Could Ukraine hold a presidential election right now? Will Europe use frozen Russian assets to fund war? How can Ukraine rebuild China ties? 'Ukraine is running out of men, money and time' Putin says Russia believes it will win in Ukraine in New Year's Eve address Russian President Vladimir Putin has said his country believes it will win the war in Ukraine, nearly four years after he launched an invasion of the neighbouring nation, in comments made during his televised annual New Year's Eve address. The Russian leader called on the country on Wednesday to "support our heroes" fighting in Ukraine, where troops have been waging a brutal offensive since February 2022.

Ramzan Kadyrov vows retaliation against Ukraine following drone attack on Grozny building, while Ukrainian officials say Zelenskyy remains unafraid of threats.

What is in the 28-point US plan for Ukraine? 'Ukraine is running out of men, money and time' Can the US get all sides to end the war? Why is Europe opposing Trump's peace plan? Here's where things stand on Saturday, December 6: A Russian drone attack killed two men, aged 52 and 67, in the Ukrainian city of Izyum as they were unloading firewood from a truck, according to local officials. Russian forces also killed a 12-year-old boy in an attack on the Vasylkivska community in Ukraine's Dnipropetrovsk region, and wounded more than a dozen Ukrainians in attacks on the Kherson, Donetsk and Sumy regions, local officials said.

South Park's 27th season return featured a jaw-dropping deepfake of Donald Trump that resulted in an official statement from the White House. South Park's 27th season return featured a jaw-dropping deepfake of Donald Trump that resulted in an official statement from the White House. Deepfakes come with risks that demand urgent regulation. But it is vital their potential as a creative and satirical tool isn't stifled S alman Rushdie believes AI will not be a threat to authors until ChatGPT can write " a funny book ". His faith in human over synthetic creativity may hold some truth in the literary space.

Breakthroughs, discoveries, and DIY tips sent every weekday. Tesla's roughly 7,000-pound stainless steel Cybertruck may not have sold particularly well among the general public, but it does appear to have found a receptive audience in one particular cohort: law enforcement. Police departments across the US--and as far away as the Qatar--have been spotted driving the electric behemoth. Now, a jet-black, militarized Cybertruck is reportedly among the vehicles set to respond to potential incidents during 2026 World Cup matches taking place in Jalisco, Mexico. Officials from the central state of Jalisco said this week that several Cybertrucks will be among 300 new tactical, armored vehicles added to its fleet. The move, first reported by the Jalisco-based newspaper El Informador, is part of a broader effort to revamp the state's police force in preparation for the influx of tourists expected to visit the capitol, Guadalajara, for World Cup matches next year.

The ability of Natural Language Processing (NLP) methods to categorize text into multiple classes has motivated their use in online content moderation tasks, such as hate speech and fake news detection. However, there is limited understanding of how or why these methods make such decisions, or why certain content is moderated in the first place. To investigate the hidden mechanisms behind content moderation, we explore multiple directions: 1) training classifiers to reverse-engineer content moderation decisions across countries; 2) explaining content moderation decisions by analyzing Shapley values and LLM-guided explanations. Our primary focus is on content moderation decisions made across countries, using pre-existing corpora sampled from the Twitter Stream Grab. Our experiments reveal interesting patterns in censored posts, both across countries and over time. Through human evaluations of LLM-generated explanations across three LLMs, we assess the effectiveness of using LLMs in content moderation. Finally, we discuss potential future directions, as well as the limitations and ethical considerations of this work. Our code and data are available at https://github.com/causalNLP/censorship

The use of narratives as a means of fusing information from knowledge graphs (KGs) into a coherent line of argumentation has been the subject of recent investigation. Narratives are especially useful in event-centric knowledge graphs in that they provide a means to connect different real-world events and categorize them by well-known narrations. However, specifically for controversial events, a problem in information fusion arises, namely, multiple viewpoints regarding the validity of certain event aspects, e.g., regarding the role a participant takes in an event, may exist. Expressing those viewpoints in KGs is challenging because disputed information provided by different viewpoints may introduce inconsistencies. Hence, most KGs only feature a single view on the contained information, hampering the effectiveness of narrative information access. This paper is an extension of our original work and introduces attributions, i.e., parameterized predicates that allow for the representation of facts that are only valid in a specific viewpoint. For this, we develop a conceptual model that allows for the representation of viewpoint-dependent information. As an extension, we enhance the model by a conception of viewpoint-compatibility. Based on this, we deepen our original deliberations on the model's effects on information fusion and provide additional grounding in the literature.

President Vladimir Putin on Saturday apologized to Azerbaijan's leader for what the Kremlin called a "tragic incident" over Russia in which an Azerbaijan Airlines plane crashed after Russian air defences were fired against Ukrainian drones. The extremely rare publicized apology from Putin was the closest Moscow had come to accepting some blame for Wednesday's disaster, although the Kremlin statement did not say Russia had shot down the plane, only noting that a criminal case had been opened. Flight J2-8243, en route from Baku to the Chechen capital Grozny, crash-landed on Wednesday near Aktau in Kazakhstan after diverting from southern Russia, where Ukrainian drones were reported to be attacking several cities. At least 38 people were killed.