Dick Cheney dead: Vice President who served with George W. Bush and took leading role in'war on terror' dies at 84 Why Tuesday's races aren't as close as you think: White House analyst CRAIG KESHISHIAN reveals what the polls always miss How Charles reacted when'difficult' William asked if he could do fewer engagements: Biographer ROBERT JOBSON reveals the'tension', secrets of Kate's family life - and how couple are making Prince George'strong' 'She used it to freshen up... it killed her': My wife died of cancer at 63. She never smoked or drank. Taylor Swift enjoys girls' night with squad member Gigi Hadid in NYC after Travis Kelce's ex took swipe Warren Buffett's $6billion stock exit is his loudest warning yet Father reveals'radical faith' spiral of American son killed in hail of arrows by reclusive tribe as new believers consider following him to isolated island My ex is the international fugitive Democrat who's fled to Europe with our nine-year-old son. Here are the disgraceful secrets she'd hate the world to know Woke Gen-Z's revenge: Poll reveals staggering number of under-30s who back Mamdani while their parents are terrified of a return to 1980s New York Coca-Cola faces huge backlash for using AI in its'Holidays are Coming' Christmas advert for the second year in a row - as one viewer calls it the'best ad I've ever seen for Pepsi' Explosive war sparked by Hollywood agent's nepo-baby son dismembering his wife It's the trendy new diagnosis for everything from fatigue to brain fog... but here's the truth about your gut problem - and how to fix it: DR EMILY LEEMING Dallas Cowboys agree huge trade for rival's defensive captain just hours before the NFL deadline Republicans join joyous liberals in dumping on Dick Cheney's death: 'Hell is hot!' AMANDA PLATELL: Fergie's delusions have reached a new low. I can't believe Beatrice and Eugenie are egging her on.

Mysterious glowing orbs have been spotted flying off the coast of Florida - months after New Jersey was invaded by drones. Residents of Daytona Beach have described the unidentified objects rising directly from the ocean and flying over the surface of the water. One extremely viral video from March 17 at around 10pm captured what appeared to be a large object moving toward land, and the flare of light surrounding it gradually dissipating to reveal the shape of an aircraft. While many have dismissed it as simply a passenger plane, locals have shared similar videos online claiming the objects moved in unconventional ways. One particularly extraordinary theory has surfaced on social media, where locals say a'group of whistleblowers' claiming to be'military personnel and sailors' told them the US Navy discovered a'huge' underwater mothership that they believe is producing the orbs.

The hypothesis that pretrained large language models (LLMs) necessitate only minimal supervision during the fine-tuning (SFT) stage (Zhou et al., 2024) has been substantiated by recent advancements in data curation and selection research. However, their stability and generalizability are compromised due to the vulnerability to experimental setups and validation protocols, falling short of surpassing random sampling (Diddee & Ippolito, 2024; Xia et al., 2024b). Built upon LLMs, multi-modal LLMs (MLLMs), combined with the sheer token volume and heightened heterogeneity of data sources, amplify both the significance and complexity of data selection. To harvest multi-modal instructional data in a robust and efficient manner, we re-define the granularity of the quality metric by decomposing it into 14 vision-language-related capabilities, and introduce multi-modal rich scorers to evaluate the capabilities of each data candidate. To promote diversity, in light of the inherent objective of the alignment stage, we take interaction style as diversity indicator and use a multi-modal rich styler to identify data instruction patterns. In doing so, our multi-modal rich scorers and styler (mmSSR) guarantee that high-scoring information is conveyed to users in diversified forms. Free from embedding-based clustering or greedy sampling, mmSSR efficiently scales to millions of data with varying budget constraints, supports customization for general or specific capability acquisition, and facilitates training-free generalization to new domains for curation. Across 10+ experimental settings, validated by 14 multi-modal benchmarks, we demonstrate consistent improvements over random sampling, baseline strategies and state-of-the-art selection methods, achieving 99.1% of full performance with only 30% of the 2.6M data.

An interactive map of UFO sightings has revealed shockingly new reports of drones in New Jersey and other states, suggesting this bizarre mystery is still unfolding. The map, created by the UAP (Unidentified Aerial Phenomena) tracking website Enigma Labs, shows hundreds of sightings logged as recently as January 7 in multiple Northeastern states. The mysterious drones along the East Coast appeared in November, with 22 people issuing reports to Enigma starting on the 20th. But that number dramatically increased to 347 by December 31. A drone ban was issued from December 18 to January 17, during which Enigma labs said the average number of reported sightings dropped by 43 percent.

At first, in mid-November, the mysterious lights were seen blinking across the night skies of New Jersey. Reports of incandescent flying objects were logged in New York, Pennsylvania and Maryland. Bystanders in Virginia Beach said they saw an aircraft "unlike any other they've seen". Sightings have now come from as far afield as Louisiana, Florida and Arizona. People across the US are looking up.

This work introduces a novel graph neural networks (GNNs)-based method to predict stream water temperature and reduce model bias across locations of different income and education levels. Traditional physics-based models often have limited accuracy because they are necessarily approximations of reality. Recently, there has been an increasing interest of using GNNs in modeling complex water dynamics in stream networks. Despite their promise in improving the accuracy, GNNs can bring additional model bias through the aggregation process, where node features are updated by aggregating neighboring nodes. The bias can be especially pronounced when nodes with similar sensitive attributes are frequently connected. We introduce a new method that leverages physical knowledge to represent the node influence in GNNs, and then utilizes physics-based influence to refine the selection and weights over the neighbors. The objective is to facilitate equitable treatment over different sensitive groups in the graph aggregation, which helps reduce spatial bias over locations, especially for those in underprivileged groups. The results on the Delaware River Basin demonstrate the effectiveness of the proposed method in preserving equitable performance across locations in different sensitive groups.

Residents and officials from multiple US states are demanding answers about mysterious drone sightings that have been blamed on everything from foreign governments to alien UFOs. Numerous'SUV-sized' craft first appeared in New Jersey in mid-November, and have since spread to New York, Pennsylvania and Connecticut. Drone sightings have also been reported in states such as Texas, Oklahoma and California as well as foreign countries such as Germany. But it's unclear whether these reports are related to the activity plaguing the Northeast. In New Jersey, the drones sometimes appear in groups and often remain in the same place for hours at a time, according to eyewitnesses.

New Jersey resident Kristen Cobo captures video of approximately 8 suspected drones over a farm near her home on Dec. 12. Drone experts have little idea what the dozens of drone sightings over New Jersey could be, but have ruled out the possibility that they might be the work of a classified government program. They say the lack of a clear image or any residual hardware makes it difficult to make any guesses. "Until something is found, it's really difficult to say," said Brett Velicovich, Fox News contributor and CEO of Expert Drones. "We haven't seen any clear images."

Kentucky Gov. Andy Beshear defended suggesting GOP vice-presidential nominee JD Vance go through a rape-induced abortion to understand the need for reproductive rights in an interview on MSNBC. There's really no other choice but to let Trump be Trump. While Kamala Harris rocked the DNC with an unexpected appearance and short speech to the rapturous crowd, Donald Trump continued to attack his new opponent, sometimes in odd ways. He is ignoring public advice from such close Republican allies as Lindsey Graham. "If you have a policy debate, he wins," the senator said on "Meet the Press."

Over the last ten years, the US Centers for Disease Control and Prevention (CDC) has organized an annual influenza forecasting challenge with the motivation that accurate probabilistic forecasts could improve situational awareness and yield more effective public health actions. Starting with the 2021/22 influenza season, the forecasting targets for this challenge have been based on hospital admissions reported in the CDC's National Healthcare Safety Network (NHSN) surveillance system. Reporting of influenza hospital admissions through NHSN began within the last few years, and as such only a limited amount of historical data are available for this signal. To produce forecasts in the presence of limited data for the target surveillance system, we augmented these data with two signals that have a longer historical record: 1) ILI+, which estimates the proportion of outpatient doctor visits where the patient has influenza; and 2) rates of laboratory-confirmed influenza hospitalizations at a selected set of healthcare facilities. Our model, Flusion, is an ensemble that combines gradient boosting quantile regression models with a Bayesian autoregressive model. The gradient boosting models were trained on all three data signals, while the autoregressive model was trained on only the target signal; all models were trained jointly on data for multiple locations. Flusion was the top-performing model in the CDC's influenza prediction challenge for the 2023/24 season. In this article we investigate the factors contributing to Flusion's success, and we find that its strong performance was primarily driven by the use of a gradient boosting model that was trained jointly on data from multiple surveillance signals and locations. These results indicate the value of sharing information across locations and surveillance signals, especially when doing so adds to the pool of available training data.