Knowledge catalogue
arXiv:2606.01708v1 Announce Type: cross Abstract: We study fixed-confidence best-action identification (BAI) in stochastic minimax trees. This problem is increasingly relevant in modern AI planning, w
arXiv:2606.02120v1 Announce Type: cross Abstract: In this report, we address the problem of determining whether a user performs an action incorrectly from egocentric video data. To this end, we propos
arXiv:2606.01443v1 Announce Type: cross Abstract: A central difficulty in training Joint-Embedding Predictive Architectures (JEPAs) is preventing representation collapse. LeJEPA addresses this by enfo
Ollama 0.30 provides improved compatibility and performance using llama.cpp, augments the MLX engine on Apple Silicon for broader hardware support, and brings support for a wider range of models inclu
arXiv:2606.00109v1 Announce Type: cross Abstract: Coronary guidewire endpoint localization is a fundamental capability for computer-assisted PCI, and its importance increases as robot-assisted PCI is
arXiv:2606.00704v1 Announce Type: new Abstract: Real-world image super-resolution (Real-ISR) requires balancing structural fidelity to degraded observations with realistic detail synthesis. However, e
arXiv:2606.02096v1 Announce Type: new Abstract: Dynamic scene reconstruction from monocular videos remains highly challenging, as existing methods often struggle to balance global structural coherence
arXiv:2602.11208v2 Announce Type: replace Abstract: The Earth's subsurface is a cornerstone of modern society, providing essential energy resources like hydrocarbons, geothermal, and minerals while se
arXiv:2605.30604v1 Announce Type: cross Abstract: Regulated cybersecurity workflows lack a runtime substrate that enforces organization-level scope across retrieval, tool calls, memory, findings, repo
arXiv:2605.31022v1 Announce Type: new Abstract: Predictive coding (PC) is a local-learning alternative to backpropagation (BP), training deep networks via local energy-minimization dynamics rather tha
b9451 is the latest release of llama.cpp, published on June 1, 2026 . Llama.cpp is an LLM inference project implemented in C/C++ that enables efficient local execution of large language models. This r
llama.cpp b9452 is a release of the LLM inference C/C++ project from the ggml-org repository. This release likely includes updates to the software's core functionality, bug fixes, or new features that
llama.cpp release b9453 added support for EXAONE 4.5 model implementations with vision capabilities, including markers, projector paths, and routing through a Qwen2.5-VL-style encode path with window
Release b9455 is a build of llama.cpp, a C/C++ implementation for LLM inference . This release represents a specific commit or version update to the llama.cpp project, which is used for running large
Release b9459 is a version of llama.cpp, the C/C++ implementation for LLM inference. The specific release would contain bug fixes, optimizations, or new features for the llama.cpp project, which enabl
Release b9464 is a version of llama.cpp, a project that enables LLM inference with minimal setup and state-of-the-art performance on a wide range of hardware. This specific release likely contains upd
arXiv:2605.31050v1 Announce Type: new Abstract: Gaussian process-based Bayesian optimization (BO) is a popular approach for expensive black-box optimization, but its performance often degrades on comp
arXiv:2605.30734v1 Announce Type: cross Abstract: Malaria remains a leading cause of mortality in sub-Saharan Africa, where scarce diagnostic infrastructure makes timely, accurate diagnosis particular
arXiv:2510.14904v3 Announce Type: replace-cross Abstract: Dense Video Object Captioning (DVOC) is the task of jointly detecting, tracking, and captioning object trajectories in a video, requiring the
arXiv:2605.30668v1 Announce Type: cross Abstract: Dialogue topic segmentation is critical in many human-AI collaborative applications which requires identifying heterogeneous boundary cues, including
Cosmos3-Super-Image2Video is an omnimodal world model capable of generating video from combinations of text and image inputs . The model is designed to run on workstation-grade compute like the NVIDIA
arXiv:2605.30901v1 Announce Type: new Abstract: Counterfactual explanations (CEs) are essential for actionable recourse, yet their reliability is often compromised in low-density regions, where classi
arXiv:2509.25906v2 Announce Type: replace Abstract: Federated Learning (FL) often adopts differential privacy (DP) to protect client data, but the added noise required for privacy guarantees can subst
arXiv:2605.30873v1 Announce Type: cross Abstract: Federated Learning (FL) offers a privacy-preserving pathway for aligning Large Language Models (LLMs); however, existing frameworks typically enforce
arXiv:2605.31446v1 Announce Type: cross Abstract: Aspect Sentiment Triplet Extraction (ASTE) aims to identify aspect terms, opinion terms, and sentiment polarities as structured triplets, providing es
arXiv:2605.31215v1 Announce Type: cross Abstract: Masked Generative Models (MGMs) enable parallel decoding and achieve strong performance across modalities, but require full-sequence bidirectional tra
arXiv:2605.31317v1 Announce Type: new Abstract: Machine unlearning aims to remove the influence of selected training examples without full retraining. Standard evaluations often summarize unlearning q
arXiv:2605.30387v1 Announce Type: cross Abstract: Functional Magnetic Resonance Imaging (fMRI) provides non-invasive access to dynamic brain activity by measuring blood oxygen level-dependent (BOLD) s
arXiv:2603.10468v2 Announce Type: replace-cross Abstract: We study timestamped speaker-attributed automatic speech recognition (SA-ASR) for long-form, multi-party speech with overlap. In this setting,
arXiv:2601.19936v2 Announce Type: replace-cross Abstract: The opacity of massive pretraining corpora in Large Language Models (LLMs) raises significant privacy and copyright concerns, making pretraini
Getting Started: 1. Update ComfyUI to the latest version [] 2. Open the Template library, then search for TripoSplat 3. Follow the note in the workflow to download models 4. Load an image, then run th
arXiv:2601.19966v2 Announce Type: replace-cross Abstract: We introduce ELECTRAFI, a fast, end-to-end differentiable model for predicting periodic charge densities in crystalline materials. ELECTRAFI c
arXiv:2605.31464v1 Announce Type: cross Abstract: GPU kernels are the workhorse of modern deep learning, and optimizing them (via evolutionary search or coding agents) usually requires repeated measur
arXiv:2603.23398v2 Announce Type: replace-cross Abstract: Generative modeling of discrete data, such as graphs, underpins many scientific and industrial applications, including molecular discovery and
Ollama Cloud enables running large language models without a powerful GPU by offloading them to Ollama's cloud service . However, recent reports document significant reliability issues, including freq
arXiv:2511.15692v2 Announce Type: replace Abstract: This paper introduces SS-MixNet, a lightweight and effective deep learning model for hyperspectral image (HSI) classification. The architecture inte
A developer created a local application that automatically themes an entire 100-card Magic: The Gathering deck and generates custom card artwork using FLUX and ComfyUI, enabling users to apply consist
A comprehensive comparison study of 62 different samplers and 16 schedulers used in WAN 2.1 image generation, with systematic quality ratings to help users understand which combinations produce the be
I'd need to search for current information about LTX2.3 and V2V workflows to provide you with an accurate summary. LTX-2.3 V2V (video-to-video) workflows enable users to recreate specific sections wit
arXiv:2605.31096v1 Announce Type: new Abstract: While visually grounded Chain-of-Thought (CoT) has emerged as a promising paradigm to enhance fine-grained perception in multimodal large language model
arXiv:2602.18837v2 Announce Type: replace Abstract: Despite their theoretical advantages, spectral methods based on the graph Fourier transform (GFT) are seldom used in graph neural networks (GNNs) du
arXiv:2605.30592v1 Announce Type: new Abstract: We study the problem of assigning a scalar score to a short trajectory window that reflects its position on an ordered continuum of predictability regim
arXiv:2605.31158v1 Announce Type: new Abstract: Interactive video world models generate video chunk by chunk in response to user-controlled camera movements, enabling applications such as real-time ga
arXiv:2605.31492v1 Announce Type: new Abstract: Large language models (LLMs) often solve reasoning problems by generating intermediate traces that explore and revise partial solutions. From a search p
arXiv:2605.31167v1 Announce Type: new Abstract: Assessing whether Large Language Models outputs are factually grounded, epistemically calibrated, and methodologically reproducible is a prerequisite fo
This Reddit post from r/StableDiffusion likely curates May 2026 AI news highlights, including releases like Stable Audio 3.0, a model family for artistic experimentation with open-weight models. The p
arXiv:2605.30476v1 Announce Type: cross Abstract: We study privately estimating the sum of n user-held values in the presence of an honest-but-curious server. This motivates requiring privacy not only
arXiv:2605.30936v1 Announce Type: new Abstract: We study the problem of learning Gaussian mixture models under overparameterization. Prior work has shown that while overparameterization is essential f
arXiv:2603.04946v2 Announce Type: replace Abstract: In local-life service platforms, query suggestion reduces user effort by generating candidate queries from input prefixes. Traditional multi-stage s
This Reddit post discusses techniques for using Stable Diffusion 1.5's img2img feature to enhance and improve generated images through upscaling, adding detail, and sharpening. The post likely contain
# May Wrapped Blog Summary ComfyUI's May Wrapped blog post provides a monthly recap of updates, features, and community highlights from May, likely covering new node additions, workflow improvements,
arXiv:2605.30526v1 Announce Type: cross Abstract: Aligned language models often exhibit a recognizable AI-like style, yet its connection to post-training and internal representations remains poorly un
arXiv:2602.13069v2 Announce Type: replace-cross Abstract: On-device fine-tuning enables privacy-preserving personalization of large language models, but mobile devices impose severe memory constraints
MiniMax M3 launched on June 1, 2026 as the first open-weights model to combine frontier coding, a 1-million-token context window, and native multimodality. The model achieves top-tier performance on c
arXiv:2511.19433v2 Announce Type: replace-cross Abstract: Vision-language-action (VLA) models have shown remarkable capabilities in robotic manipulation, but their performance is sensitive to the extb
Minimax-M3 is a model available through Ollama's model library, accessible at ollama.com/library/minimax-m3. The model was promoted or announced via Ollama's official X (Twitter) account, indicating i
arXiv:2509.00834v2 Announce Type: replace Abstract: This paper addresses the problem of suffix prediction in Business Process Management (BPM) by proposing a Neuro-Symbolic Predictive Process Monitori
Personal agents are exploding in popularity, with open source projects like OpenClaw and Hermes seeing rapid adoption by AI developer communities on GitHub. Built to adapt to individual preferences an
arXiv:2605.31460v1 Announce Type: new Abstract: Reasoning-based robotic policies using large language and vision-language models achieve strong semantic planning capabilities but mostly suffer from a
arXiv:2605.30880v1 Announce Type: cross Abstract: Text-agent environments are typically modeled as partially observable Markov decision processes (POMDPs), assuming that the simulator's latent state a