We present Distributional RewArds for Generative OptimizatioN (DRAGON), a versatile framework for fine-tuning media generation models towards a desired outcome. Compared with traditional reinforcement learning with human feedback (RLHF) or pairwise preference approaches such as direct preference optimization (DPO), DRAGON is more flexible. It can optimize reward functions that evaluate either individual examples or distributions of them, making it compatible with a broad spectrum of instance-wise, instance-to-distribution, and distribution-to-distribution rewards. Leveraging this versatility, we construct novel reward functions by selecting an encoder and a set of reference examples to create an exemplar distribution. When cross-modal encoders such as CLAP are used, the reference may be of a different modality (text versus audio). Then, DRAGON gathers online and on-policy generations, scores them with the reward function to construct a positive demonstration set and a negative set, and leverages the contrast between the two finite sets to approximate distributional reward optimization. For evaluation, we fine-tune an audio-domain text-to-music diffusion model with 20 reward functions, including a custom music aesthetics model, CLAP score, Vendi diversity, and Frechet audio distance (FAD). We further compare instance-wise (per-song) and full-dataset FAD settings while ablating multiple FAD encoders and reference sets. Over all 20 target rewards, DRAGON achieves an 81.45% average win rate. Moreover, reward functions based on exemplar sets enhance generations and are comparable to model-based rewards. With an appropriate exemplar set, DRAGON achieves a 60.95% human-voted music quality win rate without training on human preference annotations. DRAGON is a new approach to designing and optimizing reward functions for improving human-perceived quality. Demos at https://ml-dragon.github.io/web

We introduce TAPIP3D, a novel approach for long-term 3D point tracking in monocular RGB and RGB-D videos. TAPIP3D represents videos as camera-stabilized spatio-temporal feature clouds, leveraging depth and camera motion information to lift 2D video features into a 3D world space where camera movement is effectively canceled out. Within this stabilized 3D representation, TAPIP3D iteratively refines multi-frame motion estimates, enabling robust point tracking over long time horizons. To handle the irregular structure of 3D point distributions, we propose a 3D Neighborhood-to-Neighborhood (N2N) attention mechanism - a 3D-aware contextualization strategy that builds informative, spatially coherent feature neighborhoods to support precise trajectory estimation. Our 3D-centric formulation significantly improves performance over existing 3D point tracking methods and even surpasses state-of-the-art 2D pixel trackers in accuracy when reliable depth is available. The model supports inference in both camera-centric (unstabilized) and world-centric (stabilized) coordinates, with experiments showing that compensating for camera motion leads to substantial gains in tracking robustness. By replacing the conventional 2D square correlation windows used in prior 2D and 3D trackers with a spatially grounded 3D attention mechanism, TAPIP3D achieves strong and consistent results across multiple 3D point tracking benchmarks. Project Page: https://tapip3d.github.io

This research examines the potential of datasets generated by Large Language Models (LLMs) to support Natural Language Processing (NLP) tasks, aiming to overcome challenges related to data acquisition and privacy concerns associated with real-world data. Focusing on negative valence text, a critical component of sentiment analysis, we explore the use of LLM-generated synthetic news headlines as an alternative to real-world data. A specialized corpus of negative news headlines was created using tailored prompts to capture diverse negative sentiments across various societal domains. The synthetic headlines were validated by expert review and further analyzed in embedding space to assess their alignment with real-world negative news in terms of content, tone, length, and style. Key metrics such as correlation with real headlines, perplexity, coherence, and realism were evaluated. The synthetic dataset was benchmarked against two sets of real news headlines using evaluations including the Comparative Perplexity Test, Comparative Readability Test, Comparative POS Profiling, BERTScore, and Comparative Semantic Similarity. Results show the generated headlines match real headlines with the only marked divergence being in the proper noun score of the POS profile test.

Miss Israel Melanie Shiraz said she received death and rape threats after controversial video appears to show her glaring at Palestinian contestant during Miss Universe pageant in Thailand.

In 1996 Nasa and the White House made the explosive announcement that the rock contained traces of Martian bugs. The meteorite, catalogued as Allen Hills (ALH) 84001, crashed onto the frozen wastes of Antarctica 13,000 years ago and was recovered in 1984. Photographs were released showing elongated segmented objects that appeared strikingly lifelike.

A new congressional report warns China's military buildup has reached a war footing with 350 new missile silos and 20% nuclear expansion, threatening U.S. deterrence.

Under Secretary Emil Michael announces War Department's shift to six Critical Technology Areas including AI, quantum computing and hypersonics to accelerate military innovation.

What is the chance your plane will be hit by space debris? The risk of flights being hit by space junk is still small, but it's growing. About three pieces of old space equipment --used rockets and defunct satellites--fall into Earth's atmosphere every day, according to estimates by the European Space Agency. By the mid-2030s, there may be dozens thanks to the rise of megaconstellations in orbit. So far, space debris hasn't injured anybody--in the air or on the ground. But multiple close calls have been reported in recent years.

Barron Trump's mystery words to Joe Biden after his father's fierce inauguration speech are finally revealed Republican representative blasts Trump's Epstein investigation as a'smokescreen' while survivors beg Congress to finally reveal the hidden files: Live updates This is the simple weight loss trick I'd recommend to any woman over 50 who wants to burn calories and tone up - without working out or eating less: KERRY POTTER She runs the anonymous real-life Gossip Girl account outing Hollywood scandals now we expose HER identity and the secret life she's desperate to hide Keith Urban breaks his silence following split with Nicole Kidman - after admitting he's been'completely lonely and miserable' Olivia Nuzzi says Robert F. Kennedy Jr. didn't have a'brain worm' after all I was blackmailed and forced to do the unthinkable. DEAR JANE, how do I hide it from my wife? Trump turns to Epstein's lawyer to prove he has'nothing to hide' as he orders GOP to vote on releasing ALL documents to avert MAGA mutiny Terrifying rise of'taboo cancer': Doctors reveal subtle signs ALL women must know... the most common cause... and a game-changer shot that could save your life Jeff Bezos's ex MacKenzie Scott contributes more than $700MILLION to'historically black colleges' So many single men are taking this new drug cocktail before dates. The results in the bedroom are startling... as I discovered during one marathon session: JANA HOCKING I felt so ill I thought I was dying... but it was a gut condition doctors often wrongly dismiss as IBS: It's so common and there's misinformation about how to treat it, says Nicola... but this is what really works Boy, 9, accused of raping and brutally attacking girl, 5, is allowed home with ankle monitor... despite victim's mom pleading with judge Meghan's ex-husband's reaction to finding out she was dating Prince Harry is revealed by his pal Bethenny Frankel Trump wades into the most explosive debate in right wing media: 'People must decide' My Montecito mole tells me why Me-Me-Meghan'threw a fit' after Kris Jenner's birthday party... this Kardashian drama just won't go away: KENNEDY If I had to start over, here's how I'd make millions again! KEVIN O'LEARY reveals best investments, the career with soaring salaries and worst mistake he made Nigerian gunmen abduct'dozens' of girls from boarding school after killing deputy head teacher in chilling echo of Chibok kidnappings Conor McGregor's friend Dillon Danis slapped with LIFETIME ban by UFC chief Dana White after being involved in ringside brawl READ MORE: Here's what happens in football fans' brains when their team loses Scientists have unveiled the most detailed map of the brain ever created.

Apple's Adaptive Power feature in iOS 26 automatically learns your iPhone usage patterns and adjusts performance to extend battery life without manual input.