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Misinformation Detection using Large Language Models with Explainability

arXiv.org Artificial Intelligence

The COVID Fake News dataset is a collection of mostly COVID-19 pandemic-specific news headlines and brief claims. The data is representative of the combination of proven factual statements and much misleading or outright false information widespread on digital platforms during the pandemic. The data set was then preprocessed and split into training (8,160 samples) and testing (2,041 samples) categories in a balanced portion so that both real and fake labels could be checked robustly. The dataset used to check whether the pipeline can be applied to other domains rather than the pandemic area is the FakeNewsNet GossipCop. This dataset lies in the domain of entertainment and celebrity news and it is one of the prominent areas where gossip, rumors, fabricated stories are prevalent. Approximately 10,000 samples were used to train, and 2,500 samples were used to test. In the present dataset, the labels distinguish the news objects as Real or Fake by fact-checking them with regards to the original GossipCop platform. The two datasets were combined, standardized, and stratified to ensure the balanced classes in the samples during training and validation. Such prudent training has the benefit of enabling these models to improve in identifying subtle signs in language that may be contained in actual and made-up claims that can be used in enhancing the pipeline to perform better in practical misinformation detection applications.


MUG-V 10B: High-efficiency Training Pipeline for Large Video Generation Models

arXiv.org Artificial Intelligence

In recent years, large-scale generative models for visual content (\textit{e.g.,} images, videos, and 3D objects/scenes) have made remarkable progress. However, training large-scale video generation models remains particularly challenging and resource-intensive due to cross-modal text-video alignment, the long sequences involved, and the complex spatiotemporal dependencies. To address these challenges, we present a training framework that optimizes four pillars: (i) data processing, (ii) model architecture, (iii) training strategy, and (iv) infrastructure for large-scale video generation models. These optimizations delivered significant efficiency gains and performance improvements across all stages of data preprocessing, video compression, parameter scaling, curriculum-based pretraining, and alignment-focused post-training. Our resulting model, MUG-V 10B, matches recent state-of-the-art video generators overall and, on e-commerce-oriented video generation tasks, surpasses leading open-source baselines in human evaluations. More importantly, we open-source the complete stack, including model weights, Megatron-Core-based large-scale training code, and inference pipelines for video generation and enhancement. To our knowledge, this is the first public release of large-scale video generation training code that exploits Megatron-Core to achieve high training efficiency and near-linear multi-node scaling, details are available in https://github.com/Shopee-MUG/MUG-V.


Can LLMs Correct Themselves? A Benchmark of Self-Correction in LLMs

arXiv.org Artificial Intelligence

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/


Astronomers' telescope 'hack' uncovered a lopsided star

Popular Science

Science Space Deep Space Astronomers' telescope'hack' uncovered a lopsided star The rapidly spinning star beta Canis Minoris is about 162 light-years away from Earth. Breakthroughs, discoveries, and DIY tips sent every weekday. The bigger the viewing aperture, the more light it can collect. More light helps reveal fainter cosmic objects, as well as sharpen the images themselves. For astronomers, the best results usually come from sharing images between telescopes around the world that are linked together.


Our Favorite High Resolution Mirrorless Camera Is 900 Off Right Now

WIRED

We found two outstanding camera deals, including one on Sony's A7R V at the lowest price it's ever been. All products featured on WIRED are independently selected by our editors. However, we may receive compensation from retailers and/or from purchases of products through these links. If you want to step up your photography game, and graduate from your phone, why not go all the way to highest resolution camera on the market? Normally, we suggest that a more affordable camera might be the best pick for most people in our guide to mirrorless cameras, but at this price--why not go big?


Teen turns his suburban home into elaborate haunted house every October

Popular Science

This year, 16-year-old Joe Veneziale created a terrifying Old Hollywood hotel. Every October, 16-year-old Joe Veneziale builds a haunted house in his suburban Philadelphia neighborhood. The haunt is complete with live actors, intricate sets, and state-of-the-art tech. Breakthroughs, discoveries, and DIY tips sent every weekday. Joe Veneziale is known as the "Halloween guy" at his high school, and for good reason.


Suzanne Somers planned AI 'twin' decades before 2023 death, husband Alan Hamel reveals

FOX News

Alan Hamel reveals that creating an AI twin of his late wife Suzanne Somers, who died from breast cancer in 2023, was originally her idea to help fans.


Dispatch: Partying at one of Africa's largest AI gatherings

MIT Technology Review

Nyalleng Moorosi is part of a movement aimed at involving more African voices in AI policymaking. The room is draped in white curtains, and a giant screen blinks with videos created with generative AI. A classic East African folk song by the Tanzanian singer Saida Karoli plays loudly on the speakers. Friends greet each other as waiters serve arrowroot crisps and sugary mocktails. A man and a woman wearing leopard skins atop their clothes sip beer and chat; many women are in handwoven Ethiopian garb with red, yellow, and green embroidery. "The best thing about the Indaba is always the parties," computer scientist Nyalleng Moorosi tells me.


3 Things Stephanie Arnett is into right now

MIT Technology Review

MIT Technology Review's visuals editor shares the birding app, journaling system, and book series capturing her attention lately. This science fiction book series confronted me with existential questions like "Are we alone in the universe?" In the series, aliens destroy most of Earth, leaving the titular Carl and Princess Donut, his ex-girlfriend's cat, to fight in a bloodthirsty game of survival with rules that are part reality TV and part video game dungeon crawl. I particularly recommend the audiobook, voiced by Jeff Hays, which makes the numerous characters easy to differentiate. For years I've tried to find a perfect system to keep track of all my random notes and weird little rabbit holes of inspiration. None of my paper journals or paid apps have been able to top how customizable and convenient the developer-favorite notetaking app Obsidian is.


Revealed: The simple gesture that suggests your partner is a PSYCHOPATH

Daily Mail - Science & tech

Melania Trump accused of'calculated campaign to destroy' notorious biographer in lawsuit claiming she sabotaged tell-all on First Lady Popular hair products associated with multiple cancers... including one of the deadliest Prince Andrew will be summoned to give evidence on Jeffrey Epstein to US Congress committee as victim says shamed royal should'do right' by Virginia Guiffre and testify What Britney Spears is really like behind closed doors: For first time, Kevin Federline reveals secrets he refused to spill even for $1 million... including'terrifying' acts that left their children running to him The real story behind Jim Carrey's disappearance: He once made $20m per film. Now insiders tell TOM LEONARD about the mysterious suicide of his married lover and claims of autism'cure' at the heart of his Hollywood downfall Is Meghan about to launch a new'Kardashian-style' mega brand? Duchess cosies up to CEO behind Kim Kardashian's wildly successful Skims range as speculation about her new venture grows Women's tennis in'manliness' row: World's No 1 and 2 come under fire from rival for their'high testosterone' - before Aryna Sabalenka appears to fire back after being labelled a'big' player Harvey Weinstein's ex-wife Georgina Chapman is facing foreclosure on $2.5 million NYC home Suzanne Somers' widower shocks fans as he resurrects star in'AI clone' format: 'You can't tell the difference' Vicious catfight erupts between Trump's leading ladies. Feud is talk of White House: 'It's real and it's personal' Karoline Leavitt goes scorched earth on'bitter' Biden press secretary over'deplorable' comments Three brutal words in my best friend's wedding invite cut like a knife. Meghan's hit a trashy new low.