Knowledge catalogue
arXiv:2602.19179v2 Announce Type: replace Abstract: Gaussian inference on smooth manifolds is central to robotics, but exact marginalization and conditioning are generally non-Gaussian and geometry-de
arXiv:2604.26557v1 Announce Type: cross Abstract: The increasing deployment of Large Language Model (LLM) inference on edge AI systems demands efficient execution under tight memory budgets. A key cha
arXiv:2604.26857v1 Announce Type: new Abstract: Deploying accurate object detection for Vulnerable Road User (VRU) safety on edge hardware requires balancing model capacity against computational const
arXiv:2512.18365v2 Announce Type: replace Abstract: Diffusion models have emerged as powerful priors for image editing tasks such as inpainting and local modification, where the objective is to genera
arXiv:2510.05174v4 Announce Type: replace-cross Abstract: When are multi-agent LLM systems merely a collection of individual agents versus an integrated collective with higher-order structure? We intr
arXiv:2604.25949v1 Announce Type: new Abstract: Reliable perception for robotics depends on large-scale labeled data, yet real-world datasets rely on heavy manual annotation and are time-consuming to
arXiv:2604.26470v1 Announce Type: new Abstract: Industrial systems increasingly depend on Machine Learning (ML), and operate on heterogeneous nodes that must satisfy tight latency, energy, and memory
arXiv:2601.03654v2 Announce Type: replace Abstract: In this study, we introduce a quantum computing method that incorporates Ridglet transforms into quantum processing pipelines for financial time-ser
Manus, an AI company Meta acquired for $2 billion last year is running ads promising quick, easy money with AI: Find local businesses without websites or with bad websites, have AI build them one, the
arXiv:2604.26261v1 Announce Type: new Abstract: Zero-shot 3D Visual Grounding (3DVG) is a critical capability for open-world embodied AI. However, existing methods are fundamentally bottlenecked by th
This Reddit thread likely discusses hardware recommendations and considerations for purchasing a new laptop capable of running Ollama, a tool that enables running large language models locally. The di
arXiv:2604.26472v1 Announce Type: cross Abstract: We study sequential interventions under prerequisite constraints. In this setting, admissible intervention sequences are paths in the ideal lattice of
arXiv:2603.05959v3 Announce Type: replace Abstract: Reconstructing 3D geometry from streaming video requires continuous inference under bounded resources. Recent geometric foundation models achieve im
Pi + @huggingface llamacpp + Qwen3.6 = 🔥🔥🔥🔥 turns out not killing the prefix cache all the time and notnhaving a humongous set of tools and a massive system prompt is good for local model use. who'd h
arXiv:2604.26318v1 Announce Type: new Abstract: Point cloud registration (PCR) is a fundamental task for integrating 3D observations in remote sensing applications. This paper proposes a fast and effe
arXiv:2604.26073v1 Announce Type: cross Abstract: Industrial chemical plants often operate under strict data confidentiality constraints, making centralized data-driven process modeling difficult. Fed
arXiv:2604.17612v2 Announce Type: replace-cross Abstract: Multi-agent systems built on large language models (LLMs) are difficult to reason about. Coordination errors such as deadlocks or type-mismatc
arXiv:2604.25936v1 Announce Type: cross Abstract: Implicit neural representations are powerful for geometric modeling, but their practical use is often limited by the high computational cost of networ
arXiv:2604.26394v1 Announce Type: cross Abstract: Recent advances in large language models and agentic frameworks have enabled virtual customer assistants (VCAs) for complex support. We present SecMat
arXiv:2604.26940v1 Announce Type: new Abstract: Small language models (SLMs) offer computational efficiency for scalable deployment, yet they often fall short of the reasoning power exhibited by their
arXiv:2604.26897v1 Announce Type: new Abstract: Origami-inspired robotic grippers have shown promising potential for object manipulation tasks due to their compact volume and mechanical flexibility. H
arXiv:2511.20032v3 Announce Type: replace Abstract: Visual attention serves as the primary mechanism through which MLLMs interpret visual information; however, its limited localization capability ofte
arXiv:2604.26553v1 Announce Type: cross Abstract: Large language models (LLMs) demonstrate strong multilingual capabilities, yet often fail to consistently generate responses in the intended language,
arXiv:2604.26837v1 Announce Type: new Abstract: Long-context LLM serving is bottlenecked by the cost of attending over ever-growing KV caches. Dynamic sparse attention promises relief by accessing onl
v0.22.1-rc1 is a pre-release version of Ollama that includes improvements to MLX sampler batching, tokenizer BPE offset handling, NVIDIA TensorRT Model Optimizer support, and fixes for desktop app sta
arXiv:2604.26806v1 Announce Type: cross Abstract: Transformer-based architectures have established a dominant paradigm in global semantic perception; however, they remain fundamentally constrained by
A community repository of AI agent configurations for Ollama has reached 888 GitHub stars, featuring pre-built setups and configurations for running AI agents locally. The project appears to focus on
This discussion covers training custom video LoRAs for Wan and LTX Video models using Low-Rank Adaptation, a fine-tuning technique that customizes outputs for specific subjects, styles, or movements w
arXiv:2604.26604v1 Announce Type: new Abstract: Federated learning (FL) trains a shared model from updates contributed by distributed clients, often implicitly assuming that contributing clients are r
b8969 is a release build of llama.cpp (commit bdc9c74), published on April 29, 2026. Llama.cpp is a C/C++ implementation designed to enable LLM inference with minimal setup and state-of-the-art perfor
b8970 is a release of llama.cpp, a C/C++ project for large language model inference. The naming convention using a build hash (b8970) is typical of llama.cpp's continuous release pattern rather than t
b8971 is a build release of llama.cpp, an open-source C/C++ project for LLM inference . As a numbered build identifier from the llama.cpp repository, this release likely contains bug fixes, performanc
b8972 is a release of llama.cpp, a C/C++ implementation for LLM inference . The release identifier follows llama.cpp's development versioning scheme with frequent builds published to the GitHub releas
b8973 is a release of llama.cpp that added SVE tuned code for the gemm_q8_0_4x8_q8_0() kernel and changed arrays to static const in repack.cpp . The llama.cpp project enables LLM inference with minima
b8978 is a release of llama.cpp, a project designed to enable LLM inference with minimal setup and state-of-the-art performance on a wide range of hardware. The llama.cpp project uses sequential build
B8979 is a llama.cpp release that added SVE (Scalable Vector Extension) tuned code for the gemm_q8_0_4x8_q8_0() kernel and made static const changes to repack.cpp . The release includes pre-built bina
b8981 is a release version of llama.cpp, a C/C++ implementation for LLM inference . Build versions in llama.cpp releases typically contain updates to the underlying ggml library, performance optimizat
arXiv:2604.25700v1 Announce Type: cross Abstract: Software quality assurance remains a major challenge in industrial environments, where large-scale and long-lived systems inevitably accumulate defect
Clement Delangue, CEO of Hugging Face, posted about receiving a piece of hardware that fits alongside a DGX Spark system, likely referring to an AI accelerator or GPU device. The post suggests a perso
arXiv:2604.25388v1 Announce Type: new Abstract: Architectural floor plans are widely available priors which contain not only geometry but also the semantic information of the environment, yet existing
arXiv:2604.24997v1 Announce Type: new Abstract: Open-vocabulary semantic segmentation requires assigning pixel-level semantic labels while supporting an open and unrestricted set of categories. Traini
arXiv:2604.25039v1 Announce Type: new Abstract: Large Language Models (LLMs) solve many reasoning tasks via chain-of-thought (CoT) prompting, but smaller models (about 7 to 8B parameters) still strugg
arXiv:2604.24972v1 Announce Type: new Abstract: Clinical abnormality grounding for rare diseases is often hindered by data scarcity, making supervised fine-tuning impractical and single-pass inference
arXiv:2604.25482v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown strong potential for narrative generation, but their use in complex, multi-layered role-playing game (RPG) world
Quanty AI is a local AI companion playground built with Ollama as the backend, featuring animated pixel art graphics and interactive micro fiction experiences. The project integrates agent skills to e
Wan2GP users can explore high-quality output modes like LTX 2 DEV HQ Mode, which is designed to produce better output at higher resolutions by using the HQ sampler with specific settings like 15 steps
📽️ Let's Explore Comfy Hub 🎤 Host: Purz ⏲️ April 29th – 3pm PST / 6pm EST 📍 Live on YouTube, X, and Twitch Today we're diving into Comfy Hub + Comfy Cloud — your gateway to exploring what's possible w
Comfy Hub appears to be an exploratory broadcast or presentation from the ComfyUI project shared via X (formerly Twitter). Based on the context, it likely discusses features, updates, or capabilities
arXiv:2604.25405v1 Announce Type: new Abstract: Camera-based 3D object detection and tracking are central to autonomous driving, yet precise 3D object localization remains fundamentally constrained by
arXiv:2604.25860v1 Announce Type: new Abstract: Machine-generated text (MGT) detection requires identifying structurally invariant signals across generation models, rather than relying on model-specif
MiMo-V2.5 is Xiaomi's multimodal AI model with native visual and audio understanding that supports up to 1 million tokens of context. The GGUF format refers to quantized versions of the model optimize
arXiv:2603.15954v2 Announce Type: replace Abstract: Real-time AI experiences call for on-device large language models (OD-LLMs) optimized for efficient deployment on resource-constrained hardware. The
The Ministral-3:3b model requires Ollama 0.13.1, which is in pre-release , and users encountering errors when running it face various issues including memory allocation problems and GPU/CPU offloading
arXiv:2511.20211v2 Announce Type: replace Abstract: Transparency-aware generation requires modeling not only RGB appearance but also alpha-based opacity and cross-layer composition, which are essentia
arXiv:2604.25276v1 Announce Type: new Abstract: Video Temporal Grounding (VTG), the task of localizing video segments from text queries, struggles in open-world settings due to limited dataset scale a
arXiv:2604.25551v1 Announce Type: new Abstract: Recurrent Graph Neural Networks (RGNNs) extend standard GNNs by iterating message-passing until some stopping condition is met. Various RGNN models have
arXiv:2604.24832v1 Announce Type: new Abstract: Masked diffusion language models (MDMs) have recently emerged as a promising alternative to standard autoregressive large language models (AR-LLMs), yet
arXiv:2601.21293v2 Announce Type: replace Abstract: Reliability-centered prognostics for rotating machinery requires early-warning signals that remain accurate under nonstationary operating conditions
Qwen3.6 27B is a 27-billion parameter language model that can achieve approximately 60 tokens per second throughput when running on dual RTX 5060 Ti GPUs with 16GB memory each, using the vLLM inferenc
arXiv:2604.05594v2 Announce Type: replace Abstract: Pixel-level annotation is costly in low-resource dermoscopy. We present RABC-Net, a reliability-aware annotation-free segmentation system that combi