Knowledge catalogue
arXiv:2603.16141v2 Announce Type: replace-cross Abstract: Autonomous Unmanned Aerial Vehicle (UAV) swarms are increasingly used as rapidly deployable aerial relays and sensing platforms, yet practical
arXiv:2608.05743v1 Announce Type: new Abstract: Few-shot industrial anomaly detection (FS-IAD) focuses on detecting and localizing visual defects in industrial inspection during the cold-start phase,
arXiv:2608.05844v1 Announce Type: new Abstract: Radiology foundation models learn transferable representations that can be adapted to new tasks by training only small layers on top of a frozen encoder
arXiv:2608.05358v1 Announce Type: new Abstract: Federated learning repeatedly incurs local optimization and model-update transmission. We study DG-FedReuse, a simulator-level mechanism that allows sel
arXiv:2608.05893v1 Announce Type: new Abstract: Electrocardiography (ECG) is one of the most widely used non-invasive tools for diagnosing cardiovascular disease, but transforming multi-lead ECG recor
arXiv:2608.05303v1 Announce Type: cross Abstract: On-device deployment of Large Language Models (LLMs) has become essential for personalized edge applications. A primary bottleneck is external memory
arXiv:2608.05920v1 Announce Type: new Abstract: Recent advances in neural scene representations enable photorealistic novel-view synthesis, yet most methods remain tightly coupled to a single renderin
arXiv:2608.06227v1 Announce Type: cross Abstract: Despite advances in artificial intelligence (AI) across multiple sectors, today's AI tools, including deep learning and generative AI, still fail when
arXiv:2608.05704v1 Announce Type: new Abstract: Dense colored LiDAR maps provide accurate city-scale geometry, but lifting them into 3D Gaussian Splatting (3DGS) retains millions of primitives, making
arXiv:2608.05237v1 Announce Type: cross Abstract: Current few-step autoregressive video diffusion models depend on previous fully denoised clean frames as context for all denoising steps of the curren
arXiv:2608.05490v1 Announce Type: new Abstract: Autonomous agents now carry out entire data analyses, selecting cohorts, joining tables, and fitting models with little step-by-step supervision. When s
arXiv:2608.05718v1 Announce Type: new Abstract: Unmanned aerial vehicle (UAV) photogrammetry requires camera networks that provide sufficient surface coverage, image overlap, parallax, and resolution,
Live now: our Local AI Track from AI Engineer World's Fair 2026, brought to you by @nvidia. Thesis: frontier intelligence is becoming something you own. https://www.youtube.com/watch?v=KB41dTlX1Uc&lis
Hi there! I've messaged the Ollama support team 4 times with no response in 3 weeks. This is getting ridiculous. Does anyone have any recommendations as to how I should seek support? I don't want to i
High-performance inference of NVIDIA's Parakeet TDT 0.6B V2 English transcription model, in the browser. Check out the live demo: https://parakeet.narcotic.sh/ A fully custom, dependancy-free implemen
I'm considering replacing a single RTX 3090 with two ASRock AMD Pro R9700s for about 2900 new out of the door. That would move me from 24GB to 64GB VRAM. Yes yes, CUDA/ROCm, but the real problem is po
arXiv:2608.06170v1 Announce Type: cross Abstract: Hierarchical 3D scene graphs are a promising representation for high-level spatial reasoning in autonomous mobile platforms. However, existing extract
arXiv:2608.06240v1 Announce Type: cross Abstract: Unpaired image-to-image translation must decide, per image, what to change and what to preserve without paired supervision. Many diffusion-based unpai
arXiv:2606.16278v3 Announce Type: replace-cross Abstract: Long-tail hazardous scenarios are essential for safety-oriented autonomous driving, yet they are difficult to collect at scale. Editable 3D Ga
arXiv:2608.06275v1 Announce Type: new Abstract: Oral health issues affect billions globally, but the cost and limited access to professional dental care hinder preventive oral healthcare. Research rel
arXiv:2608.06021v1 Announce Type: new Abstract: Effective Visual Localization (VL) requires a map of the environment that combines compactness for efficient scalability with robustness against visual
arXiv:2607.21910v2 Announce Type: replace Abstract: World models let agents plan against predicted physical state, but that state drifts; re-observation is costly and delayed, and repair can fail. We
arXiv:2608.05365v1 Announce Type: new Abstract: This paper presents an observation-only autonomy framework for Unmanned Underwater Vehicles (UUVs) navigation in dynamic underwater environments that in
arXiv:2608.06307v1 Announce Type: new Abstract: LiDAR-based Scene Coordinate Regression (SCR) maps point clouds directly to 3D scene coordinates, enabling precise 6-DoF localisation without explicit m
arXiv:2608.05663v1 Announce Type: new Abstract: Real-time long-form avatar audio--video generation requires causal, continuous synthesis while maintaining audiovisual synchronization and visual consis
📝 Introduction We present Wan-Animate-2, a novel end-to-end character animation framework that directly consumes driving videos in a redesigned Diffusion Transformer, which achieves high-fidelity moti
For a long time now, the most popular posts on LocalLLaMA have been either about using LLM in the cloud or about politics. I suspect that people using local models are about 10% now. You can say that
arXiv:2608.05670v1 Announce Type: new Abstract: A model's agreement across perturbed inputs is used both as a label-free reliability signal and as a self-training target, on the premise that agreement
arXiv:2608.05168v1 Announce Type: new Abstract: Large language models often fail on reasoning tasks despite possessing the capability to solve them. We argue that many such failures arise from localiz
arXiv:2608.05369v1 Announce Type: cross Abstract: Vision-language-action (VLA) models often treat main-view and wrist-view observations as parallel visual inputs, overlooking their distinct roles in r
Actual is a local inference stack optimized to let you utilize your personal compute. With its low CPU impact while inferencing and multi-platform portability, it’s a great pair for your local Hermes
https://preview.redd.it/kihat320ashh1.png?width=1672&format=png&auto=webp&s=a7ccc40ba3fb229ac7ebf57e8e6a314e0ee45646 Hi r/StableDiffusion! u/New-Requirement1419 -> dacongya (Head of H3 Researcher) u/A
arXiv:2608.04458v1 Announce Type: new Abstract: Agentic AI is emerging in datacenters, but its architectural implications remain unexplored. We organize agentic workflows in a taxonomy and present its
Looking for best current solutions for combining cloud models and local models seamlessly inside a harness' orchestration Edit: Right now, we don't have harnesses (that I'm aware of) that are blending
arXiv:2509.07654v2 Announce Type: replace Abstract: Small moving target detection is crucial for many defense applications but remains highly challenging due to low signal-to-noise ratios, ambiguous v
arXiv:2510.17709v2 Announce Type: replace-cross Abstract: Training Reinforcement Learning (RL) policies using simulation models before deployment in real-world environments is a common strategy when r
arXiv:2608.04968v1 Announce Type: new Abstract: The capabilities of an LLM agent depend not only on its model but on the harness: the executable program that constructs context, invokes tools, verifie
arXiv:2604.01693v2 Announce Type: replace Abstract: Video object removal aims to erase target objects while reconstructing visually plausible and temporally coherent content. However, target objects o
So I can either pull the trigger on a 128gb AI max+ 395 laptop or wait for RTX Spark for LLMs. Maybe I get it now and the price of the spark is super high so it's a good purchase or maybe the Spark sh
[Fully open source under GPL3, made from the ground up for use with local models, no subscriptions, no corporate backing] When i first started this, it was meant to be a fully lightweight, extremely m
arXiv:2608.04121v1 Announce Type: cross Abstract: Vision-based guidance of unmanned aerial vehicles (UAVs) toward unmanned ground vehicles (UGVs) supports cooperative aerial--ground robotics, but reli
I built this because the existing benchmarks were using random data and with MTP content types can vary a lot on what performance you see. 5% or more with content types. BetterBench is designed to hav
arXiv:2608.05122v1 Announce Type: new Abstract: Vision transformers (ViTs) have become the de facto standard for image encoding across many perception tasks. Despite their empirical success, it remain
arXiv:2607.09290v2 Announce Type: replace-cross Abstract: In the digital era, Portable Document Format (PDF) is one of the most widely used file formats for storing and exchanging digital documents du
arXiv:2608.05016v1 Announce Type: cross Abstract: Predicting the existence and type of links (edges) between nodes in a multi-relational graph is key for applications from social interaction predictio
Salve a tutti. Sto valutando di mettere dei modelli locali, magari su LM studio o altro software se mi spiegate il perché da utilizzare sia come PT sia per Soc L2/L3. Ho un PC con 128 GB RAM ddr5 8gb
arXiv:2608.05076v1 Announce Type: cross Abstract: Recent advances in machine learning have enabled training of wireless foundation models, which aim to support tasks such as channel estimation, beam p
arXiv:2608.04193v1 Announce Type: cross Abstract: Language models (LMs) offer strong textual representations for electronic health records (EHRs), but they encode patient sequences in isolation and pr
arXiv:2608.04124v1 Announce Type: cross Abstract: Video question answering requires models to ground language queries in visual evidence and, when necessary, reason over that evidence across time. Exi
arXiv:2603.06140v2 Announce Type: replace-cross Abstract: Video object insertion is fundamental to video editing, yet existing diffusion methods often produce visually plausible but physically inconsi
arXiv:2608.04995v1 Announce Type: new Abstract: Animal pose estimation and tracking is important for wildlife monitoring and conservation research, and with limited expert time for labelling automated
arXiv:2608.05064v1 Announce Type: cross Abstract: Small open-weight language models increasingly run in private, offline, and cost-sensitive settings, where the key deployment question is not only wha
arXiv:2608.05110v1 Announce Type: cross Abstract: Near-term quantum hardware limits circuit depth and often imposes geometrically local connectivity for quantum generative models, restricting the outp
arXiv:2607.21597v2 Announce Type: replace Abstract: Evaluating wildfire risk systems using standard machine-learning metrics such as F1-score or IoU is fundamentally flawed: these metrics assess event
arXiv:2608.04692v1 Announce Type: cross Abstract: Task-vector arithmetic offers a closed-form way to modify a model, yet its behavioral locality remains unclear in closed-loop robot control. We presen
arXiv:2608.04698v1 Announce Type: cross Abstract: We tackle the challenging yet underexplored task of Generalized Referring Expression Comprehension (GREC), which requires a model to localize the obje
arXiv:2608.04864v1 Announce Type: cross Abstract: We introduce the neural echo as a tool for understanding the behavior of neural networks. It generalizes the model-based concepts of impulse responses
arXiv:2608.04759v1 Announce Type: cross Abstract: Although Multimodal Large Language Models (MLLMs) have made substantial progress, their spatial reasoning may still produce intermediate judgments inc
arXiv:2608.04405v1 Announce Type: cross Abstract: Long-context large language models (LLMs) are increasingly deployed in real-world applications, yet self-attention remains a major efficiency bottlene
daily reminder not to trust benchmarks and run it yourself. claimed e2e speedup is ~40%, forwards are ~140% faster I would wager that compared to a naive kernel anyone can write it's more in the range