Taylor, your album should be'Life of a Callgirl'. KENNEDY's appalled take on Swift's new record... and its ultra-vivid sex shout outs for Travis the Sasquatch The truth about Keith Urban's guitarist'other woman' Maggie Baugh revealed amid Nicole Kidman divorce How I look like this at 62. I've lost 5 stone fast, 20 years off my biological age and wear size 8... without weight-loss jabs. Hollywood A-listers pay me $50,000 to cure their drug addicted nepo-babies because they can't afford for these secrets to go public Shroud of Turin mystery deepens as surgeon spots hidden detail that points to Jesus' resurrection Trump dollar coin design released by Treasury... and it's inspired by an iconic political photo I'm no longer sleeping with my husband - and never will again, says MOLLY RYDDELL. I love him, but counted down the moments until he climaxed. Then I couldn't bear it any more and the truth spilled out... so many women feel the same Fans erupt at Taylor Swift's'dig' at Travis Kelce's ex Kayla Nicole in wild The Life of a Showgirl track Lori Loughlin's husband Mossimo Giannulli seen with mystery brunette in tiny skirt day after shock split Top plastic surgeons reveal secrets behind Taylor Swift's'changing' face: 'It is looking very full' I'm a woman with autism... here are the signs you might be masking, even from yourself Cake-faced 90s sitcom star looks unrecognizable as she ditches the heavy eyeshadow for an LA errand run can you guess who?

The Tokyo government revised its flood prevention guidelines to implement preventive measures for underground spaces that are considered to be at the highest risk of flooding, such as subway stations. The Tokyo Metropolitan Government has revised its flood prevention guidelines for underground spaces in the capital for the first time in 17 years amid abnormal weather conditions in recent years, with disaster plans updated to include artificial intelligence-based risk assessments. The guidelines were revised earlier this month to implement preventive measures for underground spaces that are considered to be at the highest risk of flooding, such as shopping malls and subway stations, as well as rooms in privately owned buildings and houses that are partially or fully below ground. The revision includes implementing AI technologies to process data on past damage and weather patterns as well as the respective area's topography data to calculate the risk of underground facilities flooding and the best route of evacuation. In a time of both misinformation and too much information, quality journalism is more crucial than ever.

Legal experts analyze the challenging defense strategy for Tyler Robinson, who allegedly shot Charlie Kirk at Utah Valley University, as prosecutors prepare evidence for trial.

Men stand at the site of heavily damaged residential buildings following a Russian air attack on the outskirts of Kyiv on Sunday. KYIV - A massive Russian drone and missile attack against Ukraine lasting 12 hours into Sunday killed at least four people in Kyiv, including a 12-year-old girl, Ukrainian authorities said. Neighboring Poland scrambled jets to secure its airspace in the wake of the barrage, after NATO accused Moscow of being behind a series of violations of the defense alliance's airspace. Diplomatic efforts to stop the war have faltered, and Russia has vowed to press on with the offensive that it launched in February 2022. In a time of both misinformation and too much information, quality journalism is more crucial than ever.

A mobile radar installation is positioned near the strait between Denmark and Sweden on Friday. COPENHAGEN - Denmark will ban all civilian drone flights across the country over the coming days to ensure security as Copenhagen hosts an EU summit gathering heads of government, the transport ministry said Sunday. Mysterious drone sightings across Denmark since Sept. 22 have prompted the closure of several airports, with Denmark hinting at possible Russian involvement, though Moscow denies the charge. Drones were observed over Danish military sites Saturday night for the second straight day, Denmark's army said on Sunday. In a time of both misinformation and too much information, quality journalism is more crucial than ever.

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The growing capabilities of large language models and multimodal systems have spurred interest in voice-first AI assistants, yet existing benchmarks are inadequate for evaluating the full range of these systems' capabilities. We introduce VoiceAssistant-Eval, a comprehensive benchmark designed to assess AI assistants across listening, speaking, and viewing. VoiceAssistant-Eval comprises 10,497 curated examples spanning 13 task categories. These tasks include natural sounds, music, and spoken dialogue for listening; multi-turn dialogue, role-play imitation, and various scenarios for speaking; and highly heterogeneous images for viewing. To demonstrate its utility, we evaluate 21 open-source models and GPT-4o-Audio, measuring the quality of the response content and speech, as well as their consistency. The results reveal three key findings: (1) proprietary models do not universally outperform open-source models; (2) most models excel at speaking tasks but lag in audio understanding; and (3) well-designed smaller models can rival much larger ones. Notably, the mid-sized Step-Audio-2-mini (7B) achieves more than double the listening accuracy of LLaMA-Omni2-32B-Bilingual. However, challenges remain: multimodal (audio plus visual) input and role-play voice imitation tasks are difficult for current models, and significant gaps persist in robustness and safety alignment. VoiceAssistant-Eval identifies these gaps and establishes a rigorous framework for evaluating and guiding the development of next-generation AI assistants. Code and data will be released at https://mathllm.github.io/VoiceAssistantEval/ .

Microscopy image enhancement plays a pivotal role in understanding the details of biological cells and materials at microscopic scales. In recent years, there has been a significant rise in the advancement of microscopy image enhancement, specifically with the help of deep learning methods. This survey paper aims to provide a snapshot of this rapidly growing state-of-the-art method, focusing on its evolution, applications, challenges, and future directions. The core discussions take place around the key domains of microscopy image enhancement of super-resolution, reconstruction, and denoising, with each domain explored in terms of its current trends and their practical utility of deep learning.

Enhancing the ability of Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) to interpret sheet music is a crucial step toward building AI musicians. However, current research lacks both evaluation benchmarks and training data for sheet music reasoning. Inspired by mathematics, where simple operations yield infinite verifiable problems, we introduce a novel approach that treats core music theory rules, such as those governing beats and intervals, as programmatic functions to systematically synthesize a vast and diverse corpus of sheet music reasoning problems. This approach allows us to introduce a data synthesis framework that generates verifiable sheet music questions in both textual and visual modalities, leading to the Synthetic Sheet Music Reasoning Benchmark (SSMR-Bench) and a complementary training set. Evaluation results on SSMR-Bench highlight the key role reasoning plays in interpreting sheet music, while also pointing out the ongoing challenges in understanding sheet music in a visual format. By leveraging synthetic data for RL VR, all models show significant improvements on the SSMR-Bench. Additionally, they also demonstrate considerable advancements on previously established human-crafted benchmarks, such as MusicTheoryBench and the music subset of MMMU. Finally, our results show that the enhanced reasoning ability can also facilitate music composition. "The sheet music is the language of musicians." Recent advancements in Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) have inspired researchers to explore the potential of developing AI musicians (Qu et al., 2025; Bradshaw & Colton, 2025; Wang et al., 2024). Given that sheet music is the universal language of musicians, the ability to read and interpret it is an essential step for AI musicians (Y uan et al., 2024; Wang et al., 2025). As illustrated in Figure 1, sheet music reasoning differs fundamentally from Music Knowledge QA (Li et al., 2024), which evaluates memorized knowledge, and from sheet music recognition (Chen et al., 2025a), which focuses on identifying notation from images.

In recent years, integrating multimodal understanding and generation into a single unified model has emerged as a promising paradigm. While this approach achieves strong results in text-to-image (T2I) generation, it still struggles with precise image editing. We attribute this limitation to an imbalanced division of responsibilities. The understanding module primarily functions as a translator that encodes user instructions into semantic conditions, while the generation module must simultaneously act as designer and painter, inferring the original layout, identifying the target editing region, and rendering the new content. This imbalance is counterintuitive because the understanding module is typically trained with several times more data on complex reasoning tasks than the generation module. To address this issue, we introduce Draw-In-Mind (DIM), a dataset comprising two complementary subsets: (i) DIM-T2I, containing 14M long-context image-text pairs to enhance complex instruction comprehension; and (ii) DIM-Edit, consisting of 233K chain-of-thought imaginations generated by GPT-4o, serving as explicit design blueprints for image edits. We connect a frozen Qwen2.5-VL-3B with a trainable SANA1.5-1.6B via a lightweight two-layer MLP, and train it on the proposed DIM dataset, resulting in DIM-4.6B-T2I/Edit. Despite its modest parameter scale, DIM-4.6B-Edit achieves SOTA or competitive performance on the ImgEdit and GEdit-Bench benchmarks, outperforming much larger models such as UniWorld-V1 and Step1X-Edit. These findings demonstrate that explicitly assigning the design responsibility to the understanding module provides significant benefits for image editing. Our dataset and models are available at https://github.com/showlab/DIM.