Search: “local-ai”

b8883 is a release build of llama.cpp, an open-source software library that performs inference on various large language models, co-developed alongside the GGML tensor library. This intermediate build

llama.cpp is a C/C++ implementation that enables LLM inference with minimal setup and state-of-the-art performance on a wide range of hardware locally and in the cloud. Release b8884 is a build/versio

The search results don't contain specific information about release b8885. Based on the llama.cpp release numbering pattern visible in the results, b8885 is an intermediate build release of llama.cpp,

B8886 is a release version from llama.cpp, the C/C++ project for LLM inference. The main goal of llama.cpp is to enable LLM inference with minimal setup and state-of-the-art performance on a wide rang

Based on the available information, b8888 appears to be a build release version identifier for llama.cpp. While I couldn't locate specific details about this particular release, llama.cpp release vers

b8891 is a release version of llama.cpp, which is a tool for LLM inference in C/C++. llama.cpp is a free and open-source tool that allows users to run AI models locally on Windows, Linux and macOS. Th

By default, Ollama binds to port 11434 on localhost, which means it's accessible only on your own machine. Ollama has no built-in authentication and should be secured with firewall rules, VPN, or reve

arXiv:2604.18623v1 Announce Type: new Abstract: Scene Graph Generation (SGG) unifies object localization and visual relationship reasoning by predicting boxes and subject-predicate-object triples. Yet

Chroma1 is an 8.9B parameter text-to-image foundational model , with different versions including V48 (512x raw pretrained checkpoint) and variants like Chroma1-HD (mixed resolution finetune) . Chroma

arXiv:2503.07259v2 Announce Type: replace-cross Abstract: The goal of creating intelligent, human-centered wearable systems for continuous activity understanding faces a fundamental trade-off: Egocent

arXiv:2604.18701v1 Announce Type: cross Abstract: Local prediction-error-based curiosity rewards focus on the current transition without considering the world model's cumulative prediction error acros

arXiv:2604.19124v1 Announce Type: new Abstract: Existing detoxification methods for large language models mainly focus on post-training stage or inference time, while few tackle the source of toxicity

arXiv:2604.18963v1 Announce Type: cross Abstract: Knowledge distillation (KD) transfers capabilities from large language models (LLMs) to smaller students, yet it can fail unpredictably and also under

arXiv:2604.19339v1 Announce Type: new Abstract: Ultra-fine-grained visual categorization (Ultra-FGVC) aims to classify highly similar subcategories within fine-grained objects using limited training s

A Reddit discussion in the Stable Diffusion community asking about available LoRAs (low-rank adaptations) and fine-tuning options that can replicate the distinctive visual styles of Niji and Midjourne

arXiv:2604.19341v1 Announce Type: cross Abstract: Language models are increasingly used in scientific discovery to generate hypotheses, propose candidate solutions, implement systems, and iteratively

arXiv:2604.18953v1 Announce Type: new Abstract: Deep learning surrogates for CFD flow-field prediction often rely on large, complex models, which can be slow and fragile when data are noisy or incompl

Flux 2-Klein-9B NVFP4 is a quantized image generation model that runs on mid-range GPUs like the RTX 3050. On this hardware, the model produces 1024-resolution images but with relatively slow inferenc

When we launched Microsoft Agent Framework last October, we made a promise: building production-grade AI agents should feel as natural and structured as building any other software. Today, we’re deliv

arXiv:2604.19736v1 Announce Type: new Abstract: Conditional medical image generation plays an important role in many clinically relevant imaging tasks. However, existing methods still face a fundament

📽️ Go From Blockout To Final Render 🎤 Special Guest: Doug Hogan ⏲️ April 22nd – 1pm PST / 4pm EST 📍 Live on YouTube, X, and Twitch Today, Doug will walk his through his workflow for ComfyUI that uses

Seedance 2.0 is a ComfyUI tool or workflow that enables users to progress from initial blockout stages through to final rendered output in a streamlined process. The broadcast likely demonstrates the

GPT Image 2.0 just dropped in ComfyUI via Partner Nodes. This isn't another image model. It *reasons* before it generates. → Plans the composition → Checks its own work → Iterates instead of one-shott

arXiv:2604.19669v1 Announce Type: new Abstract: Enforcing constraint satisfaction in neural network outputs is critical for safety, reliability, and physical fidelity in many control and decision-maki

arXiv:2604.18866v1 Announce Type: new Abstract: Despite advances in object detection, aerial imagery remains a challenging domain, as models often fail to generalize across variations in spatial resol

arXiv:2603.20092v3 Announce Type: replace Abstract: Diffusion models generate structure by progressively transforming noise into data, yet the mechanisms underlying this transition remain poorly under

A user created a workflow to test multiple Stable Diffusion schedulers and samplers simultaneously, addressing common questions about which are optimal . The post likely demonstrates a comparative tes

arXiv:2604.19186v1 Announce Type: cross Abstract: Heterophily is a prevalent property of real-world graphs and is well known to impair the performance of homophilic Graph Neural Networks (GNNs). Prior

arXiv:2604.19240v1 Announce Type: new Abstract: Industrial surface defect detection often suffers from limited defect samples, severe long-tailed distributions, and difficulties in accurately localizi

arXiv:2604.19018v1 Announce Type: cross Abstract: Inference-time LLM alignment methods, particularly activation steering, offer an alternative to fine-tuning by directly modifying activations during g

arXiv:2604.18940v1 Announce Type: new Abstract: Autonomous driving systems often degrade under adverse visibility conditions-such as rain, nighttime, or snow-where online scene geometry (e.g., lane di

arXiv:2603.20530v2 Announce Type: replace-cross Abstract: Target localization is a prerequisite for embodied tasks such as navigation and manipulation. Conventional approaches rely on constructing exp

arXiv:2604.18765v1 Announce Type: cross Abstract: Fault detection and diagnosis are critical for the optimal and safe operation of industrial processes. The correlations among sensors often display no

arXiv:2602.01651v2 Announce Type: replace-cross Abstract: Why do neural networks fail to generalize addition from 16-digit to 32-digit numbers, while a child who learns the rule can apply it to arbitr

One prompt → up to 8 consistent images with character + object continuity across the set. Storyboards, turnarounds, and product variants in a single node, no seed gymnastics. Aspect ratios from 3:1 to

arXiv:2604.00555v2 Announce Type: replace Abstract: Enterprise adoption of Large Language Models (LLMs) is constrained by hallucination, domain drift, and the inability to enforce regulatory complianc

arXiv:2604.19399v1 Announce Type: new Abstract: Federated learning (FL) is a key paradigm for distributed model learning across decentralized data sources. Communication in each FL round typically con

arXiv:2603.29078v2 Announce Type: replace Abstract: We present PolarQuant, a post-training weight quantization method for large language models (LLMs) that exploits the distributional structure of neu

arXiv:2604.18995v1 Announce Type: cross Abstract: Diffusion Large Language Models (dLLMs) have emerged as a promising alternative to autoregressive generation by enabling parallel token prediction. Ho

arXiv:2601.04562v2 Announce Type: replace Abstract: Generative recommendation with large language models (LLMs) reframes prediction as sequence generation, yet existing LLM-based recommenders remain l

arXiv:2604.19025v1 Announce Type: new Abstract: Widespread RGB-Depth (RGB-D) sensors and advanced 3D reconstruction technologies facilitate the capture of indoor spaces, improving the fields of augmen

arXiv:2604.18966v1 Announce Type: cross Abstract: While language models have been adapted for tabular data generation, two fundamental limitations remain: (1) static fine-tuning produces models that c

arXiv:2503.23439v2 Announce Type: replace-cross Abstract: Spoken dialogue systems powered by large language models have demonstrated remarkable abilities in understanding human speech and generating a

arXiv:2510.24738v2 Announce Type: replace-cross Abstract: Running offers substantial health benefits, but improper gait patterns can lead to injuries, particularly without expert feedback. While prior

arXiv:2603.20897v3 Announce Type: replace-cross Abstract: The strong and continuous increase of AI-based services leads to the steady proliferation of AI data centres worldwide with the unavoidable es

The edit fidelity is the real unlock. Targeted changes stay targeted — colorize a photo or shift noon to dusk at up to 2K, and everything outside the edit zone stays pixel-stable. No more warped faces