b9832
B9832 is a build release of llama.cpp from the ggml-org project , which is a free and open-source tool that allows you to run AI models locally on Windows, Linux and macOS . The release likely contain
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B9832 is a build release of llama.cpp from the ggml-org project , which is a free and open-source tool that allows you to run AI models locally on Windows, Linux and macOS . The release likely contain
Release b9833 is a build of llama.cpp, an open-source project for LLM inference in C/C++. This release represents an incremental update within the llama.cpp development cycle, following the standard r
Ends Tuesday. Top winners each get $ + DGX Spark + Stripe credits. The Hermes Agent Accelerated Business Hackathon presented by @NVIDIAAI × @stripe × @NousResearch starts now, for builders making agen
MASSIVE NEWS has partnered with NVIDIA to advance local AI deployment as a default option, addressing the shift toward on-device and edge AI processing rather than cloud-dependent models. This collabo
b9822 is a release of llama.cpp, a project for LLM inference in C/C++ . As a build version in the ongoing development sequence of the llama.cpp project, this release likely includes bug fixes, perform
The search results show information about other llama.cpp releases and the project generally, but do not contain specific details about release b9824. Based on the available information about llama.cp
b9825 is a release of llama.cpp, the C/C++ implementation for large language model inference . This build represents an intermediate version in the ongoing development of llama.cpp, part of the ggml-o
B9826 is a release of llama.cpp, an LLM inference project written in C/C++ . llama.cpp enables users to run large language models on consumer hardware without expensive GPUs or cloud infrastructure .
Release b9827 of llama.cpp, released on June 27, 2026, added a cudaMemcpy2DAsync fast path to ggml_cuda_cpy for improved CUDA tensor copying performance. When tensors are not fully contiguous but each
B9828 is a llama.cpp release featuring OpenCL flash attention improvements, including reworked FA kernels for f16 and f32, prefill prepass kernels, and FA kernels for q4_0 and q8_0 quantization format
Ornith is a model available through the Ollama library, a platform for running large language models locally. The specific capabilities and parameters of this model can be found on its dedicated model
arXiv:2606.27304v1 Announce Type: new Abstract: Guided wave-based structural health monitoring (GWSHM) with onboard transducers offers significant potential for the early diagnosis of damage in engine
arXiv:2606.26585v1 Announce Type: new Abstract: With the gradual introduction of AI into telescope scheduling, AI-based decision-making has shown advantages in handling complex multi-constraint proble
arXiv:2606.26881v1 Announce Type: cross Abstract: We introduce an accelerated Langevin-based sampling method that is based on two complementary devices: SamAdams adaptive timestepping, which automatic
arXiv:2606.26452v1 Announce Type: new Abstract: To minimize privacy concerns and inference latency on edge devices like smartphones, lightweight on-device models remain important for end-user applicat
b9810 is a release build of llama.cpp, an open-source software library that performs inference on various large language models such as Llama. The build identifier follows the project's versioning sch
b9811 is a release of llama.cpp , an open-source C/C++ project for running large language model inference. The release likely includes performance improvements, bug fixes, and optimizations to the cor
Based on available search results, I cannot find specific details about the b9814 release. However, b9814 is a build version identifier from the ggml-org/llama.cpp repository, which is a C/C++ impleme
B9816 is a release build number for llama.cpp, an open-source project that enables efficient large language model inference in C/C++ on consumer hardware. This release likely contains bug fixes, perfo
Release b9820 of llama.cpp introduces scheduler optimizations to reduce synchronizations during split compute and improves CUDA performance with fewer synchronizations between tokens. The update inclu
b9821 is the latest release of llama.cpp, a C/C++ implementation of LLM inference, which includes updates to allow the application to support --version, --licenses, and --help flags . Pre-built binari
arXiv:2606.26891v1 Announce Type: cross Abstract: Concept Bottleneck Models (CBMs) promise transparent reasoning by predicting through human-interpretable concepts, yet their effectiveness fundamental
arXiv:2409.17754v2 Announce Type: replace-cross Abstract: Federated Learning (FL) emerges as a distributed machine learning approach that addresses privacy concerns by training AI models locally on de
arXiv:2505.09854v3 Announce Type: replace Abstract: As end-user device capability increases and demand for intelligent services at the Internet's edge rises, distributed learning has emerged as a key
arXiv:2606.27377v1 Announce Type: cross Abstract: Modern image generation demands a single model that unifies diverse capabilities, including text-to-image (T2I), local editing, and global editing. Ho
arXiv:2606.26686v1 Announce Type: new Abstract: In order to screen a prompt or a response, the recent guardrail methods generate a chain-of-thought (CoT) before they issue a verdict. This design follo
arXiv:2606.26121v1 Announce Type: cross Abstract: Global insect population declines necessitate scalable, continuous monitoring systems, yet existing vision-based solutions remain constrained by high
arXiv:2508.17916v2 Announce Type: replace Abstract: Depth estimation is a foundational component for 3D reconstruction in minimally invasive endoscopic surgeries. However, existing monocular depth est
arXiv:2606.26217v1 Announce Type: cross Abstract: Joint-Embedding Predictive Architectures (JEPAs), including recent LeWorldModel (LeWM), have become a promising foundation for reconstruction-free vis
arXiv:2606.26880v1 Announce Type: new Abstract: Language-model representations provide structured, high-dimensional annotations of naturalistic language stimuli and can serve as informative neural pre
ComfyUI announced a livestream event scheduled for Monday, June 29th at 9am PST, likely to showcase new product launches or feature updates. The event was promoted via their official X (Twitter) accou
arXiv:2606.27136v1 Announce Type: new Abstract: For LLM agents in multi-step interactive environments, a key challenge is to make effective use of accumulated interaction experience. Existing work has
arXiv:2602.07533v2 Announce Type: replace Abstract: Reward models are critical for reinforcement learning from human feedback, as they determine the alignment quality and reliability of generative mod
arXiv:2606.26828v1 Announce Type: new Abstract: Accurate seedling detection during early growth stages is essential for timely replanting and effective crop management in precision agriculture. Howeve
arXiv:2606.26333v1 Announce Type: new Abstract: Reinforcement learning in large or sparse-reward environments suffers from slow temporal-difference reward propagation, as value information spreads onl
arXiv:2606.26392v1 Announce Type: new Abstract: Reinforcement learning (RL) for locomotion frequently converges to locally optimal but undeployable behaviors, such as vibrating limbs or scooting on th
arXiv:2606.26520v1 Announce Type: cross Abstract: Mammalian cell-culture processes underpin the manufacture of many biopharmaceuticals, yet keeping a run on track is hard: critical process parameters
arXiv:2606.27325v1 Announce Type: new Abstract: Recent advances in action-conditioned world models show promising progress in modeling complex interactions and forecasting future states under diverse
now seems like a good day to remind people we have an apache 2.0 coding model you can run with 20 gigs of ram locally for free forever. https://huggingface.co/CohereLabs/North-Mini-Code-1.0-w4a16 Its
arXiv:2606.26403v1 Announce Type: new Abstract: Foundation-model research increasingly needs data about people: user state, personal histories, relationships, contact-like fields, documents, and longi
arXiv:2606.27084v1 Announce Type: new Abstract: Reliable organ localization in abdominal CT can provide spatial priors for downstream trauma analysis. We propose CT-3GDINO, a lightweight 3D detector t
arXiv:2606.26822v1 Announce Type: new Abstract: Federated Learning (FL) has become a foundational paradigm for privacy-preserving distributed intelligence, yet its scalability remains fundamentally co
arXiv:2606.26341v1 Announce Type: new Abstract: Many robotics problems, including trajectory optimization, inverse kinematics, and contact-rich motion planning, reduce to nonlinear programs (NLPs). Ma
SITUATION EXPLAINED: 70% of frontier model queries could run locally for free. @ClementDelangue, co-founder and CEO of @huggingface: 'There was an interesting study from Stanford published last year s
arXiv:2606.26487v1 Announce Type: cross Abstract: Large language models (LLMs) are attractive for context-aware time series forecasting because they can integrate heterogeneous textual signals, yet th
arXiv:2606.26511v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) gives agents access to accumulated knowledge, but has no model of time. When a fact changes (e.g., a function is
arXiv:2606.26664v1 Announce Type: cross Abstract: Existing homomorphic encryption (HE)-based GNN systems adopt a graph-centric paradigm that couples per-query cost to global graph size, limiting evalu
arXiv:2606.25156v1 Announce Type: new Abstract: Modern large language models based on softmax scaled-dot-product attention are constrained by their training sequence length: as the key-value sequence
arXiv:2606.25253v1 Announce Type: new Abstract: Highlights provide a concise summary of the main contributions of an academic paper and help readers quickly understand its focus. However, many journal
b9786 is a release of llama.cpp, a tool for LLM inference in C/C++ . Llama.cpp is a free and open-source tool that allows users to run AI models locally on Windows, Linux, and macOS . The b9786 releas
B9787 is a build release of llama.cpp, an open-source C/C++ implementation for LLM inference created by Georgi Gerganov. The llama.cpp project enables large language model inference with minimal setup
Release b9789 of llama.cpp includes a fix for quantizing mixture-of-experts models with MTP (multi-token prediction) . Binaries are provided for multiple platforms including macOS, Linux, Android, and
arXiv:2606.25556v1 Announce Type: new Abstract: Stepwise group-based RL is an attractive way to train long-horizon LLM agents without a learned critic: it reuses multiple sampled rollouts to estimate
arXiv:2606.25508v1 Announce Type: new Abstract: Histopathological tissue segmentation is essential for computer-aided diagnosis, yet weakly supervised methods often suffer from noisy pseudo-labels gen
arXiv:2606.25524v1 Announce Type: cross Abstract: Large language models (LLMs) reach high accuracy in mathematical reasoning, but individual traces on the same problem diverge; some arrive at the corr
arXiv:2512.05394v2 Announce Type: replace Abstract: Latent diffusion models pair VAEs with diffusion backbones, and the structure of VAE latents strongly influences the difficulty of diffusion trainin
arXiv:2606.25354v1 Announce Type: new Abstract: Test-time scaling improves language-model reasoning, but existing approaches often face a difficult trade-off: long chain-of-thought sampling remains si
arXiv:2606.24941v1 Announce Type: cross Abstract: Reviewing recorded interviews for affective cues such as composure, hesitation and agitation is slow and subjective, and cloud services that could aut
arXiv:2506.21091v2 Announce Type: replace Abstract: Stereo matching has become an increasingly important component of modern autonomous systems. Developing deep learning-based stereo matching models t
arXiv:2606.25941v1 Announce Type: cross Abstract: Increasing demand for precise and reliable control in complex scenarios has led to the development of increasingly sophisticated controllers, includin