local ai

arXiv:2605.00020v1 Announce Type: new Abstract: The success of large foundation models is catalyzing a new paradigm for AI-native 6G network design: wireless foundation models for physical layer desig

I cannot provide a factual summary without access to the actual form content. This appears to be an application form shared by ComfyUI on X (Twitter), likely for a program, position, or opportunity re

llama.cpp enables LLM inference in C/C++ , and release b9014 represents a build revision or commit snapshot from the llama.cpp repository on GitHub. This release would include bug fixes, feature impro

The search results show recent llama.cpp releases but not the specific b9015 release details. Based on the pattern found (b9010 is mentioned as the latest release from the search results), b9015 is li

Release b9016 is a build of llama.cpp, an LLM inference implementation in C/C++ . This build designation represents a specific intermediate version in the project's development cycle, similar to other

B9018 is the latest version of llama.cpp released on May 4, 2026. Llama.cpp is a project for LLM inference in C/C++ , providing efficient large language model execution with broad hardware support inc

b9019 is a release of llama.cpp, a C/C++ implementation for LLM inference. As a release tag from the ggml-org/llama.cpp repository, it represents a specific commit or version of the project that inclu

b9020 is a build release of llama.cpp (a C/C++ implementation of LLM inference) released on May 4, 2026, with precompiled binaries available for multiple platforms including macOS, Android, OpenEuler,

B9022 is a release of llama.cpp created on May 4, 2026, with commit d8794ee signed with GitHub's verified signature. The llama.cpp project is the main playground for developing new features for the gg

b9025 is a release from llama.cpp, a C/C++ project for LLM inference . The release uses a build numbering system for intermediate versions of the library. As a llama.cpp release, it likely includes up

arXiv:2605.00237v1 Announce Type: new Abstract: Bayesian optimization is a sequential method for minimizing objective functions that are expensive to evaluate and about which few assumptions can be ma

A Reddit discussion from the Ollama community addresses reports of slow model responses, clarifying that the models themselves are not inherently slower but that rate limiting is a more likely cause o

arXiv:2605.00348v1 Announce Type: cross Abstract: Recent multi-bit watermarking methods for large language models (LLMs) prioritize capacity over reliability, often conflating decoding with detection.

arXiv:2605.00768v1 Announce Type: new Abstract: The transformer is the most popular neural architecture for language modeling. The cornerstone of the transformer is its global attention mechanism, whi

arXiv:2605.00005v1 Announce Type: new Abstract: The increasing deployment of deep neural networks (DNNs) in cyber-physical systems (CPS) enhances perception fidelity, but imposes substantial computati

arXiv:2605.00083v1 Announce Type: new Abstract: Accurate forecasting of bus ridership (passengers numbers) is crucial for efficient management and optimization of public transport systems. Traditional

arXiv:2605.00562v1 Announce Type: new Abstract: The emergence of deep neural networks capable of revealing high-fidelity scene details from sparse 3D point clouds has raised significant privacy concer

DeepSeek V3 and R1 API free tier includes 500M tokens per month , indicating free access remains available for API users. The search results focus on a major service outage in March 2026 and the recen

arXiv:2605.00159v1 Announce Type: new Abstract: In reinforcement learning (RL) for robotic manipulation, the Decision Transformer (DT) has emerged as an effective framework for addressing long-horizon

arXiv:2605.00628v1 Announce Type: cross Abstract: Text-to-SQL enables non-expert users to query databases in natural language, yet real-world schemas often suffer from ambiguous, abbreviated, or incon

arXiv:2605.00578v1 Announce Type: new Abstract: Federated learning (FL) offers a promising framework for collaborative digital pathology by enabling model training across institutions. However, real-w

arXiv:2605.00698v1 Announce Type: cross Abstract: Federated learning (FL) holds great potential for medical applications. However, statistical heterogeneity across healthcare institutions poses a majo

arXiv:2605.00225v1 Announce Type: cross Abstract: We show that pretrained acoustic embeddings classify elephant vocalisations at a level approaching that of end-to-end supervised neural networks, with

arXiv:2603.02727v4 Announce Type: replace Abstract: Medical image segmentation requires models that preserve fine anatomical boundaries while remaining practical for clinical deployment. Transformers

arXiv:2605.00082v1 Announce Type: new Abstract: The Forward-Forward (FF) algorithm presents a compelling, bio-inspired alternative to backpropagation. However, while efficient in training, it has a co

i thought on device ai was stupid but now my local voice model turns 4x faster on my corporate m4 max laptop than my m2 max personal laptop now i want to have a beefier computer to run the transcripti

arXiv:2605.00760v1 Announce Type: new Abstract: This paper deals with solving the 2D Helmholtz equation on non-parametric domains, leveraging a physics-informed neural operator network based on the De

arXiv:2605.00244v1 Announce Type: cross Abstract: We introduce Lucid-XR, a generative data engine for creating diverse and realistic-looking multi-modal data to train real-world robotic systems. At th

arXiv:2605.00475v1 Announce Type: cross Abstract: Real-world fine manipulation, particularly in bimanual manipulation, typically requires low-latency control and stable visual localization, while coll

arXiv:2605.00260v1 Announce Type: new Abstract: Nonlinear Parametric Optimization Network (NLPOpt-Net) is an unsupervised learning architecture to solve constrained nonlinear programs (NLP). Given the

arXiv:2605.00751v1 Announce Type: new Abstract: Monte Carlo Tree Search (MCTS) scales poorly in cooperative multi-agent domains because expansion must consider an exponentially large set of joint acti

OneTrainer is a one-stop solution for all diffusion training needs. The tool now supports the Ernie Image model, which can be trained using LoRA (Low-Rank Adaptation) methods. This adds support for tr

arXiv:2605.00265v1 Announce Type: new Abstract: Real-world knowledge is often organized as hierarchies such as product taxonomies, medical ontologies, and label trees, yet learning hierarchical repres

arXiv:2602.19423v3 Announce Type: replace Abstract: Domain adaptive segmentation (DAS) is a promising paradigm for delineating intracellular structures from various large-scale electron microscopy (EM

arXiv:2605.00421v1 Announce Type: new Abstract: Large language models (LLMs) show promise in radiology but their deployment is limited by computational requirements that preclude use in resource-const

Sentinel is a local-first AI coding desktop application built with Rust and Tauri that automatically routes coding tasks to appropriate models based on task complexity. Instead of swapping between mul

arXiv:2605.00536v1 Announce Type: cross Abstract: Scaling laws for Large Language Models (LLMs) establish that model quality improves with computational scale, yet edge deployment imposes strict const

arXiv:2605.00438v1 Announce Type: cross Abstract: Long-horizon robotic manipulation requires plans that are both logically coherent and geometrically grounded. Existing Vision-Language-Action policies

This April we shipped 14 new models ⬇️ → Seedance 2.0 → GPT Image 2 → Wan 2.7 → Ace Step 1.5 XL → Quiver SVG → Happy Horse → Ernie-Image → Veo 3.1 Lite / Veo 3.1 Fast → Sonilo → SUPIR → RIFE & FILM in

arXiv:2512.04694v3 Announce Type: replace Abstract: Effective earthquake risk reduction relies on accurate site-specific evaluations, which require models capable of representing the influence of loca

arXiv:2505.11329v5 Announce Type: replace-cross Abstract: Distributed inference of large language models (LLMs) using tensor parallelism can introduce communication overheads of 20% even over GPUs con

arXiv:2605.00219v1 Announce Type: new Abstract: We present VkSplat, a high-performance, cross-vendor 3D Gaussian Splatting (3DGS) training pipeline implemented fully in Vulkan compute, addressing perf

This Reddit post discusses the viability of using second-hand custom-built RTX 2080 Ti GPUs with 22GB VRAM for running Stable Diffusion models in ComfyUI, including whether two cards could be linked v

b9012 is a build version from the llama.cpp GitHub repository, which is an LLM inference implementation in C/C++ . The release likely contains updates, bug fixes, and improvements to the llama.cpp inf

This discussion thread explores lightweight vision-language models that can run locally, including options like Llama 3.2 Vision, Qwen2.5-VL, and SmolVLM2, optimized for tasks like OCR and visual ques

An open-source locally-run conversational AI that moves beyond simple request-response models by implementing persistent memory, belief, and self-reflection. The system stores all user profiles, memor