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.

Russian President Vladimir Putin has apologised to his Azerbaijani counterpart Ilham Aliyev for what he called a "tragic incident" following the deadly crash of an Azerbaijan Airlines plane this week in Kazakhstan. The plane was flying on Wednesday from Azerbaijan's capital of Baku to Grozny, the regional capital of the Russian republic of Chechnya, when it turned towards Kazakhstan and crashed while attempting to land. In a statement on Saturday, the Kremlin said Russian air defence systems were firing near Grozny due to a Ukrainian drone strike, but stopped short of saying one of these hit the plane. "Vladimir Putin apologised for the tragic incident that occurred in Russian airspace and once again expressed his deep and sincere condolences to the families of the victims and wished a speedy recovery to the injured," the Kremlin said. "At that time, Grozny, Mozdok and Vladikavkaz were being attacked by Ukrainian unmanned aerial vehicles, and Russian air defence systems repelled these attacks."

The Kremlin released a statement on Saturday noting Putin had spoken to Azerbaijan's president Ilham Aliyev by phone. "(President) Vladimir Putin apologised for the tragic incident that occurred in Russian airspace and once again expressed his deep and sincere condolences to the families of the victims and wished a speedy recovery to the injured," the statement said. Prior to Saturday, the Kremlin had not yet commented on the crash. But Russian aviation authorities had said the situation in the region was "very complicated" due to Ukrainian drone strikes on Chechnya. Aviation experts and others in Azerbaijan believe the plane's GPS systems were affected by electronic jamming and it was then damaged by shrapnel from Russian air defence missile blasts.

Fox News correspondent Stephanie Bennett has the latest on the aftermath of the Kazakhstan plane crash on'Special Report.' Crew members and survivors of the Azerbaijan Airlines plane that crashed in Kazakhstan on Christmas Day say they heard at least one loud bang before the aircraft crashed in a ball of fire, heightening speculation that a Russian anti-aircraft missile may have been responsible for the tragedy. The Embraer 190 passenger jet flying from Azerbaijan to Russia crashed near the city of Aktau in Kazakhstan after diverting from an area of southern Russia where Moscow has repeatedly used air defense systems against Ukrainian attack drones. At least 38 people were killed while 29 survived. Subhonkul Rakhimov, one of the passengers aboard Flight J2-8243, told Reuters from the hospital that he had begun to recite prayers and prepare for the end after hearing a bang.

Kyiv, Ukraine – Russian air defence officials could very possibly have struck an Azerbaijani passenger jet over Chechnya after panicking during a Ukrainian drone attack, analysts and experts from Ukraine, Kazakhstan and Azerbaijan have told Al Jazeera. Moscow might have also compounded what one expert described as a "crime" by not letting the damaged plane land nearby and instead forcing it to fly to Kazakhstan. The analysis by these experts comes amid mounting reports quoting unnamed Azerbaijani officials and other analysts pointing fingers at Russia for the crash, in which at least 38 people were killed. The Kremlin claimed that the AZAL 8432 flight with 67 passengers on board hit a flock of birds early Wednesday after it entered Russian airspace to land in Grozny, Chechnya's administrative capital. But within hours, photos and videos of the plane surfaced, apparently showing deep holes and multiple pockmarks on its tail.

Russian air defenses downed an Azerbaijan Airlines plane that crashed in Kazakhstan, killing 38 people, four sources with knowledge of the preliminary findings of Azerbaijan's investigation into the disaster said on Thursday. Flight J2-8243 crashed on Wednesday in a ball of fire near the city of Aktau in Kazakhstan after diverting from an area of southern Russia, where Moscow has repeatedly used air defense systems against Ukrainian drone strikes. The Embraer passenger jet had flown from Azerbaijan's capital Baku to Grozny, in Russia's southern Chechnya region, before veering off hundreds of miles across the Caspian Sea. It crashed on the opposite shore of the Caspian after what Russia's aviation watchdog said was an emergency that may have been caused by a bird strike. Officials did not explain why it had crossed the sea.

Azerbaijan is observing a day of mourning for the victims of an air crash that killed 38 people. At least 29 people survived the deadly crash on Christmas day. Azerbaijan observed a nationwide moment of silence on Thursday, with national flags lowered, traffic coming to a halt at noon, and signals sounding from ships and trains across the country. Earlier, Azerbaijani President Ilham Aliyev declared Thursday a day of mourning and cancelled a planned visit to Russia for an informal summit of the Commonwealth of Independent States (CIS), a grouping of former Soviet nations. Aliyev's office said the president "ordered the prompt initiation of urgent measures to investigate the causes of the disaster".

Inquisitive questions -- open-ended, curiosity-driven questions people ask as they read -- are an integral part of discourse processing (Kehler and Rohde, 2017; Onea, 2016) and comprehension (Prince, 2004). Recent work in NLP has taken advantage of question generation capabilities of LLMs to enhance a wide range of applications. But the space of inquisitive questions is vast: many questions can be evoked from a given context. So which of those should be prioritized to find answers? Linguistic theories, unfortunately, have not yet provided an answer to this question. This paper presents QSALIENCE, a salience predictor of inquisitive questions. QSALIENCE is instruction-tuned over our dataset of linguist-annotated salience scores of 1,766 (context, question) pairs. A question scores high on salience if answering it would greatly enhance the understanding of the text (Van Rooy, 2003). We show that highly salient questions are empirically more likely to be answered in the same article, bridging potential questions (Onea, 2016) with Questions Under Discussion (Roberts, 2012). We further validate our findings by showing that answering salient questions is an indicator of summarization quality in news.

We propose and evaluate an automated pipeline for discovering significant topics from legal decision texts by passing features synthesized with topic models through penalised regressions and post-selection significance tests. The method identifies case topics significantly correlated with outcomes, topic-word distributions which can be manually-interpreted to gain insights about significant topics, and case-topic weights which can be used to identify representative cases for each topic. We demonstrate the method on a new dataset of domain name disputes and a canonical dataset of European Court of Human Rights violation cases. Topic models based on latent semantic analysis as well as language model embeddings are evaluated. We show that topics derived by the pipeline are consistent with legal doctrines in both areas and can be useful in other related legal analysis tasks.

Autodesk's Will Harris, Foundry's Mathieu Mazerolle and Unity Technologies' Brian Gaffney will discuss how their companies are incorporating machine learning into software tools to make higher quality and more realistic visual effects and boost production speed. Visual Effects Supervisor Ryan Laney will describe the novel way artificial intelligence and machine learning were used to mask the identities of interview subjects in the award-winning HBO documentary Welcome to Chechnya. "Machine learning is poised to transform visual effects production, accelerating workflows and paving the way for a new generation of astonishingly real visual effects," says Barry Goch, who will moderate the discussion. "Will Harris, Mathieu Mazerolle and Brian Gaffney will demonstrate game-changing technologies. Ryan Laney will share his experience in applying machine learning to a real-world production."