You're viewing the US edition You can switch to the UK or AU homepage at any time using this menu. US Army U-turn over futuristic drone and robot unit is slammed as'deeply dangerous' This is an epic humiliation for Harry and Meghan. But these two are dangerous... we should fear the twisted real strategy behind their UK return: MAUREEN CALLAHAN America's pancreatic cancer explosion: Science breakthrough leaves experts fearing surprisingly common lifestyle habit is behind surge in young patients... as new early warning sign is revealed Trump's under-siege aide Natalie Harp caught in foul-mouthed explosion as insiders reveal White House whispers about her close access to president Sussexes'already have a house lined up to live in... and it's not a Royal residence' A close friend of Trump has told me the truth about his young aide Natalie. There's a reason the whispers are getting louder: KENNEDY Hayden Panettiere's LA neighbors were warned to call police if they saw her ex Brian Hickerson in the past... as DEA reportedly joins investigation into star's death I was mocked a year ago when I warned there was an Establishment plot to bring Harry and Meghan back to Britain. Now I've been proven right... and my sources have made it clear this is only the beginning: RICHARD EDEN Surrogate who refused to abort baby in fresh battle with biological parents over child's NAME Why loyal Trump aide Natalie Harp has only one pair of shoes - and she can even drive a golf cart in them! The'affair mode' phone settings that all cheaters use: I knew my partner was up to something... here's how I cracked his secret code and uncovered all his dirty antics Read Brian Hickerson's sinister texts to girlfriend Hayden Panettiere as he breaks cover after star's death: 'Time to go to war' Shocking moment 16-year-old girl storms field and tackles middle school football player... before being hit with assault charges and lifetime ban Virginia mother stabbed to death on jogging trail'by teenage migrant coworker' who was caught entering US illegally two years ago... then released Brooklyn Beckham's pizza-making post is flooded with pleas from fans as he shares cooking video hours after brother Romeo attended Italian culinary class Common brain disorder suffered by millions is often dismissed as being'all in your head' READ MORE: Life skill that reduces chances of dying from Alzheimer's disease By the time many people with functional neurological disorder - a condition in which there is a problem with how the brain sends and receives signals - arrive at a doctor's office, they have heard these five words more times than they can count.

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Alpha-gal syndrome is a strange tick-borne illness that induces an allergy to a specific type of sugar found in red meat.

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Anguished family of teenager murdered at New Year's Eve party in 1982 reveal killer's final act of cruelty as he takes crucial detail to the grave after being executed in Florida Trump outlines plan to destroy Iran's power plants and bridges next week as he warns bombing will continue until he says'enough' DR PHIL: I've reviewed hundreds of secret government UFO videos and files that have been actively hidden from the public... what I can now reveal about non-human life and this psyop cover-up could spark a national crisis Heiress' $2m Aspen wedding was'horrific nightmare' that sparked the mother of all lawsuits before a bombshell divorce... Now she'll try again with new hunk Truth about Alix Earle's revolving door of famous men: Friends insist it's just a'hot girl summer' of one-time flings... but now insiders blow lid on her desperate secret and jaw-dropping ulterior motive Matt Damon reveals'new phase of life' as he brings wife and rarely seen daughter, 20, to The Odyssey ...

Occam's razor has lost its edge. Can we sharpen our search for truth? Seeking out the simplest, most elegant explanations has served scientists well for centuries, but cognitive scientist Marina Dubova's experiments are revealing better ways to uncover reality Limited by the knowledge of his time, the ancient Greek astronomer Ptolemy imagined that the planets and sun of our solar system orbited Earth. Every new observation that pushed against this image required a slight tweak to that theory, until centuries later Nicolaus Copernicus's reimagining toppled it once and for all. A more elegant explanation proposed that all the planets orbited the sun, kicking off a scientific revolution that changed our understanding of the entire universe.

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Clinical reasoning in medicine is a hypothesis-driven process where physicians refine diagnoses from limited information through targeted history, physical examination, and diagnostic investigations. In contrast, current medical benchmarks for large language models (LLMs) primarily assess knowledge recall through single-turn questions, where complete clinical information is provided upfront. To address this gap, we introduce VivaBench, a multi-turn benchmark that evaluates sequential clinical reasoning in LLM agents. Our dataset comprises 1152 physiciancurated clinical vignettes structured as interactive scenarios that simulate a viva voce examination in medical training, requiring agents to actively probe for relevant findings, select appropriate investigations, and synthesize information across multiple steps to reach a diagnosis. We evaluated several state-of-the-art LLMs and found that while models demonstrate competence in diagnosing conditions within well-described clinical presentations, their performance degrades significantly when required to navigate diagnostic uncertainty. Our analysis identified several failure modes that mirror common issues in clinical practice, including: (1) fixation on initial hypotheses, (2) excessive investigation ordering, (3) premature diagnostic closure, and (4) missing critical conditions. These patterns reveal fundamental limitations in how current LLMs manage uncertainty and gather information sequentially. Through VivaBench, we provide a standardized benchmark for evaluating conversational medical AI systems for real-world clinical decision support. Beyond medical applications, we contribute to the larger corpus of research on agentic AI by demonstrating how sequential reasoning trajectories can diverge in complex decision-making environments.

Large Language Models are typically trained on datasets collected from the web, which may inadvertently contain harmful or sensitive personal information. To address growing privacy concerns, unlearning methods have been proposed to remove the influence of specific data from trained models. Of these, exact unlearning-- which retrains the model from scratch without the target data--is widely regarded as the gold standard for mitigating privacy risks in deployment. In this paper, we revisit this assumption in a practical deployment setting where both the pre-and post-unlearning logits API are exposed, such as in open-weight scenarios. Targeting this setting, we introduce a novel data extraction attack that leverages signals from the pre-unlearning model to guide the post-unlearning model, uncovering patterns that reflect the removed data distribution. Combining model guidance with a token filtering strategy, our attack significantly improves extraction success rates-- doubling performance in some cases--across common benchmarks such as MUSE, TOFU, and WMDP. Furthermore, we demonstrate our attack's effectiveness on a simulated medical diagnosis dataset to highlight real-world privacy risks associated with exact unlearning. In light of our findings, which suggest that unlearning may, in a contradictory way, increase the risk of privacy leakage during realworld deployments, we advocate for evaluation of unlearning methods to consider broader threat models that account not only for post-unlearning models but also for adversarial access to prior checkpoints.