A couple brought military explosive devices into a Los Angeles Police Department station Saturday afternoon in an attempt to dispose of them, spurring officials to temporarily evacuate the Pacoima station and nearby homes. The incident came less than two weeks after an explosion killed three Los Angeles County sheriff's detectives -- the deadliest incident for the Sheriff's Department in more than 150 years. The three agency veterans who were killed were Dets. On Saturday, according to the LAPD, two people came into the Pacoima station at 2:30 p.m. and said they had been cleaning out the home of a family member who recently died when they found what they believed were explosives. The department's bomb squad used a robot to take images of the plastic box the couple had brought, which had "several military ordnances inside."

The Israeli army is weaponising Chinese-made drones to kill Palestinian civilians in the Gaza Strip, according to an investigation by the Israeli publications 972 Magazine and the Local Call. The drones are operated manually by soldiers on the ground to bomb civilians – including children – to force them out of their homes or prevent them from returning to areas where Palestinians have been expelled, the outlets reported on Sunday. The publications interviewed seven soldiers and officers to produce their findings, they said. The report was published as criticism of Israel's plan to set up an internment camp in southern Gaza is growing. Former Israeli Prime Ministers Yair Lapid and Ehud Olmert said it would amount to a "concentration camp" if Palestinians there are not allowed to leave. "The weaponisation of civilian drones to kill and dispossess Palestinians is the latest revelation of the cruelties normalised in Gaza and further evidence of how Israel is trying to forcibly transfer the population to the south of the Strip," Al Jazeera's Nour Odeh said, reporting from Amman, Jordan, because Israel has banned Al Jazeera from reporting from Israel and the occupied West Bank.

Although value-aligned language models (LMs) appear unbiased in explicit bias evaluations, they often exhibit stereotypes in implicit word association tasks, raising concerns about their fair usage. We investigate the mechanisms behind this discrepancy and find that alignment surprisingly amplifies implicit bias in model outputs. Specifically, we show that aligned LMs, unlike their unaligned counterparts, overlook racial concepts in early internal representations when the context is ambiguous. Not representing race likely fails to activate safety guardrails, leading to unintended biases. Inspired by this insight, we propose a new bias mitigation strategy that works by incentivizing the representation of racial concepts in the early model layers. In contrast to conventional mitigation methods of machine unlearning, our interventions find that steering the model to be more aware of racial concepts effectively mitigates implicit bias. Similar to race blindness in humans, ignoring racial nuances can inadvertently perpetuate subtle biases in LMs.

The gaming industry has experienced substantial growth, but cheating in online games poses a significant threat to the integrity of the gaming experience. Cheating, particularly in first-person shooter (FPS) games, can lead to substantial losses for the game industry. Existing anti-cheat solutions have limitations, such as client-side hardware constraints, security risks, server-side unreliable methods, and both-sides suffer from a lack of comprehensive real-world datasets. To address these limitations, the paper proposes HAWK, a server-side FPS anti-cheat framework for the popular game CS:GO. HAWK utilizes machine learning techniques to mimic human experts' identification process, leverages novel multi-view features, and it is equipped with a well-defined workflow. The authors evaluate HAWK with the first large and real-world datasets containing multiple cheat types and cheating sophistication, and it exhibits promising efficiency and acceptable overheads, shorter ban times compared to the in-use anti-cheat, a significant reduction in manual labor, and the ability to capture cheaters who evaded official inspections.

The river in the small city of Penza suddenly turned green, residents said. The Ukrainian infantryman, call sign "Ray", said he quickly pulled on his gas mask after a Russian drone flying above his trench on the eastern front dropped a tear gas grenade. "It's like pepper spray, it makes your eyes tear up. It's not lethal, but it disturbs and knocks you out. It makes it very difficult to carry out your duties once you've inhaled it," he told Reuters of the attack he said he experienced in January.

Self-supervised representation learning on text-attributed graphs, which aims to create expressive and generalizable representations for various downstream tasks, has received increasing research attention lately. However, existing methods either struggle to capture the full extent of structural context information or rely on task-specific training labels, which largely hampers their effectiveness and generalizability in practice. To solve the problem of self-supervised representation learning on text-attributed graphs, we develop a novel Graph-Centric Language model -- GRENADE. Specifically, GRENADE exploits the synergistic effect of both pre-trained language model and graph neural network by optimizing with two specialized self-supervised learning algorithms: graph-centric contrastive learning and graph-centric knowledge alignment. The proposed graph-centric self-supervised learning algorithms effectively help GRENADE to capture informative textual semantics as well as structural context information on text-attributed graphs. Through extensive experiments, GRENADE shows its superiority over state-of-the-art methods. Implementation is available at \url{https://github.com/bigheiniu/GRENADE}.

SLOVIANSK, Ukraine – An array of mostly unremarkable items stretched across two wooden tables on the far side of a cramped workshop in eastern Ukraine: double-sided tape, gloves, Allen wrenches, a soldering iron, 3D-printed plastic, ball bearings, a digital scale. Next to them was a German DM51 fragmentation grenade. They were all important ingredients for Ukrainian troops trying to piece together a puzzle: How do you create a grenade that weighs next to nothing but can be dropped from a drone and destroy a roughly 40-ton Russian tank? It's money," said Graf, a stout, bearded Ukrainian soldier in charge of his unit's drone team. "And if you have a drone for $3,000 (¥396,326) and a grenade for $200, and you destroy a tank that costs $3 million, it's very interesting."

Scientists from China's Zhejiang University have unveiled a drone swarm capable of navigating through a dense bamboo forest without human guidance. The group of 10 palm-sized drones communicate with one another to stay in formation, sharing data collected by on-board depth-sensing cameras to map their surroundings. This method means that if the path in front of one drone is blocked, it can use information collected by its neighbors to plot a new route. The researchers note that this technique can also be used by the swarm to track a human walking through the same environment. If one drone loses sight of the target, others are able to pick up the trail.

On Monday morning, Russian President Vladimir Putin announced an assassination attempt targeting Russian journalists had been foiled. In a sting operation, the FSB, Russia's domestic security service, had arrested the would-be neo-Nazi assassins, he said. Among the arsenal apparently seized by the FSB were Molotov cocktails, a grenade, several pistols and a sawed-off shotgun, as well as Nazi paraphernalia, a green wig and copies of three expansion packs to the video game "The Sims 3." Wait.

Computer Science in the 1960s to 80s spent a lot of effort making languages which were as powerful as possible. Nowadays we have to appreciate the reasons for picking not the most powerful solution but the least powerful. Expressing constraints, relationships and processing instructions in less powerful languages increases the flexibility with which information can be reused: the less powerful the language, the more you can do with the data stored in that language. I chose HTML not to be a programming language because I wanted different programs to do different things with it: present it differently, extract tables of contents, index it, and so on. Though the Rule of Least Power targeted programming languages themselves, rather than language features, I think the same ideas still apply.