In order to be deployed safely, Large Language Models (LLMs) must be capable of dynamically adapting their behavior based on their level of knowledge and uncertainty associated with specific topics. This adaptive behavior, which we refer to as self-restraint, is non-trivial to teach since it depends on the internal knowledge of an LLM. By default, LLMs are trained to maximize the next token likelihood, which does not teach the model to modulate its answer based on its level of uncertainty. In order to learn self-restraint, we devise a utility function that can encourage the model to produce responses only when it is confident in them. This utility function can be used to score generation of different length and abstention. To optimize this function, we introduce ReSearch, a process of "self-reflection" consisting of iterative self-prompting and self-evaluation. We use the ReSearch algorithm to generate synthetic data on which we finetune our models. Compared to their original versions, our resulting models generate fewer \emph{hallucinations} overall at no additional inference cost, for both known and unknown topics, as the model learns to selectively restrain itself. In addition, our method elegantly incorporates the ability to abstain by augmenting the samples generated by the model during the search procedure with an answer expressing abstention.

This work starts with the intention of using mathematics to understand the intriguing vulnerability observed by ~\citet{szegedy2013} within artificial neural networks. Along the way, we will develop some novel tools with applications far outside of just the adversarial domain. We will do this while developing a rigorous mathematical framework to examine this problem. Our goal is to build out theory which can support increasingly sophisticated conjecture about adversarial attacks with a particular focus on the so called ``Dimpled Manifold Hypothesis'' by ~\citet{shamir2021dimpled}. Chapter one will cover the history and architecture of neural network architectures. Chapter two is focused on the background of adversarial vulnerability. Starting from the seminal paper by ~\citet{szegedy2013} we will develop the theory of adversarial perturbation and attack. Chapter three will build a theory of persistence that is related to Ricci Curvature, which can be used to measure properties of decision boundaries. We will use this foundation to make a conjecture relating adversarial attacks. Chapters four and five represent a sudden and wonderful digression that examines an intriguing related body of theory for spatial analysis of neural networks as approximations of kernel machines and becomes a novel theory for representing neural networks with bilinear maps. These heavily mathematical chapters will set up a framework and begin exploring applications of what may become a very important theoretical foundation for analyzing neural network learning with spatial and geometric information. We will conclude by setting up our new methods to address the conjecture from chapter 3 in continuing research.

Chinese and Russian companies are developing an attack drone similar to an Iranian model deployed in Ukraine, European officials familiar with the matter said, a sign that Beijing may be edging closer to providing the sort of lethal aid that western officials have warned against. The companies held talks in 2023 about collaborating to replicate Iran's Shahed drone, and started developing and testing a version this year in preparation for shipment to Russia, said the officials, who asked not to be identified to discuss private information. The Chinese drones have yet to be used in Ukraine, they said. Providing Russia a Shahed-like attack drone would mark a deepening of Beijing's support for Russia despite repeated warnings from the U.S. and its allies. Chinese President Xi Jinping has sought to portray China as neutral in the conflict in Ukraine even as western officials say it's provided components and other support for Russian President Vladimir Putin's forces.

A three-mile stretch of Interstate 94 in Michigan will be converted into America's first smart highway. Axios reports that the Alphabet-backed startup Cavnue has started constructing the smart highway as part of a new pilot project that could spur other construction projects across the country. Two more highways are in the works for Austin, Texas and somewhere else in the Southwest, according to Cavnue's website. The new smart road is big, long car tracking system for Michigan's Department of Transportation (MDOT) and for drivers on the highway. The smart highway is designed to send data like traffic updates, weather conditions, driving conditions and stranded vehicles in the hopes of relieving traffic congestion, preventing accidents and providing efficient responses to roadway emergencies.

NATO Secretary General Jens Stoltenberg to discuss how NATO members have bolstered their spending, the latest on the war in Ukraine and how the alliance can counter aggression from countries like Russia and China. Explosions reverberated across the pre-dawn sky as Ukrainian air defenses fended off a Russian attack on this small city in western Ukraine, home to an important air base and a frequent target of Moscow's strikes. Hours after the assault, the tidy streets of Starokostiantyniv had returned to a semblance of normality. But the June 27 attack was a stark reminder of the challenges Kyiv faces as it rebuilds its depleted air force and deploys the first U.S.-designed F-16s - fighter aircraft that Russia will be determined to ground or destroy. The first planes are expected to arrive this month, and Ukraine hopes they will boost forces struggling to repel a Russian onslaught along the front line, which includes devastating glide bombs that F-16s could potentially disrupt.

Barring an asteroid strike, Keir Starmer is going to be the UK prime minister in three days. Given the lead in polling, I'd probably bet on him over an asteroid, too. Labour will come into government with a broken state, a flatlining economy and no money. A thin manifesto and enormous parliamentary majority means the party will almost certainly end up stretching further afield for ideas about how to deal with that trilemma from hell. So let's try and offer some.

The Defense Ministry unveiled its first basic policy on the use of artificial intelligence on Tuesday, as Japan looks to stave off a manpower shortage and keep pace with China and the United States on the technology's military applications. The focus on AI comes as the Self-Defense Forces grapple with concerns about recruitment and its abilities to harness the power of new technologies. "In our country, where the population is rapidly declining and aging, it is essential to utilize personnel more efficiently than ever before," Defense Minister Minoru Kihara told a news conference after the policy's release. "We believe that AI has the potential to be one of the technologies that can overcome these challenges."

Whether they are called manifestos or contracts, the documents published by political parties ahead of an election are rather less substantial than their many pages would suggest. They are full of best-case scenarios, undetailed proposals and dubious costings, and it is hard to picture the impact each party would have on the UK if they followed through with their pitches. So I've been feeding party literature into the political strategy video game Democracy 4, to see how these policies might play out. The results were … well, you'll see. Democracy 4 lets you play out your political fantasies (or nightmares) to see the impact of your choices and, ultimately, if you can get re-elected.

Mae Sot, Thailand – Once again, the attack came from the sky. The Kachin resistance fighters barely heard the sound of the propellers as the Myanmar military's two drones released their payload above their heads in northern Kachin State in late April. "I fell down to the ground when the bombs dropped," Aung Nge, a fighter with the Kachin People's Defense Force (PDF), told Al Jazeera from an undisclosed location. I was awake the whole time." The drone attack seriously injured three men who were holed up close to the front line in Kachin State where battles with the armed forces have been escalating since October last year. In critical condition, field medics sent the men to a hidden hospital deep in the jungle where they could be treated by professional doctors. Within a day of receiving treatment, however, one of the soldiers started to show symptoms the doctors could not understand and his condition began to deteriorate rapidly. Another man from the Kachin Independence Army (KIA), who had been injured in a separate drone strike days after the first attack and appeared to be on the mend with no signs of infection, also took a turn for the worse and died in his sleep. Aung Nge, meanwhile, was about to endure ghastly infections that would spread across his entire body. Doctors told Al Jazeera that the men experienced rapid onset necrosis, an effect not normally seen in a blast wound. Necrosis causes the deterioration of most or all of the cells in an organ or tissue due to disease or the failure of the blood supply. While necrosis can be caused by sepsis, which appears rapidly and is usually accompanied by a fever, doctors said they could find no physiological reason for the rapid deterioration in their patients. Toxic substances can also trigger such reactions, they said. "In close examination of the wounds, they are rapidly necrotising, easily decomposed and not associated with metallic foreign bodies," Dr Soe Min, the veteran trauma doctor who treated the suspicious cases, told Al Jazeera. He has been treating combat-related cases since January 2022 and has seen and treated hundreds of blast injuries. These cases were different, he said. "After two days, all the wounds became blackish in colour with foul-smelling discharge.

Documents are visually rich structures that convey information through text, as well as tables, figures, page layouts, or fonts. While modern document retrieval systems exhibit strong performance on query-to-text matching, they struggle to exploit visual cues efficiently, hindering their performance on practical document retrieval applications such as Retrieval Augmented Generation. To benchmark current systems on visually rich document retrieval, we introduce the Visual Document Retrieval Benchmark ViDoRe, composed of various page-level retrieving tasks spanning multiple domains, languages, and settings. The inherent shortcomings Figure 1: For each term in a user query, ColPali identifies of modern systems motivate the introduction the most relevant document image patches (highlighted of a new retrieval model architecture, zones) and computes a query-to-page matching ColPali, which leverages the document score. We can then swiftly retrieve the most relevant understanding capabilities of recent Vision Language documents from a large pre-indexed corpus. Models to produce high-quality contextualized embeddings solely from images of document pages.