CollaFuse: Collaborative Diffusion Models
arXiv:2406.14429v3 Announce Type: replace-cross Abstract: In the landscape of generative artificial intelligence, diffusion-based models have emerged as a promising method for generating synthetic ima
Knowledge catalogue
arXiv:2406.14429v3 Announce Type: replace-cross Abstract: In the landscape of generative artificial intelligence, diffusion-based models have emerged as a promising method for generating synthetic ima
arXiv:2605.00222v1 Announce Type: new Abstract: Chemical reaction datasets such as USPTO suffer from substantial incompleteness, frequently missing byproducts, co-reactants, and stoichiometric coeffic
arXiv:2511.08156v2 Announce Type: replace Abstract: Land Use and Land Cover (LULC) mapping is a fundamental task in Earth Observation (EO). However, current LULC models are typically developed for a s
Pinecone announced the launch of its first serverless region in Asia, specifically in Singapore, expanding its vector database infrastructure to the Asia-Pacific market. This new cloud region enables
arXiv:2605.00080v1 Announce Type: cross Abstract: World models, which are predictive representations of how environments evolve under actions, have become a central component of robot learning. They s
Automated lint: 45 errors, 11 warnings, 3 info
The AI Engineer World's Fair is a conference event featuring talks on emerging AI research and engineering topics including autoresearch systems, advanced memory architectures, world models, tokenizat
arXiv:2602.12652v2 Announce Type: replace Abstract: Clouds are a common phenomenon that distorts optical satellite imagery, which poses a challenge for remote sensing. However, in the literature cloud
arXiv:2604.27906v1 Announce Type: new Abstract: Persistent AI memory is often reduced to a retrieval problem: store prior interactions as text, embed them, and ask the model to recover relevant contex
arXiv:2504.14602v2 Announce Type: replace-cross Abstract: The natural interaction and control performance of lower limb rehabilitation robots are closely linked to biomechanical information from vario
arXiv:2604.27032v1 Announce Type: cross Abstract: Large Language Models (LLMs) have become an integral part of many real-world workflows. However, LLMs consume a lot of energy, which becomes a large c
arXiv:2410.15272v3 Announce Type: replace-cross Abstract: Quantum annealers offer a promising hardware platform for solving combinatorial optimization problems, especially those formulated as Quadrati
arXiv:2604.27596v1 Announce Type: new Abstract: In open-world semi-supervised learning (OWSSL), a model learns from labeled data and unlabeled data containing both known and novel classes. In practica
Welcome to the second Cloud CISO Perspectives for April 2026. Today, Francis deSouza, COO Google Cloud and President, Security Products, explains why Google is multicloud and multi-AI, straight from N
arXiv:2604.26051v1 Announce Type: cross Abstract: The increasing number of satellites has improved the temporal resolution of Earth observation, making satellite-based flood mapping a promising approa
arXiv:2604.26504v1 Announce Type: new Abstract: Navigating quadruped robots in unstructured 3D environments poses significant challenges, requiring goal-directed motion, effective exploration to escap
arXiv:2604.25985v1 Announce Type: cross Abstract: General-relativistic magnetohydrodynamic (GR-MHD) simulations are essential for studying black hole accretion, relativistic jets, and magnetic reconne
arXiv:2502.14912v2 Announce Type: replace Abstract: We present a framework for generating universal semantic embeddings of chemical elements to advance materials inference and discovery. This framewor
arXiv:2604.26409v1 Announce Type: new Abstract: Sparse Autoencoders (SAEs) have demonstrated significant success in interpreting Large Language Models (LLMs) by decomposing dense representations into
Editor’s note: Want to keep up with the latest from Google Cloud? Check back here for a monthly recap of our latest updates, announcements, resources, events, learning opportunities, and more. We host
arXiv:2505.13766v5 Announce Type: replace-cross Abstract: Software Quality Assurance (SQA) is critical for delivering reliable, secure, and efficient software products. The Software Quality Assurance
arXiv:2604.24990v1 Announce Type: new Abstract: Stephen Wolfram proclaimed in his 2003 seminal work 'A New Kind Of Science' that simple recursive programs in the form of Cellular Automata (CA) are a p
arXiv:2604.25371v1 Announce Type: cross Abstract: Generating novel, biologically plausible three-dimensional morphological structures is a fundamental challenge in computational evolutionary biology,
arXiv:2506.09981v2 Announce Type: replace Abstract: How can we reliably simulate future driving scenarios under a wide range of ego driving behaviors? Recent driving world models, developed exclusivel
arXiv:2512.09923v2 Announce Type: replace Abstract: Radiance field representations have recently been explored in the latent space of VAEs that are commonly used by diffusion models. This direction of
arXiv:2604.25150v1 Announce Type: new Abstract: Overparameterization is central to the success of deep learning, yet the mechanisms by which it improves optimization remain incompletely understood. We
arXiv:2604.23049v1 Announce Type: new Abstract: AI agents are increasingly deployed to execute tasks and make decisions within agentic workflows, introducing new requirements for safe and controlled a
arXiv:2604.23622v1 Announce Type: new Abstract: In the hyperspectral image (HSI) classification task, each pixel is categorized into a specific land-cover category or material. Convolutional neural ne
arXiv:2604.23290v1 Announce Type: cross Abstract: Active learning algorithms automatically identify the most informative samples from large amounts of unlabeled data and tremendously reduce human anno
arXiv:2604.24428v1 Announce Type: cross Abstract: Electroencephalography (EEG) is highly susceptible to artifact contamination, such as electrooculographic (EOG) and electromyographic (EMG) interferen
arXiv:2309.00578v2 Announce Type: replace Abstract: In the context of unsupervised learning, Lloyd's algorithm is one of the most widely used clustering algorithms. It has inspired a plethora of work
arXiv:2604.23039v1 Announce Type: new Abstract: Physical human-robot interaction offers the potential to leverage human intelligence and robot physical capabilities to enable a range of exciting appli
arXiv:2604.23904v1 Announce Type: cross Abstract: Synthetic data offers a promising tool for privacy-preserving data release, augmentation, and simulation, but its use in causal inference requires pre
arXiv:2604.23435v1 Announce Type: cross Abstract: Radiographic grading of knee osteoarthritis (KOA) with the Kellgren-Lawrence (KL) system is limited by inter-reader variability and the opacity of cur
arXiv:2604.24053v1 Announce Type: new Abstract: Full 360^irc novel view synthesis under low-light conditions remains challenging. Insufficient illumination, noise amplification, and view-dependent pho
arXiv:2603.24143v2 Announce Type: replace Abstract: Neural operator learning directly constructs the mapping relationship from the equation parameter space to the solution space, enabling efficient di
arXiv:2604.24187v1 Announce Type: new Abstract: Wide Field-of-View (WFoV) reconstruction enhances 3D ultrasound imaging by providing valuable anatomical context for segmentation models and visualizati
arXiv:2604.06094v2 Announce Type: replace-cross Abstract: Convolutional neural networks owe much of their success to hard-coding translation equivariance. Quantum convolutional neural networks (QCNNs)
arXiv:2507.09245v2 Announce Type: replace Abstract: The Swa-bhasha Resource Hub provides a comprehensive collection of data resources and algorithms developed for Romanized Sinhala to Sinhala translit
arXiv:2604.23859v1 Announce Type: new Abstract: With spotforecast2-safe we present an integrated Compliance-by-Design approach to Python-based point forecasting of time series in safety-critical envir
arXiv:2604.24562v1 Announce Type: new Abstract: Driving in compliance with traffic laws and regulations is a basic requirement for human drivers, yet autonomous vehicles (AVs) can violate these requir
arXiv:2604.23706v1 Announce Type: new Abstract: Histologic assessment of ulcerative colitis (UC) activity is an important endpoint in clinical trials and routine care, but manual grading with indices
arXiv:2604.22045v1 Announce Type: cross Abstract: Feature attribution methods explain the predictions of deep neural networks by assigning importance scores to individual input features. However, most
arXiv:2604.22739v1 Announce Type: new Abstract: Social interactions dominate our perceptions of the world and shape our daily behavior by attaching social meaning to acts as simple and spontaneous as
arXiv:2604.22548v1 Announce Type: cross Abstract: Problem definition: Data-driven models in machine learning have enabled efficient management of production systems. However, a majority of machine lea
arXiv:2604.22439v1 Announce Type: new Abstract: We propose a neural regularization method that refines the noisy 3D semantic field produced by lifting multi-view inconsistent 2D features, in order to
arXiv:2602.07038v2 Announce Type: replace-cross Abstract: Key Information Extraction (KIE) from real-world documents remains challenging due to substantial variations in layout structures, visual qual
Automated lint: 44 errors, 10 warnings, 3 info
arXiv:2602.11871v2 Announce Type: replace Abstract: Large Language Models (LLMs) are a powerful tool for statistical text analysis, with derived sequences of next-token probability distributions offer
arXiv:2604.21830v1 Announce Type: new Abstract: We present GFlowState, a visual analytics system designed to illuminate the training process of Generative Flow Networks (GFlowNets or GFNs). GFlowNets
arXiv:2604.21905v1 Announce Type: new Abstract: Low-rank adaptation (LoRA) has emerged as the de facto standard for parameter-efficient fine-tuning (PEFT) of foundation models, enabling the adaptation
arXiv:2604.21825v1 Announce Type: cross Abstract: For continuous-time dynamical systems with reversible trajectories, the nowhere-vanishing eigenfunctions of the Koopman operator of the system form a
arXiv:2511.11439v2 Announce Type: replace-cross Abstract: Binary security has increasingly relied on deep learning to reason about malware behavior and program semantics. However, the performance ofte
arXiv:2604.21537v1 Announce Type: new Abstract: Identifying critical nodes in complex networks is a fundamental task in graph mining. Yet, methods addressing an all-or-nothing coverage mechanics in a
arXiv:2604.21312v1 Announce Type: cross Abstract: This paper presents the NTIRE 2026 Remote Sensing Infrared Image Super-Resolution (x4) Challenge, one of the associated challenges of NTIRE 2026. The
This episode discusses developments in unsupervised learning and latent space technologies presented at AIE Europe 2026, with particular focus on how unsupervised learning techniques intersect with la
arXiv:2604.19993v1 Announce Type: cross Abstract: Complex-Valued Neural Networks (CVNNs) have significant advantages in handling tasks that involve complex numbers. However, existing CVNNs are unable
arXiv:2603.24725v2 Announce Type: replace Abstract: Recently, 3D Gaussian Splatting (3DGS) greatly accelerated mesh extraction from posed images due to its explicit representation and fast software ra
arXiv:2604.01965v2 Announce Type: replace-cross Abstract: Scientific knowledge discovery increasingly relies on large language models, yet many existing scholarly assistants depend on proprietary syst
arXiv:2604.20797v1 Announce Type: cross Abstract: Local gauge symmetry underlies fundamental interactions and strongly correlated quantum matter, yet existing machine-learning approaches lack a genera