benchmark developed to evaluate the effectiveness of self-correction strategies, including intrinsic, external, and fine-tuned approaches, across three tasks: commonsense reasoning, mathematical reasoning, and code generation. Our findings reveal that: 1) Self-correction methods can improve accuracy, especially for complex reasoning tasks; 2) Mixing different self-correction strategies yields further improvements, though it reduces efficiency; 3) Reasoning LLMs (e.g., DeepSeek-R1) have limited optimization under additional self-correction methods and have high time costs. Interestingly, a comparatively simple chain-of-thought (CoT) baseline demonstrates competitive accuracy and efficiency. These results underscore the potential of self-correction to enhance LLM's reasoning performance while highlighting the ongoing challenge of improving their efficiency. Consequently, we advocate for further research focused on optimizing the balance between reasoning capabilities and operational efficiency. Project Page: https://correctbench.github.io/

Hamas executes'collaborators' in Gaza as it clings to power amid fears Trump's peace deal is already at risk Internet star who demanded free seats for fat fliers vanished without trace... now the Daily Mail has learned the heartbreaking reason why Donald Trump tells crowds there are world leaders he'doesn't like at ALL' as he teases who they are How Diane Keaton's closest friend helped her to achieve her'lifelong ambition' just months before she died - and the poignant legacy it leaves Kate and Wills' fresh start at their'forever home': Why they have fast-tracked their move to house they will never leave - even when he becomes King'It's Meghan Markle 3.0': Why the duchess has set tongues wagging that she's plotting another Sussex relaunch'as she holds cosy meeting with new editor of US Vogue' Trump's ominous warning to Macron at Egypt summit: 'You will see what is about to happen' Neil Diamond, 84, sang Sweet Caroline and worked with Cher as well as Barbra Streisand... see him now Insiders reveal how reluctant Katy Perry finally gave in to'persistent' Justin Trudeau... as sexy yacht photos get spicy response from his ex-wife Awkward moment Donald Trump asks Giorgia Meloni'You won't be offended if I say you're beautiful, right? Horrors endured by Israel's last 20 hostages: Chained, tortured, and starved. Lindsey Halligan removes senior DOJ official after taking over Virginia US attorney's office Gorgeous Bay Area enclave filled with hippies becomes America's ANGRIEST town over plans for huge affordable housing project MLB fans hail'greatest play in baseball HISTORY' after Dodgers thought they hit grand slam in Brewers game Father launches campaign to become sheriff as he faces murder trial for killing teenage daughter's abuser Spot the difference: Apple has rebranded its TV service as part of a'vibrant new identity' - so, can you see what has changed? But Apple TV+ is no more - as Apple has quietly rebranded its streaming service. 'Apple TV+ is now simply Apple TV, with a vibrant new identity,' the tech giant explained in the bottom of a press release on the streaming debut of its film, 'F1 The Movie'.

Dolly Parton's sister asks for prayers for music icon, 79, amid mystery health battle Charlie Kirk leaked text confirms he was livid about'bullying' Jewish donors: 'I'm leaving pro-Israel cause' Mom-of-two hospitalized, her son left suicidal and their dog dead... after a simple mistake turns $500K home into a death trap Trump's mass deportation effort removed staggering amount of migrants from US in first year of term: 'Just the beginning' Man is arrested on terror charges over disturbing Halloween display of fake body bags with town official's titles Selena Gomez's'disgusting' habit on her wedding day exposed by eagle-eyed fans despite star's efforts to hide it Popular actress shocks fans with'unrecognizable' appearance after suffering heartbreaking tragedy She's accused of'murder-for-hire' plot against her famous TV star husband. Now there's a shock twist in the case... and she's forced to stare her demons in the face Bloodcurdling videos shows girl aged 12 subway surfing days before she and friend, 13, died during 3.10am stunt'Kissing Trump's a**': President mocks Canada's obsequious PM as he begs for tariff relief Keith Urban's guitarist Maggie once vowed to'never' date a tour mate... as she's accused of charming Nicole Kidman's ex Hollywood's favorite muscle car primed for return as America's No.1 automaker files secret paperwork Do you have one of these gathering dust in your attic? It was only a couple of decades ago that homes and offices were filled with answering machines and BlackBerry phones. And although they've been obsolete for years, they're now among the retro gadgets that could make you a fortune. Brits are sitting on a hidden goldmine of old forgotten tech devices that may be gathering dust in the attic, according to a new report from Gumtree.

The rapid extension of context windows in large vision-language models has given rise to long-context vision-language models (LCVLMs), which are capable of handling hundreds of images with interleaved text tokens in a single forward pass. In this work, we introduce MMLongBench, the first benchmark covering a diverse set of long-context vision-language tasks, to evaluate LCVLMs effectively and thoroughly. MMLongBench is composed of 13,331 examples spanning five different categories of downstream tasks, such as Visual RAG and Many-Shot ICL. It also provides broad coverage of image types, including various natural and synthetic images. To assess the robustness of the models to different input lengths, all examples are delivered at five standardized input lengths (8K-128K tokens) via a cross-modal tokenization scheme that combines vision patches and text tokens. Through a thorough benchmarking of 46 closed-source and open-source LCVLMs, we provide a comprehensive analysis of the current models' vision-language long-context ability. Our results show that: i) performance on a single task is a weak proxy for overall long-context capability; ii) both closed-source and open-source models face challenges in long-context vision-language tasks, indicating substantial room for future improvement; iii) models with stronger reasoning ability tend to exhibit better long-context performance. By offering wide task coverage, various image types, and rigorous length control, MMLongBench provides the missing foundation for diagnosing and advancing the next generation of LCVLMs.

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Dark'race' element to Ukrainian refugee's death... as horrific way she died revealed by FBI: 'She loved America' Texas announces ban on Sharia Law after Muslim'patrols' tried to ban alcohol and pork Mindy Kaling's rumored baby daddy BJ Novak is'unconnected, distanced and reluctant' in the relationship And a warped web of'lies'. As notorious Trump schmoozer's life falls apart... another explosive twist rocks the case'I'd like to see my Platinum Jubilee. Can you keep me alive for that?' Inside late Queen's cancer battle, as PAUL BURRELL describes her final days, what happened when Harry arrived after her death - and why Meghan was not welcome Why humble Hailee Steinfeld is hardly ever shown on TV watching NFL husband Josh Allen... despite being at most of his games Canada's'dirty doctor': Shocking sex claims engulf top physician as lurid details of her'erotic examinations' are laid bare Houthis strike BACK after Israel bombed building in Qatar as Hamas says six people were killed... and that they blame the US Sweater weather starts here - the cozy, chic pieces from Soft Surroundings you'll actually wear all season Mystery over Burning Man homicide deepens as drivers describe chilling encounter with'woman in red' Epstein bombshell as big shot executor of pedophile's will is revealed after six years Inside the terrifying arsenal lair of boy, 13, planning school massacre...fit with dozens of guns and chilling manifesto Bombshell new video shows US military's direct hit on glowing UFO with hellfire missile Jannik Sinner's ex girlfriend Anna Kalinskaya names and shames'desperate' top-20 male player who slid in her DMs TEN times begging for a date Company offers huge payout to'Phillies Karen' if she returns infamous home run ball... but with one condition The woke masses fled Trump's America in a blind panic. I know the real reason he visited the Queen's grave - do not be taken in by his act: AMANDA PLATELL World-first: Apple Watch can now detect high blood pressure, 'silent killer' behind millions of heart attacks Horror as dead body is found inside trunk of singer D4vd's impounded Tesla Selena Gomez opens up on'weight loss issues' ahead of wedding after facing Ozempic rumors Apple has finally unveiled its latest range of devices at the company's'awe dropping' event in Cupertino, California . While the new iPhone 17 and iPhone 17 Air might have been the centre of attention, Apple has also unveiled two brand new smartwatches.