Zero-Shot Stance Detection (ZSSD) identifies the attitude of the post toward unseen targets. Existing research using contrastive, meta-learning, or data augmentation suffers from generalizability issues or lack of coherence between text and target. Recent works leveraging large language models (LLMs) for ZSSD focus either on improving unseen target-specific knowledge or generating explanations for stance analysis. However, most of these works are limited by their over-reliance on explicit reasoning, provide coarse explanations that lack nuance, and do not explicitly model the reasoning process, making it difficult to interpret the model's predictions. To address these issues, in our study, we develop a novel interpretable ZSSD framework, IRIS. We provide an interpretable understanding of the attitude of the input towards the target implicitly based on sequences within the text (implicit rationales) and explicitly based on linguistic measures (explicit rationales). IRIS considers stance detection as an information retrieval ranking task, understanding the relevance of implicit rationales for different stances to guide the model towards correct predictions without requiring the ground-truth of rationales, thus providing inherent interpretability. In addition, explicit rationales based on communicative features help decode the emotional and cognitive dimensions of stance, offering an interpretable understanding of the author's attitude towards the given target. Extensive experiments on the benchmark datasets of VAST, EZ-STANCE, P-Stance, and RFD using 50%, 30%, and even 10% training data prove the generalizability of our model, benefiting from the proposed architecture and interpretable design.

How much of Europe's oil still comes from Russia? The European Union is preparing to adopt a new round of sweeping sanctions against Russian energy exports on Thursday, a day after United States President Donald Trump imposed similar measures against Moscow amid setbacks to his efforts at diplomacy with Vladimir Putin. These steps come as Russia and Ukraine are increasingly targeting each other's energy infrastructure in an attempt to make it economically harder to wage war. On the ground, Russia's war in Ukraine remained stagnant. Russia claimed it had taken another handful of villages during the past week - Tykhe and Pishchane in Kharkiv, Novopavlivka, Chunyshyne and Pleshcheyevka in Donetsk, Poltavka in Zaporizhia and Privillia in Dnipropetrovsk. On the whole, however, Ukrainian front lines remained resilient and Russia scored no major breakthrough.

How is Russia replenishing its military? What is a'coalition of the willing'? How China forgot promises and'debts' to Ukraine How are Europe, the US pulling apart on Ukraine? An early morning Russian attack on Friday killed three people in northern Ukraine's Sumy region, a regional official reported. Ukrainian President Volodymyr Zelenskyy said Moscow's attempts to advance in the Sumy area had failed with heavy losses, and Russian operations in the region were being "completely foiled by our forces".

Ukraine has struck Russia's largest oil terminal on the Baltic Sea during one of its biggest overnight drone attacks in months. The aerial assault targeted the Primorsk oil port in the Leningrad region, the final station of the Baltic Pipeline System and a crucial hub for Russia's maritime exports, Ukraine's security services told multiple outlets. More than half of the 221 drones sent to Russian territory were intercepted over the Bryansk and Smolensk regions, where Lukoil facilities were also reportedly targeted, the Russian defence ministry said. Meanwhile, officials said two civilians were killed in Ukraine's Sumy region when a Russian glide bomb struck a village near the border. Authorities in the Leningrad region said 28 drones were brought down and that a fire had broken out at a vessel and a pumping station in Primorsk.

A Russian air raid on a shopping centre and market in Dobropillia, eastern Ukraine, killed at least two people, wounded 22 others and caused widespread damage on Wednesday, the regional governor, Vadym Filashkin, said. Filashkin said the building was struck by a 500kg (1,100-pound) bomb at 5:20pm (14:20 GMT). Russia launched 400 Shahed and decoy drones, as well as one ballistic missile, on Wednesday night, the Ukrainian air force said. The strikes targeted the northeastern city of Kharkiv, the central city of Kryvyi Rih, Vinnytsia in the west, and Odesa in the south. A Ukrainian drone killed one person and injured six others in the Russian city of Belgorod, and injured one person in a village northeast of the city, the regional governor, Vyacheslav Gladkov, said.

The Ukrainian Air Force said Russia launched four missiles and 131 drones towards Ukraine overnight. The Air Force also said that 72 of the drones were destroyed while 59 disappeared without reaching their targets. Moscow's Ministry of Defence said its troops intercepted and destroyed 55 Ukrainian drones in six Russian regions overnight. Six drones were downed in Voronezh where, according to the region's Governor Aleksandr Gusev, falling debris started a blaze just six days after remnants of another intercepted drone triggered an earlier fire. Kyiv's military claimed responsibility for attacking an aviation manufacturing plant in Russia's Smolensk region where "combat aircraft[s] are being modernised and manufactured", as well as an attack on Voronezh which resulted in a fuel depot fire.

Russia and Ukraine have continued to exchange barrages of air attacks, despite Donald Trump having said he would end the war within 24 hours of becoming US president. While Trump was inaugurated on Monday afternoon, neither Kyiv nor Moscow have shown signs of de-escalating the drone and missile strikes they have been launching against one another in recent months. Both launched barrages overnight on Tuesday. Russia said it downed 55 Ukrainian drones, more than half of which were intercepted over regions on the border. Kyiv said it struck an oil depot near the town of Liski in the Voronezh region, sparking a blaze at the facility for the second time in less than a week.

Three people have been killed in Kyiv overnight, according to the head of the Ukrainian military. Explosions were heard across the Ukrainian capital as air raid sirens sounded and air defence crews responded to a Russian ballistic missile attack. Ukraine has continued its drone attacks against Russian oil infrastructure, hitting depots in the Tula and Kaluga regions south of Moscow overnight. Images said to depict the burning depots have been shared online as Kaluga's regional governor claimed several drones had been shot down. The governors of Russia's Bryansk and Smolensk regions reported that air defence units had shot down a total of 14 Ukrainian drones with no reports of casualties.

A Ukrainian drone attack targeting an armoury has caused a giant fireball, leading to a partial evacuation in western Russia. The attack, reported early on Wednesday, targeted a large arsenal close to the town of Toropets, some 400km (250 miles) northwest of Moscow in the Tver region. It illustrates Ukraine's continued effort to show it can strike at targets deep inside Russia. The drone attack caused an "extremely powerful detonation" and destroyed a large warehouse of the Main Missile and Artillery Directorate of the Russian Ministry of Defence and sparked a fire 6km (3.7 miles) wide, an unnamed source from the Ukrainian security services said. "The warehouse contained missiles intended for Iskander tactical missile systems, Tochka-U tactical missile systems, guided aerial bombs and artillery ammunition," the source told news wires.

This thesis is a corpus-based, quantitative, and typological analysis of the functions of Early Slavic participle constructions and their finite competitors ($jegda$-'when'-clauses). The first part leverages detailed linguistic annotation on Early Slavic corpora at the morphosyntactic, dependency, information-structural, and lexical levels to obtain indirect evidence for different potential functions of participle clauses and their main finite competitor and understand the roles of compositionality and default discourse reasoning as explanations for the distribution of participle constructions and $jegda$-clauses in the corpus. The second part uses massively parallel data to analyze typological variation in how languages express the semantic space of English $when$, whose scope encompasses that of Early Slavic participle constructions and $jegda$-clauses. Probabilistic semantic maps are generated and statistical methods (including Kriging, Gaussian Mixture Modelling, precision and recall analysis) are used to induce cross-linguistically salient dimensions from the parallel corpus and to study conceptual variation within the semantic space of the hypothetical concept WHEN.