A comparison of a T-shirt as sold by Lonely Kids Club and Temu. The business owner says AI may have been used to scrape the content of his site and replicate the designs. A comparison of a T-shirt as sold by Lonely Kids Club and Temu. The business owner says AI may have been used to scrape the content of his site and replicate the designs. 'Brutal': thousands of T-shirt designs stolen and listed on Temu, Sydney label claims After 15 years running a small business making T-shirts, Warwick Levy says it was "brutal" when he first discovered an identical design for sale on Temu.

Follow this author to personalize your feed and get instant alerts. Follow Go to your personalized feed WHY FOLLOW? Smart Alerts: Get notified about major news as it happens. Carlin is a contributor for TIME. Growing up in São Paulo, it was so hot that "wearing black was not even an option," says the former fashion director turned shoe designer, 46, who has called New York City home for half her life.

The Watch World Went Crazy This Week. The main action took place at Geneva Watch Days, but others dialed in remotely to make sure it wasn't just a Swiss party. While Watches and Wonders every April is undoubtedly the watch world's main event of the year, Geneva Watch Days--which inauspiciously launched in 2020, the year Covid was declared a pandemic --is now establishing itself as a serious follow-up. Big brands can hold back key releases and gain valuable space to shout about new pieces away from the horological hubbub of W&W. A second bite of the marketing apple in the latter half of the year seems like a good idea, as Swiss watch exports declined again in 2025 after a drop in 2024.

Instruction tuning is essential for Large Language Models (LLMs) to effectively follow user instructions. To improve training efficiency and reduce data redundancy, recent works use LLM-based scoring functions, e.g., Instruction-Following Difficulty (IFD), to select high-quality instruction-tuning data with scores above a threshold. While these data selection methods often lead to models that can match or even exceed the performance of models trained on the full datasets, we identify two key limitations: (i) they assess quality at the sample level, ignoring token-level informativeness; and (ii) they overlook the robustness of the scoring method, often selecting a sample due to superficial lexical features instead of its true quality. In this work, we propose Token-Selective HIeRarchical Data Selection for Instruction Tuning (T-SHIRT), a novel data selection framework that introduces a new scoring method to include only informative tokens in quality evaluation and also promotes robust and reliable samples whose neighbors also show high quality with less local inconsistencies. We demonstrate that models instruction-tuned on a curated dataset (only 5% of the original size) using T-SHIRT can outperform those trained on the entire large-scale dataset by up to 5.48 points on average across eight benchmarks. Across various LLMs and training set scales, our method consistently surpasses existing state-of-the-art data selection techniques, while also remaining both costeffective and highly efficient. For instance, by using GPT-2 for score computation, we are able to process a dataset of 52k samples in 40 minutes on a single GPU.

Science This shoe is made entirely from mushroom'brains' Fungi footwear may offer a solution. More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. Two types of fungi were used to create the boot. Breakthroughs, discoveries, and DIY tips sent six days a week. The fashion industry is ecologically tacky, to put it mildly.

A startup is transforming polluted air into apparel. At least 15 major brands, including H&M and Walmart, are testing new technology for carbon neutral clothing. Breakthroughs, discoveries, and DIY tips sent six days a week. It might not seem like it when you nonchalantly click a Buy Now button while online shopping, but that new t-shirt is part of a complex global web of commerce taking a toll on the environment . Consulting giant McKinsey estimates that the fashion industry alone accounts for as much as 4 percent of total global climate emissions.

Watch Party: The Best TAG in Years, a '60s Sensation, and Omega Goes All White It's LVMH Watch Week, so here's WIRED's pick of the timepieces that made their debut--plus one notable gatecrasher. The watch world is readying itself for the slew of new releases from the likes of Patek Philippe and Rolex when Watches and Wonders descends on Geneva in April. But this week, the watchmaker Omega and the luxury conglomerate LVMH both spotted a window of opportunity to get pieces out ahead of the annual gathering. Since 2020, LVMH has been kicking off each new year by serving up watches from its stable of brands, including Zenith, TAG Heuer, Hublot, and Louis Vuitton. Meanwhile, Omega--muscling in on LVMH's party somewhat--is leaning into its connection to next month's Winter Olympics in Italy, where it will once again serve as the event's official timekeeper.

The team found the deceased with scallop shelves partly covering the mouth. Breakthroughs, discoveries, and DIY tips sent every weekday. It's been a good year for metal detectorists. And now there's yet another discovery to add to the list. Archaeologists in Norway have excavated a Viking Age grave of an individual bedecked in costume and jewelry, as reported by, an outlet that publishes research news from the Norwegian University of Science and Technology and the Scandinavian research group SINTEF.

Italian luxury fashion house Valentino is facing criticism after posting disturbing adverts made using artificial intelligence (AI) for one of its luxury handbags online. The brand announced a collaboration with digital artists as part of what it dubbed a digital creative project promoting its new DeVain handbag. But an AI-generated advert it posted on Instagram has been met with intense criticism from fans, who called the visuals - and use of AI - sloppy and sad. The BBC has approached Valentino for comment. The Instagram post promoting the handbag, which has a label to say it was made using AI, shows a surreal collage of models spliced between Valentino logos and its DeVain bag.

Instruction tuning is essential for Large Language Models (LLMs) to effectively follow user instructions. To improve training efficiency and reduce data redundancy, recent works use LLM-based scoring functions, e.g., Instruction-Following Difficulty (IFD), to select high-quality instruction-tuning data with scores above a threshold. While these data selection methods often lead to models that can match or even exceed the performance of models trained on the full datasets, we identify two key limitations: (i) they assess quality at the sample level, ignoring token-level informativeness; and (ii) they overlook the robustness of the scoring method, often selecting a sample due to superficial lexical features instead of its true quality. In this work, we propose Token-Selective HIeRarchical Data Selection for Instruction Tuning (T-SHIRT), a novel data selection framework that introduces a new scoring method to include only informative tokens in quality evaluation and also promotes robust and reliable samples whose neighbors also show high quality with less local inconsistencies. We demonstrate that models instruction-tuned on a curated dataset (only 5% of the original size) using T-SHIRT can outperform those trained on the entire large-scale dataset by up to 5.48 points on average across eight benchmarks. Across various LLMs and training set scales, our method consistently surpasses existing state-of-the-art data selection techniques, while also remaining both cost-effective and highly efficient. For instance, by using GPT-2 for score computation, we are able to process a dataset of 52k samples in 40 minutes on a single GPU. Our code is available at https://github.com/Dynamite321/T-SHIRT.