Knowledge catalogue
Build on-device personal AI agents on Windows PCs with new tools from NVIDIA and Microsoft, including secure sandboxing, faster local inference, multi-GPU support, and RTX acceleration for Windows AI
arXiv:2606.00251v1 Announce Type: new Abstract: The ability to recognize one's own limitations and decide whether to solve a problem or delegate is fundamental for reliable intelligent systems. Yet we
arXiv:2606.00811v1 Announce Type: cross Abstract: Data centers now account for 4.4% of United States electricity demand, yet the grid-level effectiveness of the renewable energy certificates (RECs) an
arXiv:2606.01946v1 Announce Type: new Abstract: Embedded magnetic tracking holds highly attractive prospects for remote navigation of endoluminal medical devices. However, existing six-degree-of-freed
arXiv:2606.00837v1 Announce Type: cross Abstract: Diffusion models provide strong priors for generating structured data, but many tasks require outputs beyond the scale on which these models are typic
arXiv:2606.01513v1 Announce Type: cross Abstract: High-stakes enterprise document generation, including financial dispute narratives, compliance notices, and audit summaries, demands schema correctnes
arXiv:2606.01149v1 Announce Type: new Abstract: Video Moment Retrieval (MR) and Highlight Detection (HD) are crucial tasks in video analysis that aim to localize specific moments and estimate clip-wis
arXiv:2606.01544v1 Announce Type: new Abstract: Deploying Large Language Models (LLMs) in practice incurs substantial memory and computational costs. Post-training pruning (PTP) is an effective approa
arXiv:2606.00955v1 Announce Type: new Abstract: Despite the growing availability of cryo-electron microscopy (cryo-EM) density maps, effectively leveraging them for protein representation remains chal
arXiv:2602.19848v2 Announce Type: replace Abstract: Skin lesion classification datasets often suffer from severe class imbalance, with malignant cases significantly underrepresented, leading to biased
arXiv:2606.01212v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems are widely deployed and increasingly influential, but their reliance on external corpora exposes new secu
arXiv:2606.00690v1 Announce Type: new Abstract: Sequential conformal prediction (CP) provides valid uncertainty quantification under the assumption of residual exchangeability. However, this assumptio
arXiv:2606.01294v1 Announce Type: new Abstract: Linear attention reduces the quadratic cost of softmax attention by maintaining a recurrent fast-weight state, but it consistently lags on in-context re
arXiv:2606.01024v1 Announce Type: cross Abstract: Discrete Masked diffusion language models generate text by iterative parallel decoding, but few-step decoding suffers from a tradeoff between length a
arXiv:2606.00576v1 Announce Type: new Abstract: Reliable mobile manipulation in dynamic indoor environments requires a scene representation that remains geometrically consistent, semantically queryabl
arXiv:2606.02418v1 Announce Type: cross Abstract: Quantum LDPC code discovery requires searching large algebraic design spaces while reliably certifying the parameters and equivalence classes of any c
Excited for Ollama to be working with @nvidia for the NVIDIA RTX Spark launch! NVIDIA RTX Spark: a 1-petaflop superchip, the full CUDA and RTX ecosystem, and Windows-native agents. A new beginning for
arXiv:2411.05196v3 Announce Type: replace Abstract: This study presents DhondtXAI as a SHAP-independent, D'Hondt-based attribution framework for tabular XAI. Instead of model-native feature importance
arXiv:2606.01521v1 Announce Type: new Abstract: A central problem in machine learning is that models can achieve near-perfect training performance while generalizing substantially less well to unseen
arXiv:2511.15645v3 Announce Type: replace Abstract: Pedestrian inertial odometry (PIO) estimates autonomous pedestrian motion using only acceleration and angular velocity measurements collected by an
arXiv:2606.01607v1 Announce Type: cross Abstract: Federated learning (FL) is a decentralized approach that enables collaborative model training without exposing raw data. Instead of transferring sensi
This post discusses creating or using a LoRA (Low-Rank Adaptation) model compatible with Flux Klein 9b, an AI image generation model, specifically for generating comic book-style characters. The discu
arXiv:2606.01549v1 Announce Type: new Abstract: AI-based semantic and instance segmentation of terrestrial and drone LiDAR point clouds is emerging as a transformative approach for converting the comp
arXiv:2602.06841v4 Announce Type: replace Abstract: Over the last decade, Explainable AI has primarily focused on interpreting individual model predictions, producing post-hoc explanations that relate
Generate a complete storyboard from a single prompt, then animate it in Seedance 2.0 using a reference image. This ComfyUI workflow uses LLMs to expand prompts, create storyboard scenes, and format ev
arXiv:2603.11946v2 Announce Type: replace-cross Abstract: Probabilistic circuits (PCs) enable exact and tractable inference but employ data independent mixture weights that limit their ability to capt
Orion4D Anaglyph is a custom node that converts 2D images into stereoscopic 3D renders using depth maps, offering adjustable parameters for parallax, convergence, and depth processing. Designed for hi
Orion4D MaskPro is an advanced mask editor extension for ComfyUI, a popular node-based AI image generation interface. It provides specialized tools for creating and editing masks directly within Comfy
TextMakerPro is a custom node for ComfyUI that includes a browser-based text and layout editor for creating stylized text images within the ComfyUI workflow. The tool allows users to design and genera
arXiv:2606.01273v1 Announce Type: new Abstract: Spatio-temporal point processes (STPPs) provide a principled framework for modeling asynchronous events in continuous time and space. Recent diffusion-b
arXiv:2603.06741v2 Announce Type: replace-cross Abstract: Training frontier-scale diffusion models often requires substantial computational resources concentrated in tightly-coupled clusters, limiting
arXiv:2606.01819v1 Announce Type: new Abstract: Photorealistic style transfer aims to match the color and tone of an input image to that of a style target while preserving the content and details of t
Flux 2 Klein, the smaller quantized version of the Flux 2 image generation model, exhibits noticeable quality loss through VAE decoding artifacts that manifest as visual degradation in smooth gradient
arXiv:2606.02385v1 Announce Type: cross Abstract: Sparse Autoencoders (SAEs) have found success parsing neural representations into interpretable concepts, providing a basis for understanding and cont
Adds knowledge to Ollama models using Retrieval-Augmented Generation (RAG) , where users create a knowledge base directory with reference files like PDFs, text files, or CSVs . A custom model can be c
arXiv:2510.01891v2 Announce Type: replace-cross Abstract: Individual Head-Related Transfer Functions (HRTFs) are starting to be introduced in many commercial immersive audio applications and are cruci
arXiv:2603.02650v2 Announce Type: replace-cross Abstract: Diffusion planners are a strong approach for offline reinforcement learning, but they can fail when value-guided selection favours trajectorie
Perplexity AI demonstrates a hybrid approach to AI inference that combines on-device processing for sensitive data with cloud-based AI services to achieve scalability and contextual understanding. Thi
arXiv:2606.00991v1 Announce Type: new Abstract: Transportation systems management and operations (TSMO) increasingly depends on timely interpretation of heterogeneous data, from various sensor streams
arXiv:2606.00776v1 Announce Type: new Abstract: Fast and accurate prediction of crystal properties is a central challenge in new materials design. Graph neural networks and Transformer-based models ha
arXiv:2606.01596v1 Announce Type: cross Abstract: Learning chaotic dynamical systems from data requires more than short-term predictive accuracy: the learned model must preserve the attractor geometry
arXiv:2606.00718v1 Announce Type: new Abstract: While Large Language Models (LLMs) have recently shown promise in Automated Heuristic Design (AHD), existing methods typically generate and evolve heuri
arXiv:2603.00171v3 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) are shifting towards 'Thinking with Images' by actively exploring image details. While effective, lar
arXiv:2606.01060v1 Announce Type: cross Abstract: Preference alignment has substantially improved the observable behavior of large language models, yet it remains unclear what alignment changes intern
Paul Thurrott / Thurrott: Microsoft announces new on-device AI updates for Edge: a dev preview of a new SLM called Aion-1.0-Instruct, Language Detector and Translator APIs, and more — Tied to the earl
Tom Warren / The Verge: Microsoft announces the new Surface RTX Spark Dev Box for local AI development, powered by Nvidia's new Arm-based RTX Spark chips and 128GB of unified memory — The Surface RTX
Microsoft only just announced a new Surface Laptop Ultra at the weekend, and it's now revealing a miniature Surface PC aimed at developers. The new Surface RTX Spark Dev Box is powered by Nvidia's new
arXiv:2512.07806v2 Announce Type: replace Abstract: We propose Multi-view Pyramid Transformer (MVP), a scalable multi-view transformer architecture that directly reconstructs large 3D scenes from tens
arXiv:2510.02528v2 Announce Type: replace Abstract: Large Multimodal Models (LMMs) demonstrate impressive in-context learning abilities from few multimodal demonstrations, yet the internal mechanisms
arXiv:2503.07325v2 Announce Type: replace Abstract: Understanding and certifying the behavior of modern deep neural networks remains a fundamental challenge in reliable machine learning. We introduce
The agentic AI moment has arrived, but delivering on its promise requires more than good models. It also takes fast hardware, secure runtimes, a responsive data layer and models tuned for long-running
A Reddit post discussing an issue where Ollama (an AI model tool) refuses to process or list a C# game script due to safety concerns about potential destructive code. The post likely explores the limi
arXiv:2606.00936v1 Announce Type: new Abstract: Visual Place Recognition (VPR) is fundamental to long-term robot localization and SLAM, yet current systems overwhelmingly rely on RGB input, implicitly
arXiv:2602.07955v2 Announce Type: replace Abstract: Crowd scenes captured by cameras at different locations vary greatly, and existing crowd models have limited generalization for unseen surveillance
arXiv:2606.00104v1 Announce Type: cross Abstract: Foundation models are increasingly used to drive autonomous systems, yet existing approaches either keep the model in a tight control loop, raising la
arXiv:2606.01597v1 Announce Type: new Abstract: Robot swarms can exhibit coherent collective behaviors through local perception, limited communication and decentralized decision-making, yet modeling a
PixelDiT is a 1.3B parameter diffusion transformer model that generates images directly in pixel space without requiring a VAE (Variational Autoencoder), representing an alternative approach to tradit
arXiv:2512.22702v2 Announce Type: replace Abstract: Deep learning models have grown popular in time series applications. However, the large quantity of newly proposed architectures and the often contr
arXiv:2606.00523v1 Announce Type: new Abstract: Standard Large Language Models (LLMs) follow a read-then-generate paradigm, causing unnecessary latency and computation. Streaming LLMs alleviate this i
arXiv:2606.00108v1 Announce Type: cross Abstract: Global biodiversity is declining at unprecedented rates, yet the tools available to monitor and protect ecosystems remain limited by constraints in po