Knowledge catalogue
arXiv:2609.28366v1 Announce Type: cross Abstract: Vision-language models (VLMs) offer a promising approach to long-tail autonomous driving, but existing driving datasets provide limited supervision fo
Hi. I’m developing my first Python project (been at it a couple weeks). I built a very basic CLI ollama client. When a user sends a prompt I append the message to session['history'], save the sessio
arXiv:2609.26828v1 Announce Type: cross Abstract: NAND-backed storage offers the capacity needed to scale LLM prefix caching, but its block I/O path incurs CPU cache contention and host-DRAM staging i
arXiv:2609.28328v1 Announce Type: new Abstract: Accurate localization of the bronchoscope within the bronchial tree is essential for clinicians to be able to reach target lesions, perform biopsies and
Closed model, open model, or train your own? 📅 Wed, Oct 7 🕐 5 PM 📍 San Francisco At our next AI Talk, Crusoe’s @ErwanM94707 joins @ollama's @jmorgan and @trajectorylabs's @MichaelElabd to explore this
arXiv:2609.27469v1 Announce Type: new Abstract: Controlling the shape of a continuum soft robot typically requires an accurate dynamic model and actuation of all degrees of freedom. We show that regul
arXiv:2609.27994v1 Announce Type: cross Abstract: Financial institutions are beginning to deploy agentic workflows in credit, fraud, collections, compliance, and operational control. Governance remain
arXiv:2609.28299v1 Announce Type: new Abstract: Contact-implicit trajectory optimization formulates contact-rich manipulation as a single constrained program; however, that single program run collapse
arXiv:2609.28247v1 Announce Type: cross Abstract: Large Language Models (LLMs) introduce an exciting new paradigm for planning and navigation in robotics, but fail on even simple multi-robot tasks as
arXiv:2609.27702v1 Announce Type: cross Abstract: A camera and an IMU are the minimal sensor setup for metric localization and dense mapping, yet classical visual--inertial filters must wait for paral
arXiv:2609.28131v1 Announce Type: new Abstract: Synthesizing realistic articulated hand-object interactions is a fundamental problem in virtual reality, embodied intelligence, and digital human applic
arXiv:2609.27040v1 Announce Type: cross Abstract: Multi-GPU servers have become the standard building block of modern data centers, providing aggregated capacity through high-bandwidth interconnects.
arXiv:2607.10128v3 Announce Type: replace Abstract: Recursive models show promise on reasoning and language tasks, yet their test-time scaling lacks a principled criterion for selecting trajectories o
arXiv:2609.27118v1 Announce Type: new Abstract: Greenhouse climate management aims to improve crop production while limiting energy use. This requires knowing how a crop will respond before conditions
arXiv:2609.27779v1 Announce Type: new Abstract: Class-guided 3D object generation is important for intelligent content creation, virtual environments, and digital asset design. Although 3D Gaussian Sp
arXiv:2609.27018v1 Announce Type: new Abstract: Residual vector quantization (RVQ) turns physiological waveforms into compact token sequences, but conventional masked modeling treats every incorrect t
arXiv:2609.27156v1 Announce Type: new Abstract: Large reasoning models can produce correct yet unnecessarily long reasoning traces. Existing methods improve reasoning efficiency with trajectory-level
arXiv:2609.27695v1 Announce Type: new Abstract: Perceiving objects in the environment is a fundamental capability of autonomous robots. In dark or low-light environments, external cameras often fail t
Hi - I want to build a home server for Ollama. I want to connect to the server via my laptop and mobile devices to do research and run agents. What is recommended to get this going ? submitted by /u/R
Hey everyone, A major issue when building test environments or fine-tuning pipelines is balancing data realism with privacy. Pasting real internal/client data into cloud endpoints is a massive complia
I was having trouble searching and analyzing the different models that Ollama has available ( https://ollama.com/library ). I wanted to filter for specific model sizes and tooling capabilities, so I b
arXiv:2609.28015v1 Announce Type: cross Abstract: Data assimilation estimates a dynamical state from partial and noisy observations. Classical ensemble filters are efficient but restrict analysis upda
Enterprises are increasingly standardizing on Google Kubernetes Engine (GKE) to run their most critical and AI-driven workloads. From Cloud Storage FUSE for high-throughput data access to custom compu
Just trained Tev1 0.8B, a tiny Jev-like classifier. Here it is running completely locally on my mac with @ollama & classifying some tasks. It's extremely fast: only ~50ms E2E latency. Video is not spe
arXiv:2609.27509v1 Announce Type: new Abstract: Stereo visual SLAM systems built on local descriptors suffer from semantic ambiguity, instance-level confusion, and independently moving objects, each c
arXiv:2609.28086v1 Announce Type: cross Abstract: We propose LAYERSCOPE, a label-free, layerwise framework that aims to characterize a model's learned representations in video and multimodal settings.
I’ve been experimenting with local AI lately, and one thing I’m finding interesting is what comes after getting a model running. Ollama makes local model access pretty straightforward, but for an actu
arXiv:2609.27959v1 Announce Type: cross Abstract: We investigate a local spectral-complexity representation for perceptual image quality assessment (IQA) based on Shannon entropy of singular values co
arXiv:2505.04417v3 Announce Type: replace Abstract: Diffusion models are state-of-the-art tools for various generative tasks. Yet training these models involves estimating high-dimensional score funct
arXiv:2609.27523v1 Announce Type: new Abstract: Breast image classification requires local detail and global tissue context, yet these cues can weaken as representations deepen. We present M3D-Net, a
Hello Everyone! Good news for anyone who can compile code on apple, you can now experience using a AMD Radeon AI Pro R9700 on a MacBook Pro or Mac mini, Mac Studio or any OSX variant as long as it has
Guys I have a M4-mac air with 24 GB unified memory and I wanna run some local LLM model on my machine Currently I am working on building and RAG application which is mostly and QnA system but I wanna
arXiv:2609.26924v1 Announce Type: new Abstract: Radiological artificial intelligence has advanced rapidly, yet most systems remain narrowly task-specific, data-intensive, and fragile under domain shif
arXiv:2609.28393v1 Announce Type: new Abstract: World models are useful for robotic manipulation because robots can predict how actions change the states of objects before executing them. We present P
arXiv:2609.27378v1 Announce Type: cross Abstract: End-to-end speech-to-speech dialogue models listen and speak simultaneously, so a continuously open acoustic channel is exposed to adversarial manipul
arXiv:2609.28425v1 Announce Type: cross Abstract: Recursive state estimation often executes approximate numerical solutions inside a feedback loop, where highly accurate local steps do not guarantee b
arXiv:2505.10080v3 Announce Type: replace-cross Abstract: Scrambling quantum systems have attracted attention as effective substrates for temporal information processing. Here we consider a quantum re
arXiv:2609.27289v1 Announce Type: cross Abstract: Conventional Japanese automatic speech recognition (ASR) is supervised by an orthographic transcript, although the same written form can correspond to
arXiv:2609.27463v1 Announce Type: new Abstract: Distributed model predictive control (DMPC) often constructs both predictions and collision constraints from neighbor trajectories, so packet loss can r
arXiv:2609.27149v1 Announce Type: new Abstract: Remote sensing change detection requires both global reasoning across bitemporal images and precise localization of changed regions. However, dense atte
Been building some multi-agent pipelines recently and the degradation in direct execution is insane. Whenever I pass a strict operational variable or hypothesis, the LLM triggers this 'Devil's Advocat
arXiv:2609.26972v1 Announce Type: new Abstract: Training Universal Differential Equations (UDEs) traditionally relies on backpropagating through numerical ODE solvers, creating memory footprints far e
arXiv:2609.28184v1 Announce Type: cross Abstract: Robotic operation in previously unseen environments requires both semantic understanding and reliable metric information. While vision--language model
I am creating a local AI agent called 'Ontelic' for Windows. Ontelic returns to Ollama and also manipulates the actual Chrome. This is not for promotion but to share what we've learned. I'll give GitH
arXiv:2609.24348v1 Announce Type: cross Abstract: AI coding agents increasingly support software development beyond code completion, including planning, implementation, testing, and repository-level t
arXiv:2609.23953v1 Announce Type: new Abstract: AI agents that carry a multi-step computer task through on their own became ordinary tools in the past year, and the same autonomy is available to anyon
arXiv:2609.25891v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) often struggle with fine-grained visual perception when processing complete images, as critical evidence may on
arXiv:2609.23152v1 Announce Type: cross Abstract: Recently proposed self-supervised audio encoders learn powerful general-purpose representations of sound scenes, yet they are spatially blind. To supp
arXiv:2609.26704v1 Announce Type: new Abstract: Large language models increasingly tackle hard reasoning problems by spending more test-time compute, yet the dominant strategy remains naive repeated s
arXiv:2609.25916v1 Announce Type: new Abstract: Mixed-precision weight quantization is commonly formulated as a Multiple-Choice Knapsack Problem (MCKP), yet existing solvers rely on scalar sensitivity
arXiv:2609.26214v1 Announce Type: new Abstract: We present a methodology that places a 3D digital twin (DT) of the environment as the main enabler behind the development of radio sensing at scale. The
arXiv:2609.26460v1 Announce Type: new Abstract: Anomaly detection systems are often trained using normal data alone, while model selection and evaluation typically require labeled anomalies. We study
arXiv:2511.15371v3 Announce Type: replace Abstract: Assessing the importance of individual features in Machine Learning is critical to understand the model's decision-making process. While numerous me
arXiv:2609.25264v1 Announce Type: new Abstract: Cosserat rod models for soft robots usually construct sectional stiffness by summing material properties over a common cross-section. This assumption be
arXiv:2609.24174v1 Announce Type: new Abstract: Long-horizon language agents receive sparse terminal feedback, while intermediate rubrics provide structured but potentially misspecified assessments of
arXiv:2609.26658v1 Announce Type: cross Abstract: Integrating heterogeneous datasets within data lakes is a critical challenge, particularly for semantically related tables that lack the explicit attr
arXiv:2609.26423v1 Announce Type: new Abstract: This paper introduces Dr-LiSA, a first-of-its-kind direct method for localizing 2D spinning radar intensity measurements in SE(3) against 3D lidar maps.
arXiv:2609.25131v1 Announce Type: new Abstract: Uniform discrete flow permits repeated updates at every generation position. While continued revision supports correction of wrong tokens, it also expos
arXiv:2606.22886v2 Announce Type: replace Abstract: Objective: This study aims to improve the reliability and robustness of medical named entity recognition (NER) in Chinese atopic dermatitis (AD) cli
arXiv:2609.25373v1 Announce Type: new Abstract: On-device assistants require function-calling models that map natural language to local system actions, but existing resources emphasize web APIs or nar