b9578
Release b9578 of llama.cpp includes a refactor of video subprocess handling in the mtmd (multi-threaded multi-device) component via pull request #24316 . The release provides prebuilt binaries across
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Release b9578 of llama.cpp includes a refactor of video subprocess handling in the mtmd (multi-threaded multi-device) component via pull request #24316 . The release provides prebuilt binaries across
b9580 is a llama.cpp release that adds v_dot2_f32_f16 support in matrix-matrix multiplication and Flash Attention via Vulkan, implementing support for Valve's fp16 dot2 extension. The release also inc
llama.cpp b9581 is a release that includes optimization for Vulkan backend memory usage, specifically reducing iq1 shared memory usage for mul_mm operations. Released on June 9, 2026 , this build prov
The search results don't contain specific information about release b9584. Based on the context from other llama.cpp releases in the results, b9584 is likely an intermediate build version of llama.cpp
Release b9585 of llama.cpp fixes granite speech model inference by applying embedding scale when deepstack is not used . The release was published on June 9, 2026, and represents a bug fix within the
arXiv:2606.09051v1 Announce Type: new Abstract: Convolutions have successfully transitioned from image processing to the complex realm of non-Euclidean higher-order domains, particularly in hypergraph
arXiv:2606.07771v1 Announce Type: cross Abstract: Foundation models for astronomical surveys offer powerful learned representations that can be transferred to downstream regression tasks such as galax
arXiv:2606.09175v1 Announce Type: cross Abstract: Recently, mobile edge computing (MEC)-enabled collaborative deep neural network (DNN) inference has emerged as a promising approach for delivering int
arXiv:2512.16349v2 Announce Type: replace-cross Abstract: We propose a collaborative edge-to-server inference framework for vision-language models (VLMs) that reduces communication cost while maintain
arXiv:2410.05662v4 Announce Type: replace Abstract: Most federated learning (FL) approaches assume a fixed device set. However, real-world scenarios often involve devices dynamically joining or leavin
arXiv:2606.08810v1 Announce Type: cross Abstract: Gaussian-corrupted sentence embeddings have no direct linguistic interpretation, yet continuous diffusion language models can generate fluent text fro
arXiv:2606.09181v1 Announce Type: new Abstract: Recent advances in video multimodal models have significantly improved VideoQA performance. However, these systems often rely on spurious statistical co
arXiv:2606.09572v1 Announce Type: cross Abstract: Vision-language-action models have shown strong promise for robot manipulation, yet raw language is primarily needed to specify task intent rather tha
NVIDIA DGX Spark Enterprise Manageability enables IT administrators to plan, configure, and manage DGX Spark deployments at scale with coverage of workflows, provisioning, update procedures, and syste
arXiv:2606.09758v1 Announce Type: cross Abstract: Parametric imitation learning via behavior cloning can suffer from poor generalization to out-of-distribution states due to compounding errors during
arXiv:2411.03253v2 Announce Type: replace-cross Abstract: We propose a general framework for end-to-end learning of data structures. Our framework adapts to the underlying data distribution and provid
arXiv:2601.06188v3 Announce Type: replace Abstract: As Earth-observing satellite constellations grow in size and capability, distributed onboard control offers a pathway to novel responses and time-se
arXiv:2606.07999v1 Announce Type: new Abstract: Effective skill grounding is essential for deploying reusable skills in embodied agents, as even minor embodiment or environmental differences can rende
arXiv:2606.08205v1 Announce Type: new Abstract: Feed-forward 3D reconstruction models have recently shown strong generalization across diverse scenes, yet most of them recover geometry only up to an u
arXiv:2602.05175v2 Announce Type: replace Abstract: Deep neural networks demonstrate impressive performance in visual recognition but remain highly vulnerable to imperceptible adversarial attacks. Exi
arXiv:2606.09208v1 Announce Type: new Abstract: During warhead detonation, high-density, high-speed, and mutually occluded fragments are generated. Their mechanical parameters (position, velocity, kin
arXiv:2409.15723v3 Announce Type: replace Abstract: Large Language Models have achieved impressive performance across diverse applications, yet their training typically depends on centralized data col
arXiv:2606.08653v1 Announce Type: cross Abstract: Action-supervised fine-tuning of vision-language-action (VLA) policies fits demonstrations effectively but constrains only the directions that change
Frame Adjustments Demo: Most people think AI filmmaking means finding the one perfect model. It doesn't. @heydoughogan breaks down why the best workflows are mix-and-match. Different models for differ
arXiv:2606.09681v1 Announce Type: new Abstract: Eye movements, including saccades, are widely regarded as highly sensitive and objective biomarkers of neurophysiologic states. Detecting saccadic signa
I2T2I (image-to-text-to-image) is an image editing approach that converts an image to text, allows editing of the text, and then converts the edited text back to an image. Unlike inpainting or masking
Introducing the Comfy Affiliate Program! Earn 30% recurring commission for 3 months on every Comfy Cloud subscription you refer. If you create tutorials, review AI tools, run a newsletter, or just hav
Ideogram 4.0 supports inpainting workflows , and Magic Fill is its inpainting tool that allows editing specific regions of images to replace objects, add text, fix imperfections, and change background
Krea 2 is @krea_ai's first foundation model built from scratch. Most models render what you describe. Krea 2 interprets the mood, style, and direction behind it. Simple prompts → wide range of distinc
Krea2 is an AI image generation tool that supports both text-to-image generation and style reference capabilities, allowing users to create images from text prompts and apply specific visual styles to
arXiv:2606.08751v1 Announce Type: new Abstract: Accurate quantification and uptake measurement in PET are critical for assessing disease progression and supporting clinical decision-making. While high
arXiv:2606.09343v1 Announce Type: new Abstract: Neural combinatorial optimization has recently achieved strong results on the Euclidean Traveling Salesman Problem (TSP) using generative models such as
LM Studio demonstrated its capabilities at WWDC (Apple Worldwide Developers Conference) at the Steve Jobs Theater, showcasing MLX running on four Mac Studio computers in a distributed setup. The demo
arXiv:2507.20975v5 Announce Type: replace-cross Abstract: Operator models are regression algorithms between Banach spaces of functions. They have become an increasingly critical tool for spatiotempora
A user announced a major update to their Ollama coding assistant featuring Cline, an autonomous coding agent that operates within IDEs and can create, edit files, execute commands, and interact with t
arXiv:2606.08744v1 Announce Type: new Abstract: Global LiDAR localization is a fundamental task for autonomous navigation systems. Recent methods perform Scene Coordinate Regression (SCR) and achieve
arXiv:2407.13303v2 Announce Type: replace Abstract: Conventional large-scale indoor localization based on Wi-Fi RSSI fingerprinting faces issues of time-consuming and labor-intensive labeled data coll
arXiv:2606.07669v1 Announce Type: cross Abstract: Deploying Video Anomaly Detection (VAD) in real-world surveillance faces a fundamental tension between the demand for high-level semantics to ensure e
arXiv:2606.07835v1 Announce Type: new Abstract: A fundamental tension exists in the large-step inference of diffusion models via their deterministic probability flow ordinary differential equation (PF
arXiv:2606.09548v1 Announce Type: cross Abstract: Federated Learning (FL) allows a set of clients to collectively train a global model without sharing local training data. Giving the responsibility of
arXiv:2606.09355v1 Announce Type: new Abstract: Robust inertial odometry is essential for various carriers when external sensing is unreliable. Learning-based methods reduce integration drift by captu
NAVA FP8 ComfyUI likely discusses FP8 precision quantization for ComfyUI, a technique that reduces memory usage and improves performance on compatible GPUs while maintaining reasonable output quality.
arXiv:2606.07660v1 Announce Type: new Abstract: Adapting foundation models to detect generative artifacts via gradient-based updates compromises their intrinsic representations. Under optimization on
arXiv:2512.03606v2 Announce Type: replace Abstract: Accurate marine wind forecasts are essential for safe navigation, ship routing, and energy operations, yet they remain challenging because observati
Ollama has been made available on Hermes, enabling users to run Ollama locally on the Hermes Desktop application. This release was anticipated by the community and represents a significant development
Ollama now supports Hermes Desktop Run: 'ollama launch hermes-desktop' Media Self-learning skills Hermes generates Python skills from natural-language descriptions and improves them as you use them. S
arXiv:2606.08046v1 Announce Type: new Abstract: We present OSMGraphCLIP, a CLIP-style geospatial representation model that learns global location embeddings from freely available OpenStreetMap (OSM) d
arXiv:2606.08935v1 Announce Type: cross Abstract: Representation-based time-series anomaly detection algorithms significantly outperform other methods on diverse anomaly detection tasks. However, we n
arXiv:2606.08059v1 Announce Type: new Abstract: Humanoid behavior foundation models aim to acquire reusable whole-body control policies from broad human motion priors, enabling a single controller to
arXiv:2606.08688v1 Announce Type: cross Abstract: Achieving fully automated, physically plausible 3D motion synthesis is a core objective in graphics and generative AI. However, configuring complex en
arXiv:2603.11917v2 Announce Type: replace Abstract: Real-time, on-device segmentation is critical for latency-sensitive and privacy-aware applications such as smart glasses and Internet-of-Things devi
arXiv:2606.07607v1 Announce Type: new Abstract: Advances in machine learning and computational power have unlocked the predictive potential of the human genome, yet biologists now demand that these mo
arXiv:2512.12320v2 Announce Type: replace Abstract: Conventional soft pneumatic actuators, typically based on hollow elastomeric chambers, often suffer from small structural support and require costly
arXiv:2606.09816v1 Announce Type: cross Abstract: Standard diffusion models typically use a single time-homogeneous Gaussian terminal distribution as the reference law for generation. While this choic
arXiv:2604.04554v2 Announce Type: replace Abstract: A key component of Visual Simultaneous Localization and Mapping (VSLAM) is estimating relative camera poses using matched keypoints. Accurate estima
arXiv:2606.09719v1 Announce Type: new Abstract: Autonomous mobile robots operating in tight environments require motion planning frameworks that account for the physical footprint of the robot. Simpli
arXiv:2606.09404v1 Announce Type: cross Abstract: Feature interactions drive much of the predictive power of machine learning models, yet existing explanation methods only detect and quantify interact
arXiv:2606.09587v1 Announce Type: cross Abstract: People are increasingly using AI for creative tasks such as writing. While adoption continues to grow, this form of use risks undermining individual c
arXiv:2606.08953v1 Announce Type: new Abstract: Modern generative models often define an entire probability path from a simple prior to the data law, rather than only an endpoint map. Diffusion models
Self-learning skills Hermes generates Python skills from natural-language descriptions and improves them as you use them. Start with the 70+ skills it ships with and grow your own library around your