Knowledge catalogue
arXiv:2607.20142v1 Announce Type: new Abstract: We present a two-stage vision system that detects EEG cap electrodes in a live webcam stream and validates their anatomical placement in real time. A si
arXiv:2607.20116v1 Announce Type: new Abstract: Global visual localization of unmanned aerial vehicles (UAVs) using remote-sensing reference maps has attracted increasing attention. However, acquisiti
arXiv:2607.19877v1 Announce Type: new Abstract: Weakly supervised segmentation relies heavily on class activation maps (CAMs) to initially localize target regions. However, CAMs are often noisy and pr
arXiv:2607.20162v1 Announce Type: new Abstract: The growing demand for intelligent processing at the edge of IoT networks is constrained by the severe computational and memory limitations of microcont
arXiv:2607.20274v1 Announce Type: cross Abstract: Medical image encoders from different groups are increasingly treated as interchangeable, on the assumption that scale and clinical supervision concen
arXiv:2607.20159v1 Announce Type: new Abstract: Attention Mechanism (AM) selectively focuses on essential information for imaging tasks and captures relationships between distant pixel neighborhoods t
When trying to access the models folder on /usr/share/ollama, I'm asked to authenticate as sudo, which weirdly enough, fails. I type my password, which I'm sure is correct since I use it several time
arXiv:2607.19524v1 Announce Type: cross Abstract: Federated learning (FL) offers a promising approach to privacy-preserving clinical risk prediction, but its deployment remains limited by restricted d
arXiv:2607.19973v1 Announce Type: new Abstract: AI researchers describe state-of-the-art models as one thing repeated at scale: the Transformer, wired identically for text, pixels, or speech. Neurosci
Not Self Promotion: Just sharing an open-source tool I built to democratize image to 3D creations. For OpenAI Build Week Hackathon I built a free, open-source local Image-to-3D Studio that makes TRELL
arXiv:2607.20115v1 Announce Type: new Abstract: Large language models (LLMs) are known to be sensitive to prompt and input formulations. However, existing studies have focused on lexical realization a
What interface do you use, and what’s the most frustrating part of using it? Specific examples would be especially helpful. I’m working on an Ollama interface and want to understand which real problem
arXiv:2607.20027v1 Announce Type: new Abstract: Short-term Heart Rate Variability (HRV) forecasting could provide clinicians with actionable lead time for detecting autonomic dysfunction and adverse c
A fun AI video effect to try: balance on top of a moving animal while pulling off impossible tricks. This ComfyUI workflow uses an LLM to generate the right Seedance 2.0 prompts, making it easy to rec
Guys, this is my current opencode.jsonc ``` { '$schema': 'https://opencode.ai/config.json', // Start in plan mode 'default_agent': 'plan', // Use OpenRouter as the provider for GLM 5.2 'model': 'openr
Hi everyone, I have access to a self-hosted (or third-party) LLM that exposes an OpenAI-compatible API. I have both the API URL and an API token, and the provider states that it's fully compatible wit
I installed OpenCode and an Ollama model (qwen3.5) sucessfully connected the model respond in OpenCode but doesn't find My MCP server, i Made one using fastMCP other models like bigPickle and openai m
Let me try to explain this clearly, simply, and neatly. Originally, I just wanted to build a small WebUI adapter with an admin panel, but things escalated over the last few months. At first, I faced t
Nativ: Run AI models locally on your Mac Prince Canuma is the developer behind the excellent MLX-VLM Python library for running vision-LLMs using MLX on a Mac. I'm really excited about his new project
I've been considering Ollama's Cloud Max plan to replace my GLM Max plan but couldn't find good documentation on how their limits actually translate into GLM 5.2 usage. I know it's by GPU time but tha
This release introduces native Computer Use for Windows and macOS, allowing Row-Bot to interact with desktop applications while keeping the user firmly in control. Computer Use is opt-in and protected
The **v0.32.2‑rc1** release (commit 4d1b53e, signed with a GPG key) introduces server-side logic to detect download stalls that occur before any data is received. It also removes the stall‑timeout set
This refactors the existing integration tests into 3 priumary groups: fast, release, and library. It also refines some of the release tests to drop some of the older models and pick up newer models, w
Vibe coding isn't just for your PC anymore. Here's LLM Hub generating and previewing code entirely on an iPhone. Everything runs locally. Using the RunAnywhere SDK, Timmy Qian ported LLM Hub, an Andro
A fun AI video effect: ride a living animal like it's a skateboard. This ComfyUI workflow uses an LLM to generate optimized Seedance prompts, making the effect easy to recreate without all the prompt
Erin Davis calls it the “SuperDuperPOD.” That’s two things in one name: pharmaceutical giant Bristol Myers Squibb (BMS) already runs one of the largest AI clusters in life sciences, with serious resul
**Release v0.32.2‑rc0 (commit de1ce45)** adds support for Compute Capability 10.0 in the Linux “CUDA v12” preset, enabling B200‑class GPUs to use the `cuda_v12` backend even when drivers do not meet t
I have a 48GB M5 Pro and have far too many development projects going that just don't need the power of Anthropic to churn through so have started looking into running local models and while it certai
arXiv:2607.13237v1 Announce Type: new Abstract: Precise spatial-temporal annotation of laparoscopic videos is time-consuming and requires expert knowledge. We propose a human-in-the-loop knowledge acq
arXiv:2607.13738v1 Announce Type: cross Abstract: Background and Objective: Deep video models estimate left-ventricular ejection fraction (EF) from echocardiography with near-expert accuracy, and post
arXiv:2607.10188v2 Announce Type: replace Abstract: Breast cancer remains the most commonly diagnosed malignancy among women worldwide, yet accurate detection and characterization of breast masses in
arXiv:2511.11949v2 Announce Type: replace Abstract: Federated learning (FL) is a powerful paradigm for distributed learning, but increasing model complexity leads to significant energy consumption fro
arXiv:2607.13265v1 Announce Type: new Abstract: Physically based differentiable rendering has proven to be a powerful tool for inverse rendering problems (e.g., 3D reconstruction, reflectance estimati
arXiv:2607.13093v1 Announce Type: cross Abstract: On-device LLM inference faces a trilemma of response latency, limited hardware resources and user privacy. Full cloud inference delivers strong comput
arXiv:2607.13045v1 Announce Type: cross Abstract: Federated Learning (FL) has emerged as a key paradigm for privacy-preserving collaborative model training across distributed and heterogeneous data so
arXiv:2607.13454v1 Announce Type: cross Abstract: Although multimodal large language models (MLLMs) have achieved remarkable progress, understanding 3D spatial relationships from 2D images remains a c
arXiv:2607.13960v1 Announce Type: new Abstract: World Action Models (WAMs) improve robot policy learning by jointly modeling actions and future visual observations, using future scene evolution as den
arXiv:2607.13285v1 Announce Type: new Abstract: The capability of a modern AI agent depends not only on its foundation model but also on its harness, which constructs prompts, manages state, invokes t
arXiv:2607.13072v1 Announce Type: cross Abstract: Zero-shot object-goal navigation aims to enable an intelligent agent to explore and navigate to objects of unknown categories in an unfamiliar environ
arXiv:2607.13432v1 Announce Type: new Abstract: Plasticity -- a neural network's ability to adapt to new tasks -- is critical for continual and transfer learning. Existing measures, such as effective
arXiv:2603.06228v2 Announce Type: replace Abstract: Event cameras provide sequential visual data with spatial sparsity and high temporal resolution, making them attractive for low-latency object detec
arXiv:2607.13826v1 Announce Type: cross Abstract: Accurate determination of pancreatic ductal adenocarcinoma (PDAC) resectability relies on evaluating how the tumor interacts with major peripancreatic
Open models are already being used in the enterprise. Over 85% of the Fortune 500 companies already use Ollama to fulfill specific tasks. @jmorgan Why open models and Ollama? Ownership. Open models ar
arXiv:2606.15587v2 Announce Type: replace Abstract: Expert demonstrations are widely assumed to be the gold standard for robot imitation learning. Yet for fine-grained manipulation such as insertion,
arXiv:2607.13371v1 Announce Type: new Abstract: Accurate estimation of landfast sea ice roughness is critical for climate modeling and safe Arctic over-ice travel, yet existing approaches rely on cost
arXiv:2607.13111v1 Announce Type: cross Abstract: Distinguishing semantic-preserving commits from changing ones remains an open challenge in software repository mining. While existing approaches detec
arXiv:2607.13444v1 Announce Type: new Abstract: Structural damage in modular spacecraft can disrupt mechanical and communication connectivity, reducing system capability. Existing approaches rely on r
arXiv:2607.13880v1 Announce Type: new Abstract: In underwater covert cooperative missions, autonomous underwater vehicles (AUVs) often cannot rely on active sonar to continuously obtain complete infor
arXiv:2607.13101v1 Announce Type: cross Abstract: Global Station Weather Forecasting (GSWF) is pivotal for localized and extreme weather prediction over key regions. Despite efforts to exploit look-ba
arXiv:2607.13584v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) trained through unsupervised Spike-Timing-Dependent Plasticity (STDP) have been explored as solutions to visual loop cl
arXiv:2607.13674v1 Announce Type: new Abstract: Existing iterative stereo matching methods primarily adopt two types of correspondence representation: explicit matching search via correlation volumes
arXiv:2607.12640v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards, and Group Relative Policy Optimization (GRPO) in particular, is now run routinely on a supervised checkp
arXiv:2607.12886v1 Announce Type: new Abstract: Clinical notes contain many of the signs and symptoms that bring patients to care, yet this information rarely reaches structured fields. Existing extra
arXiv:2607.12110v1 Announce Type: new Abstract: Ground segmentation is a fundamental prerequisite for autonomous navigation, environmental perception, and object detection in ground mobile platforms.
arXiv:2607.10183v2 Announce Type: replace-cross Abstract: Running large language models on consumer devices such as laptops and desktops is challenging because model weights often exceed GPU memory ca
arXiv:2607.11962v1 Announce Type: new Abstract: Self-supervised learning offers a compelling approach for medical imaging, where labeled data are scarce and acquisition costs are high. We present COJE
After over a year in development, ExLlamaV3 has had its first production release. Turboderp has been pulling 10 hour days with Fable to bring us this massive batch of improvements. Check out detailed
arXiv:2606.16847v3 Announce Type: replace-cross Abstract: Diffusion Large Language Models (dLLMs) offer a promising avenue for parallel generation but face a trade-off between decoding speed and quali
arXiv:2607.12962v1 Announce Type: cross Abstract: Frozen small code LLMs are deployed locally, yet the information guiding a retry after a failed attempt is still measured without placebo controls in
arXiv:2607.11588v2 Announce Type: replace Abstract: We present FoundationGeo, a two-stage framework that explicitly bridges relative and metric prediction via spatial calibration and principled data d