Search: “local-ai”

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

arXiv:2511.14143v2 Announce Type: replace-cross Abstract: Video Moment Retrieval is a task in video understanding that aims to localize a specific temporal segment in an untrimmed video based on a nat

arXiv:2606.08712v1 Announce Type: cross Abstract: Purpose: Spatial transcriptomics (ST) enables gene expression measurements within the tissue context. However, these measurements are often noisy, low

arXiv:2507.09751v3 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated impressive capabilities in natural language understanding and generation, but exhibit problems with l

arXiv:2405.17823v5 Announce Type: replace-cross Abstract: A central question in vector- and function-valued learning is how to design kernels that capture both local and non-local interactions while r

arXiv:2406.19749v2 Announce Type: replace-cross Abstract: Automatic vessel segmentation plays a pivotal role in the development of next-generation interventional navigation systems for surgical roboti

ComfyUI announced upcoming video content on their YouTube channel, encouraging followers to subscribe for future releases. The post was shared via X (formerly Twitter) as a promotional update directin

arXiv:2506.20699v2 Announce Type: replace Abstract: Learning in non-stationary and multi-context environments requires more than ordinary within-task generalization. A system must also discover which

arXiv:2302.09832v4 Announce Type: replace Abstract: In distributed optimization and federated learning, slow and costly communication between parallel devices and the central server constitutes the pr

arXiv:2606.07856v1 Announce Type: new Abstract: When a language model trains on its own verified outputs, does it acquire capability beyond its base, or merely get better at expressing capability the

arXiv:2606.09248v1 Announce Type: new Abstract: Multi-modal Large Language Models (MLLMs) have achieved remarkable progress in video temporal grounding with reinforcement learning for generating reaso

arXiv:2606.07675v1 Announce Type: cross Abstract: Smartphone telephoto cameras are approaching a 'telephoto physics wall': as pixel pitches shrink toward sub-0.5 micron, the optics remain limited by g

arXiv:2606.08719v1 Announce Type: new Abstract: ''Thinking with Images'' has emerged as an effective paradigm for fine-grained visual reasoning: by explicitly zooming into relevant regions and reasoni

this model is the opposite of mythos. Its small, cost effective, apache 2.0, and locally deployable. This is the way LLMs should go. small, open source, transparent and sovereign vs large, expensive,

Three MLX videos dropped at WWDC: Running agents locally by @angeloskath https://www.youtube.com/watch?v=wykPErJ8M-8 Distributed inference and training by Tatiana Likhomanenko https://www.youtube.com/

arXiv:2606.09188v1 Announce Type: cross Abstract: Bearing-only target localization is a fundamental problem in optical measurement and finds extensive applications in unmanned aerial vehicle (UAV) tec

Turn a simple idea into a storyboard, then generate the video with Seedance 2.0. This ComfyUI workflow uses LLMs to structure prompts into storyboard-ready scenes that define how the video should play

arXiv:2606.09012v1 Announce Type: cross Abstract: Post-training quantization (PTQ) converts a trained full-precision model into low-bit weights without task-level retraining, while quantization-aware

arXiv:2606.07592v1 Announce Type: new Abstract: Offline reinforcement learning requires careful conservatism to mitigate distribution shift, yet most existing methods apply a fixed penalty uniformly a

Use Ollama with Hermes Desktop by @NousResearch. Hermes Desktop brings the same agent (its multi-agent engine, self-improving skills, and messaging integrations) into a desktop app on macOS, Windows,

arXiv:2606.08032v1 Announce Type: cross Abstract: Reinforcement Learning from Human Feedback via Proximal Policy Optimization often suffers from policy mode collapse, brittle exploration loops, and di

arXiv:2606.08918v1 Announce Type: new Abstract: Worldwide image geo-localization aims to determine the capture location of an image on a global scale. Existing methods often mislocalize images by matc

Ollama automatically unloads inactive models from memory based on inactivity parameters, with models being removed after a specified duration of non-use . By default, Ollama unloads a model after 5 mi

I'd need to search for this specific Reddit post to provide accurate details about the actual findings and technical specifics of this GPU performance benchmark. This post likely discusses throughput

arXiv:2606.07325v1 Announce Type: cross Abstract: We study the minimax rate of estimating a future value mu_{t_n+h} of a curve tmapstomu_t in the 2-Wasserstein space P_2(R^d) from finitely many noisy

arXiv:2606.06536v1 Announce Type: cross Abstract: Automated defect detection in high-voltage transmission-line insulators remains challenging due to severe class imbalance, large scale variation, and

This release updates the compute runtime version to 26.x within a Docker configuration for SYCL (Syclon Compute Language) support in llama.cpp. The change, addressed in pull request #24070, modernizes

llama.cpp is an LLM inference tool in C/C++ , and b9555 represents a specific build or version release from the ggml-org/llama.cpp GitHub repository. The project does not follow traditional release pr

llama.cpp b9556 release adds support for AMD RDNA3.5 graphics hardware (gfx1152 and gfx1153) in its HIP backend . The release includes compiled binaries for multiple platforms including macOS, Linux,

llama.cpp release b9558 includes a Vulkan optimization that uses cm2 decode_vector for mul_mat_id B matrix loads, allowing vec4 loads and increasing BK to 64, resulting in performance speedups. The re

B9561 is an intermediate build release of llama.cpp, the C/C++ implementation of large language model inference. Llama.cpp releases use build identifiers (b-numbers) to track development versions betw

b9563 is a release build of llama.cpp, an open-source software library for large language model inference that is co-developed alongside the GGML tensor library. This intermediate build includes vario

The search results did not provide specific information about the b9564 release. Based on the context of llama.cpp releases and the pattern observed with nearby releases (b9542, b9543, b9544, etc.), I

Based on available search results, I cannot find specific details about the b9568 release. B9568 is a build number from llama.cpp, an LLM inference implementation in C/C++ . This release likely contai

arXiv:2606.07311v1 Announce Type: cross Abstract: As video generation models like Veo 3.1 and LTX-2 advance, their ability to accurately represent diverse global cultures remains a critical yet unders

Ideogram offers JSON prompting functionality that some users find powerful and useful, though others prefer natural language prompting interfaces. This post discusses a comparison between Ideogram and

arXiv:2606.06906v1 Announce Type: cross Abstract: Long-context question answering (QA) remains challenging for smaller language models even when answer-bearing evidence is already present in the input

Epic research. Not far off from personal experience : https://tomtunguz.com/using-local-ai-to-work-faster/ Narrative violation: according to @Stanford research, local models can answer 71.3% of real-w

arXiv:2606.07179v1 Announce Type: new Abstract: Streaming 3D Gaussian Splatting requires highly scalable, progressive representations. Existing progressive methods rely on extit{discrete layering}, ac

arXiv:2606.07190v1 Announce Type: new Abstract: Reasoning prefixes shape the future trajectory of LLM problem solving, yet existing process reward models usually evaluate them through local step corre

arXiv:2512.20963v3 Announce Type: replace-cross Abstract: Diffusion models excel at generating high-quality, diverse samples, yet they risk memorizing training data when overfit to the training object

Clem Delangue discusses using local AI models and LlamaCPP to prepare for a flight to NYC without internet access, highlighting the utility of offline AI tools for travel preparation. The post demonst

User seeks guidance on PDF processing methods for local AI agents built with Ollama, comparing approaches like PDFPlumber extraction, vector database RAG systems, and alternative techniques for accura

arXiv:2606.07334v1 Announce Type: cross Abstract: Harmony is a compact symbolic layer where mathematical pitch relations, acoustic consonance, and musical convention meet. This report treats chord-sym

Ideogram 4 is Ideogram's first open-weight text-to-image model trained from scratch, introducing structured JSON prompting with multilingual text rendering and explicit layout controls. Released on Ju

Ideogram 4 is an AI image generation model that features improved capabilities for creating text within images and generating visual content . The Reddit post likely showcases a comic or sequential ar