Novel categories names:['High_Jump', 'Front_Crawl', 'Pole_V ault', 'Hammer_Throw', All experiments are conducted under the 16-shot setting. An incremental bayesian approach tested on 101 object categories. Conditional prompt learning for vision-language models.

To bridge this gap, we introduce the BABILong benchmark, designed to test language models' ability to reason across facts distributed in extremely

Science Ask Us Anything What is human composting? A new'Ask Us Anything' podcast episode digs into how human bodies can be turned into nutrient-rich soil. Breakthroughs, discoveries, and DIY tips sent every weekday. Do you know what want to have happen to your body after you die? Do you want to be cremated, buried, or given an epic Viking burial? While it may seem macabre, it's important to think about so our loved ones don't have to while their in the throes of grief. On this episode of, editors Sarah Durn and Annie Colbert dig into a novel way people are choosing to handle their bodies after they die: human composting.

Adapting language models to new tasks through continued pretraining faces a fundamental trade-off: models must learn new capabilities while avoiding catastrophic forgetting of existing knowledge. While prior work has studied synthetic data generation techniques, the optimal replay ratios for balancing task performance and knowledge retention under computational constraints remain poorly understood. We present a comprehensive empirical study investigating the interplay between replay ratio configuration and computational budget when adapting language models to new tasks. Using the bAbI reasoning tasks as our target objective, we apply synthetic data generation and systematically evaluate different total token budgets and replay ratio configurations. We analyze their effects on both task mastery and general knowledge retention. Our experiments reveal an optimal configuration that balances task-specific performance with general knowledge retention. Based on our findings, we provide empirically-grounded guidelines for selecting replay ratios based on computational budget, enabling practitioners to achieve strong task adaptation with significantly reduced training costs.

To bridge this gap, we introduce the BABILong benchmark, designed to test language models' ability to reason across facts distributed in extremely

Your local beetles and chipmunks will thank you for backing away from the rake. Breakthroughs, discoveries, and DIY tips sent every weekday. There's the shift to cooler weather and the opportunity to pull out your favorite hoodie and enjoy the colorful symphony of fall leaves. However, many do not look forward to raking leaves. Believe it or not, you do have a choice when it comes to whether or not to rake leaves.

While you don't always have to spend big to get the best tech, when it comes to robot mowers, the pricey Husqvarna Automower 450X EPOS proved to be a cut above the competition (technically, I tested the Husqvarna 410XE Nera (9/10, WIRED Recommends), which is the closest model in the UK and Europe). It employs Husqvarna's EPOS (Exact Positioning Operating System) tech and relies on a satellite connection to navigate your chosen virtual boundaries (no wire required). But you do need to install the receiver in an area with an open line of sight to the sky and, ideally, no tall trees or buildings nearby. Setup involves remote control driving the Husqvarna around your garden to map the virtual boundaries. You can have multiple separate areas and potentially cover an area up to 2.5 acres. I marked out my front and back lawns and simply carried the mower between them.

Novel categories names:['High_Jump', 'Front_Crawl', 'Pole_V ault', 'Hammer_Throw', All experiments are conducted under the 16-shot setting. An incremental bayesian approach tested on 101 object categories. Conditional prompt learning for vision-language models.

Urban greenery is often linked to better health, yet findings from past research have been inconsistent. One reason is that official greenery metrics measure the amount or nearness of greenery but ignore how often people actually may potentially see or use it in daily life. To address this gap, we introduced a new classification that separates on-road greenery, which people see while walking through streets, from off-road greenery, which requires planned visits. We did so by combining aerial imagery of Greater London and greenery data from OpenStreetMap with quantified greenery from over 100,000 Google Street View images and accessibility estimates based on 160,000 road segments. We linked these measures to 7.45 billion medical prescriptions issued by the National Health Service and processed through our methodology. These prescriptions cover five conditions: diabetes, hypertension, asthma, depression, and anxiety, as well as opioid use. As hypothesized, we found that green on-road was more strongly linked to better health than four widely used official measures. For example, hypertension prescriptions dropped by 3.68% in wards with on-road greenery above the median citywide level compared to those below it. If all below-median wards reached the citywide median in on-road greenery, prescription costs could fall by up to £3.15 million each year. These results suggest that greenery seen in daily life may be more relevant than public yet secluded greenery, and that official metrics commonly used in the literature have important limitations.