'Arc de Trump' designed by president unveiled as he reveals controversial past plan for monument site'Vile' American flag spotted in Republican's office sparks Capitol investigation Experts reveal five-day window when'life-threatening' storm is set to smash US as it brews in Atlantic Ocean RICHARD EDEN: The VERY telling video that suggests one of Meghan's closest confidants has been'Markled'. He once leapt to her defence... now like so many others he needs to watch his step She's the dancer caught'going at it' in bed with Britney Spears. Nepo babies dare to bare! Celebrity offspring leave nothing to imagination as they dominate Victoria's Secret show... what would their parents say? Nightmarish moment train door closes on 65-year-old man's coat and drags him to his death MAUREEN CALLAHAN: Trump's depraved critics have committed their foulest act yet... Bella Hadid's health battle takes dark turn: Loved ones reveal hellish new details about model... as ominous texts emerge Why'embarrassed' Keith Urban is'in hiding' amid divorce from wife Nicole Kidman Disney superfan, 31, vanishes from her Midwest home months after announcing pregnancy... then horrific discovery is made at Walt Disney World Selena Gomez admits she was'sobbing' and fearing the worst just WEEKS after marrying music producer Benny Blanco in lavish ceremony Race against time to build a 211-mile gravel track across America's most extreme frontier for new'Manhattan Project'... but it could be too late Victoria's Secret show 2025: Bella Hadid rules the runway after her health woes, Jasmine Tookes opens the show at nine months pregnant and Emily Ratajkowski makes her debut aged 34 as legendary Angels and nepo babies unite after failed woke rebrand Red-eyed female executive, 61, with $1.1m home attacked two Alaska Airlines staff and forced plane to make emergency landing, police say Most shocking moments from female-fronted talk show dubbed'The View for conservatives' Nancy Pelosi explodes at reporter as she's escorted down Capitol Building steps Is this why aliens haven't contacted us yet? READ MORE: Reaching out to aliens could result in'the end of all life on Earth' It's one of the biggest unanswered questions in science: if there's life beyond Earth, why hasn't it contacted us yet?

'Arc de Trump' designed by president unveiled as he reveals controversial past plan for monument site'Vile' American flag spotted in Republican's office sparks Capitol investigation Experts reveal five-day window when'life-threatening' storm is set to smash US as it brews in Atlantic Ocean RICHARD EDEN: The VERY telling video that suggests one of Meghan's closest confidants has been'Markled'. He once leapt to her defence... now like so many others he needs to watch his step She's the dancer caught'going at it' in bed with Britney Spears. Nepo babies dare to bare! Celebrity offspring leave nothing to imagination as they dominate Victoria's Secret show... what would their parents say? Nightmarish moment train door closes on 65-year-old man's coat and drags him to his death MAUREEN CALLAHAN: Trump's depraved critics have committed their foulest act yet... Bella Hadid's health battle takes dark turn: Loved ones reveal hellish new details about model... as ominous texts emerge Why'embarrassed' Keith Urban is'in hiding' amid divorce from wife Nicole Kidman Disney superfan, 31, vanishes from her Midwest home months after announcing pregnancy... then horrific discovery is made at Walt Disney World Selena Gomez admits she was'sobbing' and fearing the worst just WEEKS after marrying music producer Benny Blanco in lavish ceremony Race against time to build a 211-mile gravel track across America's most extreme frontier for new'Manhattan Project'... but it could be too late Victoria's Secret show 2025: Bella Hadid rules the runway after her health woes, Jasmine Tookes opens the show at nine months pregnant and Emily Ratajkowski makes her debut aged 34 as legendary Angels and nepo babies unite after failed woke rebrand Red-eyed female executive, 61, with $1.1m home attacked two Alaska Airlines staff and forced plane to make emergency landing, police say Most shocking moments from female-fronted talk show dubbed'The View for conservatives' Nancy Pelosi explodes at reporter as she's escorted down Capitol Building steps Experts reveal five-day window when'life-threatening' storm is set to smash US as it brews in Atlantic Ocean A powerful tropical system brewing in the Atlantic Ocean could become the next major threat to lives and property in the US, meteorologists have warned. Forecasters are tracking a tropical wave, a poorly organized area of showers and thunderstorms, currently located off the coast of Africa, which is expected to develop into a named storm between October 21 and 25.

Nancy Pelosi explodes at reporter as she's escorted down Capitol Building steps Trump threatens'land strikes' on Venezuela as CIA begins covert operations in Latin American country and Maduro declares'No to coups' She's the dancer caught'going at it' in bed with Britney Spears. Bella Hadid's health battle takes dark turn: Loved ones reveal hellish new details about model... as ominous texts emerge Diane Keaton's cause of death revealed just days after actress' passing at 79 as her family pens emotional message to fans Emily Ratajkowski fans rejoice as she makes Victoria's Secret show debut at age 34 Murderer's final words and hearty last meal as he's executed after 30 years on death row Nepo babies dare to bare! Celebrity offspring leave nothing to imagination as they dominate Victoria's Secret show... what would their parents say? Victoria's Secret show 2025: Bella Hadid rules the runway after her health woes, Jasmine Tookes opens the show at nine months pregnant and Emily Ratajkowski makes her debut aged 34 as legendary Angels and nepo babies unite after failed woke rebrand Popular food can be used to fight resistant viruses ... and it costs just pennies Disney superfan, 31, vanishes from her Midwest home months after announcing pregnancy... then horrific discovery is made at Walt Disney World Chilling new footage shows knifeman on night he'stabbed Ukrainian refugee to death' on a train in murder that shook America Britney Spears unleashes on ex Kevin Federline AND her SONS - accusing him of'gaslighting' and claiming she's seen one boy for just 45 minutes in five years Jailed Diddy's harsh reality check as very unglamorous conditions rapper has to abide by after prison revealed Mel Gibson's highly-anticipated sequel to The Passion of the Christ has sparked outrage from fans, after it was revealed that it is moving forward with a new cast due to the time gap. The original 2004 movie followed the final 12 hours of Jesus Christ's life, and starred Jim Caviezel, 57, as Christ. However, The Resurrection of the Christ -- which takes place three days after Christ's crucifixion on Good Friday -- will now star Finnish actor Jaakko Ohtonen, 36, in the role of Christ.

Nancy Pelosi explodes at reporter as she's escorted down Capitol Building steps Trump threatens'land strikes' on Venezuela as CIA begins covert operations in Latin American country and Maduro declares'No to coups' She's the dancer caught'going at it' in bed with Britney Spears. Bella Hadid's health battle takes dark turn: Loved ones reveal hellish new details about model... as ominous texts emerge Diane Keaton's cause of death revealed just days after actress' passing at 79 as her family pens emotional message to fans Emily Ratajkowski fans rejoice as she makes Victoria's Secret show debut at age 34 Murderer's final words and hearty last meal as he's executed after 30 years on death row Nepo babies dare to bare! Celebrity offspring leave nothing to imagination as they dominate Victoria's Secret show... what would their parents say? Victoria's Secret show 2025: Bella Hadid rules the runway after her health woes, Jasmine Tookes opens the show at nine months pregnant and Emily Ratajkowski makes her debut aged 34 as legendary Angels and nepo babies unite after failed woke rebrand Popular food can be used to fight resistant viruses ... and it costs just pennies Disney superfan, 31, vanishes from her Midwest home months after announcing pregnancy... then horrific discovery is made at Walt Disney World Chilling new footage shows knifeman on night he'stabbed Ukrainian refugee to death' on a train in murder that shook America Meghan-linked charity is hit by racism and sexism allegations as staff claim it is a'toxic' and'hostile' workplace Britney Spears unleashes on ex Kevin Federline AND her SONS - accusing him of'gaslighting' and claiming she's seen one boy for just 45 minutes in five years Jailed Diddy's harsh reality check as very unglamorous conditions rapper has to abide by after prison revealed Scientists reveal the surprising age at which your brain reaches its peak - so, are YOUR best days behind you? READ MORE: Actor Tom Hanks thinks 35 is the hardest age - but is he right? With each passing day, you may feel like you're getting further past your peak.

Nancy Pelosi explodes at reporter as she's escorted down Capitol Building steps Trump threatens'land strikes' on Venezuela as CIA begins covert operations in Latin American country and Maduro declares'No to coups' She's the dancer caught'going at it' in bed with Britney Spears. Bella Hadid's health battle takes dark turn: Loved ones reveal hellish new details about model... as ominous texts emerge Diane Keaton's cause of death revealed just days after actress' passing at 79 as her family pens emotional message to fans Emily Ratajkowski fans rejoice as she makes Victoria's Secret show debut at age 34 Murderer's final words and hearty last meal as he's executed after 30 years on death row Nepo babies dare to bare! Celebrity offspring leave nothing to imagination as they dominate Victoria's Secret show... what would their parents say? Victoria's Secret show 2025: Bella Hadid rules the runway after her health woes, Jasmine Tookes opens the show at nine months pregnant and Emily Ratajkowski makes her debut aged 34 as legendary Angels and nepo babies unite after failed woke rebrand Popular food can be used to fight resistant viruses ... and it costs just pennies Disney superfan, 31, vanishes from her Midwest home months after announcing pregnancy... then horrific discovery is made at Walt Disney World Chilling new footage shows knifeman on night he'stabbed Ukrainian refugee to death' on a train in murder that shook America Britney Spears unleashes on ex Kevin Federline AND her SONS - accusing him of'gaslighting' and claiming she's seen one boy for just 45 minutes in five years Jailed Diddy's harsh reality check as very unglamorous conditions rapper has to abide by after prison revealed Britain has experienced its first official'MEGA FIRE' - and scientists warn the devastating blazes could soon become the norm READ MORE: Scientists warn that'FIREWAVES' will devastate UK cities Britain has experienced its first official'mega fire' - and scientists warn the devastating blazes could soon become the norm. Back in June, the Carrbridge and Dava Moor in the Scottish Highlands was devastated by the worst wildfire in living memory. The blaze burned over 11,000 hectares (42.5 square miles) of forest and peatland, killing thousands of animals in its path.

Grounded Multimodal Named Entity Recognition (GMNER) task aims to identify named entities, entity types and their corresponding visual regions. GMNER task exhibits two challenging attributes: 1) The tenuous correlation between images and text on social media contributes to a notable proportion of named entities being ungroundable. 2) There exists a distinction between coarse-grained noun phrases used in similar tasks (e.g., phrase localization) and fine-grained named entities. In this paper, we propose RiVEG, a unified framework that reformulates GMNER into a joint MNER-VE-VG task by leveraging large language models (LLMs) as connecting bridges. This reformulation brings two benefits: 1) It enables us to optimize the MNER module for optimal MNER performance and eliminates the need to pre-extract region features using object detection methods, thus naturally addressing the two major limitations of existing GMNER methods. 2) The introduction of Entity Expansion Expression module and Visual Entailment (VE) module unifies Visual Grounding (VG) and Entity Grounding (EG). This endows the proposed framework with unlimited data and model scalability. Furthermore, to address the potential ambiguity stemming from the coarse-grained bounding box output in GMNER, we further construct the new Segmented Multimodal Named Entity Recognition (SMNER) task and corresponding Twitter-SMNER dataset aimed at generating fine-grained segmentation masks, and experimentally demonstrate the feasibility and effectiveness of using box prompt-based Segment Anything Model (SAM) to empower any GMNER model with the ability to accomplish the SMNER task. Extensive experiments demonstrate that RiVEG significantly outperforms SoTA methods on four datasets across the MNER, GMNER, and SMNER tasks.

Recent years have seen the dramatic rise of the usage of AI algorithms in pure mathematics and fundamental sciences such as theoretical physics. This is perhaps counter-intuitive since mathematical sciences require the rigorous definitions, derivations, and proofs, in contrast to the experimental sciences which rely on the modelling of data with error-bars. In this Perspective, we categorize the approaches to mathematical discovery as "top-down", "bottom-up" and "meta-mathematics", as inspired by historical examples. We review some of the progress over the last few years, comparing and contrasting both the advances and the short-comings in each approach. We argue that while the theorist is in no way in danger of being replaced by AI in the near future, the hybrid of human expertise and AI algorithms will become an integral part of theoretical discovery.

Self-supervised learning on graphs can be bifurcated into contrastive and generative methods. Contrastive methods, also known as graph contrastive learning (GCL), have dominated graph self-supervised learning in the past few years, but the recent advent of graph masked autoencoder (GraphMAE) rekindles the momentum behind generative methods. Despite the empirical success of GraphMAE, there is still a dearth of theoretical understanding regarding its efficacy. Moreover, while both generative and contrastive methods have been shown to be effective, their connections and differences have yet to be thoroughly investigated. Therefore, we theoretically build a bridge between GraphMAE and GCL, and prove that the node-level reconstruction objective in GraphMAE implicitly performs context-level GCL. Based on our theoretical analysis, we further identify the limitations of the GraphMAE from the perspectives of alignment and uniformity, which have been considered as two key properties of high-quality representations in GCL. We point out that GraphMAE's alignment performance is restricted by the masking strategy, and the uniformity is not strictly guaranteed. To remedy the aforementioned limitations, we propose an Alignment-Uniformity enhanced Graph Masked AutoEncoder, named AUG-MAE. Specifically, we propose an easy-to-hard adversarial masking strategy to provide hard-to-align samples, which improves the alignment performance. Meanwhile, we introduce an explicit uniformity regularizer to ensure the uniformity of the learned representations. Experimental results on benchmark datasets demonstrate the superiority of our model over existing state-of-the-art methods.

The fractal dimension provides a statistical index of object complexity by studying how the pattern changes with the measuring scale. Although useful in several classification tasks, the fractal dimension is under-explored in deep learning applications. In this work, we investigate the features that are learned by deep models and we study whether these deep networks are able to encode features as complex and high-level as the fractal dimensions. Specifically, we conduct a correlation analysis experiment to show that deep networks are not able to extract such a feature in none of their layers. We combine our analytical study with a human evaluation to investigate the differences between deep learning networks and models that operate on the fractal feature solely. Moreover, we show the effectiveness of fractal features in applications where the object structure is crucial for the classification task. We empirically show that training a shallow network on fractal features achieves performance comparable, even superior in specific cases, to that of deep networks trained on raw data while requiring less computational resources. Fractals improved the accuracy of the classification by 30% on average while requiring up to 84% less time to train. We couple our empirical study with a complexity analysis of the computational cost of extracting the proposed fractal features, and we study its limitation.

Undoubtedly that the Bidirectional Encoder representations from Transformers is the most powerful technique in making Natural Language Processing tasks such as Named Entity Recognition, Question & Answers or Sentiment Analysis, however, the use of traditional techniques remains a major potential for the improvement of recent models, in particular word tokenization techniques and embeddings, but also the improvement of neural network architectures which are now the core of each architecture. recent. In this paper, we conduct a comparative study between Fine-Tuning the Bidirectional Encoder Representations from Transformers and a method of concatenating two embeddings to boost the performance of a stacked Bidirectional Long Short-Term Memory-Bidirectional Gated Recurrent Units model; these two approaches are applied in the context of sentiment analysis of shopping places in Morocco. A search for the best learning rate was made at the level of the two approaches, and a comparison of the best optimizers was made for each sentence embedding combination with regard to the second approach.