Search: “local-ai”

arXiv:2605.10634v1 Announce Type: new Abstract: LLM-based automatic heuristic design has shown promise for generating executable heuristics for combinatorial optimization, but existing methods mainly

Thanks to the @huggingface team for adding Hermes Agent to local apps and shipping a native Hermes traces viewer! 🆕 Hugging Face 🤝 Hermes Agent 🔥 > we added Hermes Agent to local apps: run it locally

arXiv:2605.09969v1 Announce Type: cross Abstract: How should hidden states generated autoregressively be collapsed into a representation that reflects a language model's internal state? Despite tokens

arXiv:2603.08588v2 Announce Type: replace-cross Abstract: State-of-the-art deep reinforcement learning (RL) methods have achieved remarkable performance in continuous control tasks, yet their computat

Uncensored LLMs are architectures that have been modified or fine-tuned to remove standard safety alignment layers (guardrails) that limit a model's ability to discuss sensitive topics. Ollama offers

arXiv:2603.07686v2 Announce Type: replace-cross Abstract: End-to-end (E2E) driving has become a cornerstone of both industry deployment and academic research, offering a single learnable pipeline that

arXiv:2601.23273v2 Announce Type: replace Abstract: Prompt agents have recently emerged as a promising paradigm for automated prompt optimization, framing prompt discovery as a sequential decision-mak

This discussion explores using Ollama to run large language models locally for invoice processing while maintaining control over data. The thread likely addresses selecting appropriate smaller models

v0.30.0-rc15 is a release candidate version of Ollama, an open-source platform for running large language models locally. This particular release is part of the development cycle leading toward the st

arXiv:2605.10325v1 Announce Type: new Abstract: Reinforcement learning from verifiable rewards (RLVR) has improved the reasoning abilities of large language models (LLMs), but most existing approaches

arXiv:2605.10622v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) have achieved remarkable progress in multimodal tasks, yet their reliability is persistently undermined by halluc

arXiv:2605.09173v1 Announce Type: cross Abstract: Wearable sensors enable the continuous acquisition of high-resolution physiological waveforms, such as photoplethysmography and accelerometry, under f

Recent posts on the r/ollama subreddit discuss Ollama Cloud service issues, with the platform experiencing request errors while handling demand and working to scale infrastructure further . Ollama Clo

arXiv:2605.08878v1 Announce Type: cross Abstract: Aligned large language models (LLMs) remain vulnerable to jailbreak attacks. Recent mechanistic studies have identified latent features and representa

arXiv:2605.06741v1 Announce Type: new Abstract: Learning-rate steps are usually treated as hyperparameters. This paper isolates a local beliefspace calculation: when an update is modeled as a projecte

arXiv:2605.07863v1 Announce Type: new Abstract: We present Agentic Decentralized Knowledge Optimization (ADKO), a framework for collaborative black-box optimization across autonomous agents that achie

arXiv:2605.06759v1 Announce Type: new Abstract: The decline of natural pollinators has created a major challenge for crop production in controlled indoor agriculture, particularly in vertical farming

Release b9102 adds support for the im2col_3d operator to the SYCL backend in llama.cpp, expanding GPU-accelerated tensor operations for Intel GPU inference. The im2col_3d operation converts 3D input v

B9103 is a recent release of llama.cpp , a C/C++ implementation for large language model inference. This release represents one of the latest versions in the project's active development cycle, buildi

Release b9105 of llama.cpp includes updates to the AllReduce implementation for CUDA, introducing a NCCL-free provider for tensor parallelism that pipelines data transfers and GPU reduction operations

Release b9106 of llama.cpp includes support for asymmetric FlashAttention in scalar, MMQ, and cooperative matrix paths for Vulkan. The release provides builds for multiple platforms including macOS, L

Release b9109 of llama.cpp introduces refinements to the CUDA tensor parallelism AllReduce implementation, including renaming the --allreduce flag to --reduction-provider and updates to NCCL-free AllR

The search results show recent llama.cpp releases and general information but don't contain specific details about the b9110 release. Based on the search patterns and similar recent releases documente

Release b9112 of llama.cpp introduces a NCCL-free AllReduce implementation for LLAMA_SPLIT_MODE_TENSOR using a single-phase CUDA kernel, and adds an --allreduce flag to llama-bench to select between A

Bare Metal: Z-Image Turbo - Flux.2 Klein 9b - Wan 2.2 discusses comparisons between these lightweight AI image generation models, with Flux.2 Klein 9B showing good prompt adherence and natural composi

With 32GB of RAM, 30B Q4 models run comfortably on M5 MacBook Air , and popular choices include Qwen 3.6 27B (requiring 18GB+ VRAM) and Qwen 3.6 9B (lightweight, runs on 8GB) . Ollama's macOS implemen

Ollama versions prior to 0.17.1 contain a critical out-of-bounds read vulnerability (CVE-2026-7482, CVSS 9.1) that allows remote unauthenticated attackers to leak entire process memory, potentially af

arXiv:2604.02753v2 Announce Type: replace Abstract: Open-vocabulary Object Detection (OVOD) enables models to recognize objects beyond predefined categories, but existing approaches remain limited in

arXiv:2605.07844v1 Announce Type: new Abstract: Energy-based learning is a powerful framework for generative modelling, but its training is inherently non-convex, leading potentially to sensitivity to

arXiv:2508.06816v3 Announce Type: replace Abstract: Lesion segmentation, in contrast to natural scene segmentation, requires handling subtle variations in texture and color, frequent imaging artifacts

arXiv:2605.07457v1 Announce Type: new Abstract: Recent text-guided image editing (TIE) models have made remarkable progress, yet edited images still frequently suffer from fine-grained issues such as

arXiv:2602.20338v2 Announce Type: replace Abstract: Chain-of-Thought (CoT) prompting significantly improves reasoning in Large Language Models, yet the temporal dynamics of the underlying representati

arXiv:2605.06280v2 Announce Type: replace Abstract: Recent advancements in image animation have utilized diffusion models to breathe life into static images. However, existing controllable frameworks

arXiv:2510.02371v2 Announce Type: replace-cross Abstract: Smart grids are exposed to passive eavesdropping, where attackers listen silently to communication links. Although no data is actively altered

arXiv:2605.07962v1 Announce Type: new Abstract: Performance evaluation is essential for assessing the quality of machine learning (ML) models and guiding deployment decisions. In federated learning (F

arXiv:2605.07698v1 Announce Type: new Abstract: Grammar-constrained generation is often combined with local vocabulary masking and speculative decoding, but the resulting sampling law is not the gramm

Generate split-stack videos like this in a single click. The basic setup is simple, just upload an image and the system takes care of the rest. Want more control? Switch to graph mode and fine-tune ea

arXiv:2605.07432v1 Announce Type: new Abstract: Chatbots are robots that can communicate with humans using text or voice signals. Legal chatbots improve access to justice, since legal representation a

arXiv:2605.06740v1 Announce Type: cross Abstract: We introduce Geometric Kolmogorov--Arnold Networks (GeoKANs), a family of geometry-aware KAN-type models in which approximation is carried out in lear

arXiv:2605.07536v1 Announce Type: cross Abstract: Detecting stealthy malicious communications from flow logs under benign-only training remains a critical challenge in network security. Malicious comm

arXiv:2605.08074v1 Announce Type: new Abstract: Conformal prediction (CP) provides a distribution-free approach to uncertainty quantification with finite-sample guarantees. However, applying CP to gra

arXiv:2605.07211v1 Announce Type: cross Abstract: Mobile devices face diverse resource constraints and non-IID data class distributions, requiring fast on-device inference for local in-distribution (I

A Reddit discussion comparing HiDream-O1-Image-Dev (the newer, 8B pixel-native distilled model) with ZImage Base, examining stylistic and performance differences between the two text-to-image generati

arXiv:2605.07214v1 Announce Type: new Abstract: Large Language Models have recently emerged as a promising paradigm for automated heuristic design for NP-hard combinatorial optimization problems. Desp

🆕 Hugging Face 🤝 Hermes Agent 🔥 > we added Hermes Agent to local apps: run it locally with any compatible GGUF/MLX model > shipped native traces support for Hermes Agent: visualize your Hermes traces

This post describes a fixed-camera timelapse visualization created using AI (likely Stable Diffusion) that depicts Los Angeles's transformation over 2,000 years, starting from its original state as To