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A Mixture of Experts Vision Transformer for High-Fidelity Surface Code Decoding

arXiv:2601.12483v2 Announce Type: replace-cross Abstract: Quantum error correction is a key ingredient for large scale quantum computation, protecting logical information from physical noise by encodi

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AgenticCache: Cache-Driven Asynchronous Planning for Embodied AI Agents

DGX agent

arXiv:2604.24039v1 Announce Type: cross Abstract: Embodied AI agents increasingly rely on large language models (LLMs) for planning, yet per-step LLM calls impose severe latency and cost. In this pape

local-aiarxiv-cs-ai

28 Apr 2026

AI use in American newspapers is widespread, uneven, and rarely disclosed

arXiv:2510.18774v4 Announce Type: replace Abstract: AI is rapidly transforming journalism, but the extent of its use in published newspaper articles remains unclear. We address this gap by auditing a

local-aiarxiv-cs-cl

b8953

Release b8953 of llama.cpp adds Q1_0 quantization support for WebGPU, including fast matmul and matvec kernels and optimized shared memory initialization. The release was published on April 28 and inc

b8954

llama.cpp is a C/C++ implementation for LLM inference. Build b8954 is a release version from the ggml-org/llama.cpp repository that likely includes bug fixes, optimizations, or new features added sinc

b8957

b8957 is a release of llama.cpp that includes spec parameter refactoring changes , featuring modifications to parameter handling and model specifications. The llama.cpp project enables LLM inference w

b8958

b8958 is a release of llama.cpp, a C/C++ library for LLM inference . The project uses rapid release cycles with frequent version tags tracking incremental updates and improvements to the codebase. Thi

b8960

B8960 is a build release of llama.cpp, an open-source C/C++ project for running large language models locally with minimal setup and optimized performance across various hardware platforms. It is one

b8963

B8963 is a build release of llama.cpp, the C/C++ implementation of LLM inference. Llama.cpp is an open-source project that enables efficient language model execution on consumer hardware with minimal

b8964

b8964 is a release of llama.cpp, a C/C++ library for LLM inference . The release likely includes bug fixes, performance optimizations, or new features as part of the project's continuous development c

b8966

b8966 is one of the latest releases in the llama.cpp project , a C/C++ implementation for efficient LLM inference. This release represents an intermediate development build in the llama.cpp repository

b8967

llama.cpp b8967 is an intermediate build release of llama.cpp, a C/C++ implementation for LLM inference with minimal setup and state-of-the-art performance. The project follows a rapid release cycle w

Benchmarking Source-Sensitive Reasoning in Turkish: Humans and LLMs under Evidential Trust Manipulation

arXiv:2604.24665v1 Announce Type: cross Abstract: This paper investigates whether source trustworthiness shapes Turkish evidential morphology and whether large language models (LLMs) track this sensit

Breaking the Resource Wall: Geometry-Guided Sequence Modeling for Efficient Semantic Segmentation

arXiv:2604.23399v1 Announce Type: new Abstract: High-performance semantic segmentation has achieved significant progress in recent years, often driven by increasingly large backbones and higher comput

CF-VLA: Efficient Coarse-to-Fine Action Generation for Vision-Language-Action Policies

arXiv:2604.24622v1 Announce Type: cross Abstract: Flow-based vision-language-action (VLA) policies offer strong expressivity for action generation, but suffer from a fundamental inefficiency: multi-st

CNN-ViT Fusion with Adaptive Attention Gate for Brain Tumor MRI Classification: A Hybrid Deep Learning Model

arXiv:2604.23137v1 Announce Type: cross Abstract: Early detection and classifying brain tumors using Magnetic Resonance Imaging (MRI) images is highly important but difficult to extract in medical ima

Code Broker: A Multi-Agent System for Automated Code Quality Assessment

arXiv:2604.23088v1 Announce Type: cross Abstract: We present Code Broker, a multi agent system built with Google Agent Development Kit ADK that analyses Python code from files, local directories, or G

DeepSignature: Digitally Signed, Content-Encoding Watermarks for Robust and Transparent Image Authentication

arXiv:2604.23016v1 Announce Type: cross Abstract: AI-powered generative models have significantly expanded the possibilities for editing, manipulating, and creating high-quality images. Particularly,

Deployment-Aligned Low-Precision Neural Architecture Search for Spaceborne Edge AI

arXiv:2604.24492v1 Announce Type: cross Abstract: Designing deep networks that meet strict latency and accuracy constraints on edge accelerators increasingly relies on hardware-aware optimization, inc

Domain-Filtered Knowledge Graphs from Sparse Autoencoder Features

arXiv:2604.23829v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) extract millions of interpretable features from a language model, but flat feature inventories aren't very useful on their ow

DYMAPIA: A Multi-Domain Framework for Detecting AI-based Video Manipulation

arXiv:2604.24426v1 Announce Type: new Abstract: AI-generated media are advancing rapidly, raising pressing concerns for content authenticity and digital trust. We introduce DYMAPIA, a multi-domain Dee

EXACT: an explainable anomaly-aware vision foundation model for analysis of 3D chest CT

arXiv:2604.24146v1 Announce Type: new Abstract: Chest computed tomography (CT) is central to the detection and management of thoracic disease, yet the growing scale and complexity of volumetric imagin

Explaining Temporal Graph Predictions With Shapley Values

arXiv:2604.24078v1 Announce Type: new Abstract: Temporal Graph Neural Networks (TGNNs) have become increasingly popular in recent years due to their superior predictive performance by combining both s

Factual and Edit-Sensitive Graph-to-Sequence Generation via Graph-Aware Adaptive Noising

arXiv:2604.24104v1 Announce Type: new Abstract: Fine-tuned autoregressive models for graph-to-sequence generation (G2S) often struggle with factual grounding and edit sensitivity. To tackle these issu

local-aiarxiv-cs-cl

GeoFunFlow-3D: A Physics-Guided Generative Flow Matching Framework for High-Fidelity 3D Aerodynamic Inference over Complex Geometries

arXiv:2604.23350v1 Announce Type: cross Abstract: Deep generative models and neural operators have demonstrated significant potential for 3D aerodynamic inference. However, they often face inherent ch

Got early access access to LingBot-World-Fast at 17 FPS! Here's what I found.

local-air-stablediffusion

LingBot-World-Fast successfully preserves the structural integrity and physical logic of the teacher model , achieving acceleration that introduces a necessary trade-off in theoretical upper-bound qua

h-MINT: Modeling Pocket-Ligand Binding with Hierarchical Molecular Interaction Network

arXiv:2604.23134v1 Announce Type: new Abstract: Accurate molecular representations are critical for drug discovery, and a central challenge lies in capturing the chemical environment of molecular frag

Hidden States Know Where Reasoning Diverges: Credit Assignment via Span-Level Wasserstein Distance

arXiv:2604.23318v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO) performs coarse-grained credit assignment in reinforcement learning with verifiable rewards (RLVR) by assignin

local-aiarxiv-cs-cl

Kwai Summary Attention Technical Report

arXiv:2604.24432v1 Announce Type: cross Abstract: Long-context ability, has become one of the most important iteration direction of next-generation Large Language Models, particularly in semantic unde

LAMP: Extracting Local Decision Surfaces From Large Language Models

arXiv:2505.11772v3 Announce Type: replace Abstract: We introduce LAMP (Local Attribution Mapping Probe), a method that shines light onto a black-box language model's decision surface and studies how r

Learning from Noisy Prompts: Saliency-Guided Prompt Distillation for Robust Segmentation with SAM

arXiv:2604.23314v1 Announce Type: new Abstract: Segmentation is central to clinical diagnosis and monitoring, yet the reliability of modern foundation models in medical imaging still depends on the av

Load constrained wind farm flow control through multi-objective multi-agent reinforcement learning

arXiv:2604.22795v1 Announce Type: cross Abstract: This study presents a multi-agent reinforcement learning (MARL) framework for load-constrained wind farm flow control (WFFC). While wake steering can

Local model users get a lot of boring-good fixes: @ollama context handling, thinking controls, timeouts, local auth, discovery, and OpenAI-c…

Local model users get a lot of boring-good fixes: @ollama context handling, thinking controls, timeouts, local auth, discovery, and OpenAI-compatible proxy behavior. https://docs.openclaw.ai/providers

local-aiollama--x

LTX Desktop 1.0.5 is live

local-air-stablediffusion

LTX Desktop 1.0.5 is an open-source desktop app for generating videos with LTX models on Windows/Linux NVIDIA GPUs locally or via API . The version 1.0.5 release includes bug fixes such as LTX API ins

Memory for Personal AI Agents

A discussion about AI agents that can remember information from one interaction to the next, even across separate sessions , exploring how to implement persistent memory systems for personal AI assist

local-air-ollama

Meta is about to release a pixel space model (Tuna-2)

local-air-stablediffusion

Tuna-2 is a unified multimodal model that performs visual understanding and generation directly based on pixel embeddings, employing simple patch embedding layers to encode visual input without a VAE

Mimo V2.5-Pro open sourced

MiMo-V2.5-Pro is a fully open-sourced Mixture-of-Experts language model with 1.02T total parameters and 42B active parameters , available under the MIT License for commercial use, training, and fine-t

local-air-ollama

Model page: https://ollama.com/library/laguna-xs.2

Laguna XS 2 is a compact language model available through Ollama's model library, designed for efficient inference on resource-constrained devices. The model represents an update or variant in the Lag

local-aiollama--x

Model page: https://ollama.com/library/nemotron3

Nemotron-3 is an open-source language model available through Ollama's model library, likely representing NVIDIA's Nemotron-3 family of instruction-tuned models designed for various NLP tasks. The mod

local-aiollama--x

RADIANT-LLM: an Agentic Retrieval Augmented Generation Framework for Reliable Decision Support in Safety-Critical Nuclear Engineering

arXiv:2604.22755v1 Announce Type: cross Abstract: Reliable decision support in nuclear engineering requires traceable, domain-grounded knowledge retrieval, yet safety and risk analysis workflows remai

Read the full blog: https://open.substack.com/pub/comfyui/p/comfystudio-has-arrived?utm_campaign=post-expanded-share&utm_medium=web

ComfyUI has announced the arrival of ComfyStudio, a new development or feature release for their platform. This announcement was shared via a Substack blog post and promoted through their official X (

local-aicomfyui--x

Reliable Microservice Tail Latency Prediction via Decoupled Dual-Stream Learning and Gradient Modulation

arXiv:2508.01635v2 Announce Type: replace-cross Abstract: Microservice architectures enable scalable cloud-native applications; however, the distributed nature of these systems complicates the mainten

Resource-Constrained UAV-Based Weed Detection for Site-Specific Management on Edge Devices

arXiv:2604.23442v1 Announce Type: new Abstract: Weeds compete with crops for light, water, and nutrients, reducing yield and crop quality. Efficient weed detection is essential for site-specific weed

Rethinking Trust Region Bayesian Optimization in High Dimensions

arXiv:2604.22967v1 Announce Type: cross Abstract: Trust Region Bayesian Optimization (TuRBO) is an effective strategy for alleviating the curse of dimensionality in high-dimensional black-box optimiza

S^2IT: Stepwise Syntax Integration Tuning for Large Language Models in Aspect Sentiment Quad Prediction

arXiv:2604.23296v1 Announce Type: cross Abstract: Aspect Sentiment Quad Prediction (ASQP) has seen significant advancements, largely driven by the powerful semantic understanding and generative capabi

SATTC: Structure-Aware Label-Free Test-Time Calibration for Cross-Subject EEG-to-Image Retrieval

arXiv:2603.20738v2 Announce Type: replace Abstract: Cross-subject EEG-to-image retrieval for visual decoding is challenged by subject shift and hubness in the embedding space, which distort similarity

Scalable Explainability-as-a-Service (XaaS) for Edge AI Systems

arXiv:2602.04120v2 Announce Type: replace-cross Abstract: Though Explainable AI (XAI) has made significant advancements, its inclusion in edge and IoT systems is typically ad-hoc and inefficient. Most

Self Knowledge Re-expression: A Fully Local Method for Adapting LLMs to Tasks Using Intrinsic Knowledge

arXiv:2604.22939v1 Announce Type: cross Abstract: While the next-token prediction (NTP) paradigm enables large language models (LLMs) to express their intrinsic knowledge, its sequential nature constr