Angel Reese's latest WNBA controversy shows how victimhood became central to her brand Atlanta Hawks dump former No. 1 pick Zaccharie Risacher after disappointing two-year stint Angel Reese thanks WNBA for suspending Sandy Brondello, frames'protected species' comment as discrimination Rory McIlroy should be the last golfer to criticize others for'performative' behavior Brexton Busch wins first race since father Kyle Busch's death in emotional return to Victory Lane Caitlin Clark'cheering hard' for Argentina over Spain in World Cup final: 'I want Messi' Ella Langley turns 63-year-old former NFL head coach into'Ella Fella' I am once again begging the folks in USC's athletic department to study some Greek literature Jaxson Dart's swimsuit model girlfriend gets patriotic, golfer Hailey Ostrom takes on Lake Powell & Bigfoot Caitlin Clark's former teammate calls out WNBA for suspending Tempo head coach over'protected species' remark Brig Gen John Teichert: Iran's first priority is to kill Americans Brig Gen John Teichert: Iran's first priority is to kill Americans Rod Blagojevich: Democratic Party infected with'virus of socialism' Faith leaders divided on AI's role in worship Rod Blagojevich: Democratic Party infected with'virus of socialism' We've already been living in a'data center world': mikeroweWORKS Foundation CEO OutKick Sports WTA adopts SRY gene testing to protect fair competition in women's professional tennis Supreme Court upholds state bans on biological boys in girls' sports The Supreme Court issues a landmark ruling, upholding state bans that prevent biological boys from competing in girls' sports. Justice Brett Kavanaugh's majority opinion emphasizes biological sex, while Justice Sonia Sotomayor's dissent argues the ruling fails to protect transgender students. This decision draws both celebration from women's sports advocates and criticism from the Democratic Women's Caucus. The Women's Tennis Association (WTA) has just become the latest sports organization to require players to take a genetic test to establish their eligibility to compete in the women's category . The WTA's updated women's eligibility policy requires players to undergo a one-time screening for the SRY gene, which is found on the Y chromosome and is involved in male-typical sex development.

Follow this author to personalize your feed and get instant alerts. Follow Go to your personalized feed WHY FOLLOW? Smart Alerts: Get notified about major news as it happens. Morgan Riddle never swung a racquet on the court at Wimbledon, but her presence in the stands contributed to a cultural shift in the world of tennis all the same. For years, Riddle accompanied her former boyfriend, American player Taylor Fritz, on the ATP Tour, gaining an audience that was just as interested in her style content as it was in her access behind the scenes.

British Wimbledon semi-finalist Arthur Fery has invited Prince George and Princess Charlotte to play tennis with him, after meeting the royals at the men's single's final. The Prince and Princess of Wales, along with Charlotte and George, arrived at the All England Club shortly after 15:00 BST on Sunday, receiving a standing ovation as they entered the royal box. Fery, who turned 24 on Sunday, said: I know the whole family are all tennis fans, so I told her if her kids ever wanted to hit, I'm free. Prince William and Catherine congratulated the tennis player on his run to the semi-finals and wished him a happy birthday. Image caption, Britain's Arthur Fery lost to Alexander Zverev in the men's single's semi-finals Fery also received a birthday card from the Prince and Princess of Wales.

A large-scale wildfire in north Wales as been declared a major incident by emergency services, as firefighters tackle fires across England and Wales during the record-breaking heatwave. Residents near Conwy Mountain and the Sychnant Pass have been evacuated, while members of the public were warned to avoid the area. In Greater Manchester, fire crews are working to contain a moorland fire near a reservoir, while in Camberley, Hampshire, crews are extinguishing a large heathland fire. Wildfires burned in County Durham, Derbyshire, East Sussex, West Sussex, Devon and Somerset over the weekend, during a warning that parts of the country were facing an exceptional risk for fires. North Wales Fire and Rescue Service said in an update on Sunday afternoon that it was working in challenging conditions in order to contain the Conwy Mountain fire, with operations expected to continue for some time.

A racing driver who was in the car with Andrew Freddie Flintoff when he crashed while filming Top Gear in 2022 is suing BBC Studios. Paul Rees gave the presenter expert driving advice from the passenger seat, and is now seeking up to £150,000 for personal injury, according to court documents. It was not publicly known that anyone else was in the open-topped three-wheeled Morgan Super 3 when it overturned during filming. Flintoff suffered serious facial and rib injuries. BBC Studios in its legal response said Rees did not complain of any injuries at the time or after the crash.

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To this end, this paper proposes UNIFIEDREWARD-THINK, the first unified multimodal CoT-based reward model, capable of multi-dimensional, step-by-step long-chain reasoning for both visual understanding and generation reward tasks. Specifically, we adopt an exploration-driven reinforcement finetuning approach to elicit and incentivize the model's latent complex reasoning

Augmenting large language models (LLMs) with external retrieval has become a standard method to address their inherent knowledge cutoff limitations. However, traditional retrieval-augmented generation methods employ static, pre-inference retrieval strategies, making them inadequate for complex tasks involving ambiguous, multi-step, or evolving information needs. Recent advances in test-time scaling techniques have demonstrated significant potential in enabling LLMs to dynamically interact with external tools, motivating the shift toward adaptive inference-time retrieval. Inspired by Information Foraging Theory (IFT), we propose InForage, a reinforcement learning framework that formalizes retrievalaugmented reasoning as a dynamic information-seeking process. Unlike existing approaches, InForage explicitly rewards intermediate retrieval quality, encouraging LLMs to iteratively gather and integrate information through adaptive search behaviors. To facilitate training, we construct a human-guided dataset capturing iterative search and reasoning trajectories for complex, real-world web tasks. Extensive evaluations across general question answering, multi-hop reasoning tasks, and a newly developed real-time web QA dataset demonstrate InForage's superior performance over baseline methods.

Multimodal Large Language Model (MLLM) relies on the powerful LLM to perform multimodal tasks, showing amazing emergent abilities in recent studies, such as writing poems based on an image. However, it is difficult for these case studies to fully reflect the performance of MLLM, lacking a comprehensive evaluation. In this paper, we fill in this blank, presenting the first comprehensive MLLMEvaluation benchmark MME. It measures both perception and cognition abilities on a total of 14 subtasks. In order to avoid data leakage that may arise from direct use of public datasets for evaluation, the annotations of instructionanswer pairs are all manually designed. The concise instruction design allows us to fairly compare MLLMs, instead of struggling in prompt engineering. Besides, with such an instruction, we can also easily carry out quantitative statistics. A total of 30 advanced MLLMs are comprehensively evaluated on our MME, which not only suggests that existing MLLMs still have a large room for improvement, but also reveals the potential directions for the subsequent model optimization. The data are released at the project page: https://github.com/BradyFU/

Effective generalization in language models depends critically on the diversity of their training data. Yet existing diversity metrics often fall short of this goal, relying on surface-level heuristics that are decoupled from model behavior. This motivates us to ask: What kind of diversity in training data actually drives generalization in language models--and how can we measure and amplify it? Through largescale empirical analyses spanning over 300 training runs, carefully controlled for data scale and quality, we show that data diversity can be a strong predictor of generalization in LLM reasoning--as measured by average model performance on unseen out-of-distribution benchmarks. We introduce G-Vendi, a metric that quantifies diversity via the entropy of model-induced gradients. Despite using a small off-the-shelf proxy model for gradients, G-Vendi consistently outperforms alternative measures, achieving strong correlation (Spearman's ρ 0.9) with outof-distribution (OOD) performance on both natural language inference (NLI) and math reasoning tasks.