Search: “local-ai”

Decoupling Cross-Modality Manifold Discrepancy: Leveraging Visible Diffusion Priors for Infrared Super-Resolution

arXiv:2607.21174v1 Announce Type: new Abstract: Infrared image super-resolution (IISR) mitigates the limitations imposed by low spatial resolution. Existing methods have recognized that IISR should pr

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Local Ai

Delivery, Not Storage: Cue-Anchored Working Memory as a Harness Property for Coding Agents

DGX agent

arXiv:2607.20972v1 Announce Type: new Abstract: Coding agents ship with one kind of memory: documents. Instruction files, plan artifacts, and auto-written memory directories are deliberately authored

local-aiarxiv-cs-ai

24 Jul 2026

Detecting LLM-Generated Tokens in Human--LLM Coauthored Text

arXiv:2607.21458v1 Announce Type: new Abstract: The rise of human-AI collaborative writing has created a growing need for fine-grained detection methods that support localizing likely LLM-generated co

Does Ollama Cloud prompt caching even work?

I launched a new session and tasked GLM to create an implementation plan for a spec. The plan was on the bigger side, about 5k lines. I started with 0% 5h used and ended with 80% used. A few more twea

Enabling Scalable Topology Inference in Distribution Systems via Constrained Multi-Source Inference

arXiv:2607.20480v1 Announce Type: new Abstract: Accurate distribution system topology is essential for outage localization, voltage analytics, and operation of distribution grids, yet maintaining reli

Encode Once, Decode Never: Reusing Audio LM Internals for Efficient Temporal Localization

arXiv:2602.10230v2 Announce Type: replace Abstract: Audio language models process input audio into rich frame-level representations, but the standard approach to temporal localization generates timest

ExecuGraph: A Multi-Agent, Execution-Grounded Framework for Reliable Backend Code Synthesis with Large Language Models

arXiv:2607.20499v1 Announce Type: new Abstract: Large Language Models generate plausible backend code, but a single-pass paradigm provides no guarantee of correctness or runtime reliability. We presen

Explain love in one sentence...

Love is an active commitment of deep affection where you find genuine joy in prioritizing someone else’s well-being as deeply as or beyond your own needs. VS Love is the deep, enduring connection betw

FLUX 3 - Real World Models: Towards Multimodal Flow Models as the Backbone of Visual Intelligence

Introducing FLUX 3. One multi-modal model for Image, Video, Audio and Action-Prediction. Creations are truer to life in every kind of style. Blog Post : https://bfl.ai/blog/flux-3 submitted by /u/pmtt

From Dependency to Compositionality: A Neurosymbolic Lifting of LLM Outputs via Combinatory Categorial Grammar

arXiv:2607.18961v2 Announce Type: replace Abstract: Large language models (LLMs) generate fluent text by incrementally predicting the next token from a prefix. Critics in the generative tradition argu

Hardware-Software Co-Design for Float16 On-Device Training on RISC-V Single-Core

arXiv:2607.21130v1 Announce Type: cross Abstract: By leveraging standard RISC-V extensions, namely Zfh (scalar float16) and Zvfh (vector float16), this work proposes an open-source framework to enable

Hugging Face releases The Stack v3 – largest open code dataset yet

From Anton Lozhkov on 𝕏: https://x.com/anton_lozhkov/status/2080254608639701222 Two ways in: stack-v3-train - near-deduplicated, quality-filtered, PII-redacted, contents inline. Point load_dataset at

Information-Theoretically Secure Aggregation for Lightweight Federated Learning: Resilient to Dropouts and Adversaries

arXiv:2607.20890v1 Announce Type: new Abstract: On-device federated learning (FL) enables privacy-preserving and personalized model training on resource-constrained devices such as smartphones and IoT

Is corruption the lobbying against Open weights?

Like, reading things like Anthropic 'donated' to some people with the condition of lobbying against Chinese LLMs.. it's that right? It feels nothing like freedom but at the same time it's said 'out lo

Is everyone training a single model together, based on the principle of the Tor network?

I just had a thought while scrolling. No idea if this already exists. What if users trained an AI model together—a bit like the Tor network or Bitcoin mining back in the day? - Participants download a

It appears that the anti opensource AI lobby is far outgunned already

The earlier post on this subreddit by 20+ companies signing the petition including Microsoft, Meta, Nvidia, YC (https://www.microsoft.com/en-us/corporate-responsibility/topics/open-weight/) etc plus t

Machine Learning for Charge State Characterization of Isolated Double Quantum Dots

arXiv:2607.20871v1 Announce Type: cross Abstract: Scaling semiconductor quantum dot arrays toward fault-tolerant quantum computing requires efficient tuneup of spin qubits, a process that depends on t

Minimum Bayes Risk Decoding for Error Span Detection in Reference-Free Automatic Machine Translation Evaluation

arXiv:2512.07540v4 Announce Type: replace-cross Abstract: Error Span Detection (ESD) extends automatic machine translation (MT) evaluation by localizing translation errors and labeling their severity.

More than 20 companies including NVIDIA, Meta, Microsoft, Palantir, and Hugging Face have signed a letter urging policymakers to avoid premature restrictions on open weight models.

The Open Letter was initiated by Microsoft and published today: “Open Weights and American AI Leadership”. It argues against broad or premature restrictions on open-weight models and explicitly says p

MSBraM: A Multi-scale Self-supervised Brain Foundation Model for Hierarchical EEG Dynamics Learning

arXiv:2607.21402v1 Announce Type: new Abstract: Self-supervised foundation models have recently shown strong potential for electroencephalogram (EEG)-based analysis. However, existing approaches strug

Naju: A Native Discrete State-Space Model with Independent Retention and Writing for Long-Sequence Memory

arXiv:2607.21000v1 Announce Type: new Abstract: Long-sequence memory tracking places two opposing demands on a recurrent state: near-lossless retention of stored bindings over long horizons, and activ

No sé nada de Ollama, ni programación ni idea, pero estoy creando un agente evolutivo

Con ayuda de ChatGPT y con el modelo de Ollama, Qwen3:14b estoy creando un agente que corre local y tiene la iniciativa para pensar, investigar, aprender, generar propuestas y esperar mi autorización

Open models matter. Ollama works hard with the model creators, hardware partners, and most importantly developers building software leveragi…

Open models matter. Ollama works hard with the model creators, hardware partners, and most importantly developers building software leveraging various open models for their own use cases. For my first

local-aiollama--x

Open weights = freedom. You can run them on your own hardware. No vendor can pull the plug. No API can deprecate you. No company logs your p…

Open weights = freedom. You can run them on your own hardware. No vendor can pull the plug. No API can deprecate you. No company logs your private data. That's sovereignty. Closed models hand one comp

local-aifireworks-ai--x

Overcoming the Communication-Performance Tradeoff in LLM Pretraining

arXiv:2508.15706v3 Announce Type: replace Abstract: Communication-efficient distributed training algorithms (e.g., DiLoCo) have received considerable interest due to their benefits for training large

Quick Demo of the new Auto-Control feature in my Open-Source App that monitors stuff on your screen using local LLMs, so you don't have to :))

TLDR: This is a demo of my open-source app which now auto-controls itself so you can monitor your downloads, renders, progress bars, or whatever's on your screen and camera :) Hey r/ollama !! I'm deve

RadioTrace: Transmitter-Aware Diffusion for Radio Map Estimation without Deployment-Time Fine-Tuning

arXiv:2607.20909v1 Announce Type: cross Abstract: Radio map (RM) estimation aims to reconstruct the spatial distribution of wireless signal characteristics, such as received signal strength (RSS), fro

REFACT: Adaptive Fact Restatement for Compact and Faithful Chain-of-Thought Reasoning

arXiv:2607.20833v1 Announce Type: new Abstract: Large language models increasingly rely on long-form reasoning for complex tasks, yet their reasoning traces may drift away from the supplied context wh

local-aiarxiv-cs-cl

Representation Robustness Under Executable Reasoning Constraints in Large Language Models for Mathematical Problem Solving

arXiv:2607.20520v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly evaluated on mathematical problem solving, yet prior work often treats representationally equivalent formu

Rethinking Open-World Video Anomaly Detection: Diagnosing Definition Blindness

arXiv:2607.20780v1 Announce Type: new Abstract: Open-world video anomaly detection (OWVAD) is expected to detect events that match a user-specified definition of abnormality. This requirement is stron

Routing Without Training: Controllable-Ratio LLM Offloading via Reliability Gating

arXiv:2607.20481v1 Announce Type: new Abstract: Local-cloud collaboration is a practical way to deploy large language models under resource constraints, but existing methods often rely on trained rout

Spectral Transformation for Layer-wise Global Rank Discovery in Federated LoRA for Vision Transformers

arXiv:2607.21074v1 Announce Type: new Abstract: Fine-tuning Vision Transformers (ViTs) with low-rank adapters (LoRA) promises better communication efficiency under federated setup, yet existing aggreg

Spent two weeks on a kernel that benchmarked 29x faster. End to end it's maybe 6-10%, and it's not even wired in yet.

I've been building a C99 inference engine from scratch (no Python, no BLAS, just gcc and make) that runs BitNet's ternary models on CPU. A few weeks ago I got obsessed with the matmul kernel - wrote a

Test-Time Scaling via Error Localization

arXiv:2607.21453v1 Announce Type: new Abstract: Scaling inference-time computation has emerged as a reliable method to improve the performance of large language models on complex reasoning and program

The demand for GLM-5.2 and other frontier-level open models has been surging on Ollama's cloud. We're adding capacity in anticipation for so…

The demand for GLM-5.2 and other frontier-level open models has been surging on Ollama's cloud. We're adding capacity in anticipation for some very large models next week! To make sure Ollama's infras

local-aiollama--x

Toward Continuous Assurance for the Democratization of AI Agent Creation in Industry

arXiv:2607.21495v1 Announce Type: new Abstract: AI agents are increasingly created inside organizations by non-engineering users through low-code, no-code, and conversational development environments.

Towards Privacy-Preserving Federated Prompt Tuning under Data Heterogeneity: A Subspace-Decomposed Expert Approach

arXiv:2607.21417v1 Announce Type: new Abstract: Federated prompt tuning (FPT) enables collaborative adaptation of vision--language models (VLMs) using lightweight prompts. Existing methods often addre

VibeVoice-ASR-BitNet Technical Report

arXiv:2607.21075v1 Announce Type: cross Abstract: We present VibeVoice-ASR-BitNet, a compressed variant of VibeVoice-ASR optimized for real-time inference on edge CPUs. We apply heterogeneous quantiza

local-aiarxiv-cs-cl

What I learned using Ollama on a real Paperless archive: model choice was not the main problem

I maintain Tagvico, an open-source companion for Paperless-ngx. I added Ollama because document text is exactly the kind of data many people do not want to send to a hosted model. The surprising failu

What's the last model trained on human-data only?

From my understanding, most current LLMs are trained on trillions and trillions of tokens of mostly AI-generated data. Are there any recent models that are trained purely (or as close as possible) on

which model to use on local 24gb mac mini M4 pro

So, i have been building some apps that should run on the local every user system, tried gemma4 although its fast and great at reasoning its not as good in instructions following and tool calling. tri

Wisdom of LLM Crowds: Aggregation and Contamination in Language Model Ensembles

arXiv:2607.18269v2 Announce Type: replace Abstract: The wisdom of crowds -- the finding that aggregating judgments across individuals often outperforms the best individual -- has been extensively stud

A caveman qwen3.6 27B

Just saw this on huggingface: https://huggingface.co/ProCreations/grug-27b The benchmarks claim that it's quite a bit better than qwen3.6 27B original and that they reduced the amount of necessary tok

A local-first harness for multi-agent workflows

Hey all, I’ve been working on this in my spare time and finally feel ready to share it outside my own circles. Arbiter is a single binary for running agents locally. I originally built it because I wa

ABot-World-0: Infinite Interactive World Rollout on a Single Desktop GPU

arXiv:2607.19191v1 Announce Type: new Abstract: We present ABot-World-0, an action-conditioned video world model for real-time, long-horizon closed-loop interaction, supported by a multi-source data i

Absurd claim: the distilled model outperforms the originals

As an AI community of LLM experts, are we really going to stay silent while US officials make absurd claims to push anti-consumer laws? Not only does the release timeline between Fable and K3 make hig

Active Inference as a Convex Markov Decision Process

arXiv:2607.20152v1 Announce Type: cross Abstract: Active Inference (AIF) frames adaptive behavior as the minimization of expected free energy (EFE), combining epistemic and pragmatic objectives within

AdaHome: An Adaptive Smart Home Assistant using Local Small Language Models

arXiv:2607.18034v2 Announce Type: replace Abstract: Smart home assistants interpret a wide range of user commands, from explicit device control to underspecified and preference dependent requests. Whi