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Personalized Federated Learning for Gradient Alignment

arXiv:2605.02143v1 Announce Type: new Abstract: Personalized federated learning (pFL) aims to adapt models to client specific data distributions, yet it often fails to reliably preserve personalized i

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Robust and Explainable Divide-and-Conquer Learning for Intrusion Detection

DGX agent

arXiv:2605.02015v1 Announce Type: new Abstract: Machine learning-based intrusion detection requires complex models to capture patterns in high-dimensional, noisy, and class-imbalanced raw network traf

local-aiarxiv-cs-lg

5 May 2026

Robust Cross-Domain WiFi Fall Detection via Physics-Driven Attention-Enhanced Transformers

arXiv:2605.00869v1 Announce Type: cross Abstract: Device-free fall detection utilizing WiFi Channel State Information (CSI) has emerged as a promising, privacy-preserving solution for elderly health m

Seedance 2.0 https://links.comfy.org/4d0Lkv2

Seedance 2.0 is an update or feature release for ComfyUI, a node-based UI for Stable Diffusion and other generative AI models. This announcement likely describes new functionality, improvements, or en

Semantic Context-aware mOdality fUsion Transformer (SCOUT): A Context-Aware Multimodal Transformer for Concept-Grounded Pathology Report Generation

arXiv:2605.01144v1 Announce Type: new Abstract: Whole-slide images (WSIs) present a fundamental challenge for computational pathology due to their extreme resolution, multi-scale heterogeneity, and th

Spatial-Temporal Learning-Based Distributed Routing for Dynamic LEO Satellite Networks

arXiv:2605.02413v1 Announce Type: cross Abstract: In this paper, we propose a spatial-temporal learning-based distributed routing framework for dynamic Low Earth Orbit (LEO) satellite networks, where

Super-resolution of airborne laser scanning point clouds for forest inventory

arXiv:2605.02201v1 Announce Type: new Abstract: Airborne Laser Scanning (ALS) can collect point clouds across large areas, enabling large-scale forest inventory. However, ALS point clouds are sparse a

TagRAG: Tag-guided Hierarchical Knowledge Graph Retrieval-Augmented Generation

arXiv:2601.05254v3 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation enhances language models by retrieving external knowledge to support informed and grounded responses. However,

TIQA: Human-Aligned Perceptual Text Quality Assessment in Generated Images

arXiv:2603.07119v2 Announce Type: replace Abstract: Recent text-to-image models have improved global realism, but text rendering remains a persistent failure mode: images may look convincing overall,

Topaz Astra 2 is live. The sharpest cloud-based video upscaler in the industry is now available via partner nodes. Adjustable levels, prompt…

Topaz Astra 2 is live. The sharpest cloud-based video upscaler in the industry is now available via partner nodes. Adjustable levels, prompt-based control, and next-gen detail for everything from land

Trust, but Verify: Peeling Low-Bit Transformer Networks for Training Monitoring

arXiv:2605.02853v1 Announce Type: new Abstract: Understanding whether deep neural networks are effectively optimized remains challenging, as training occurs in highly nonconvex landscapes and standard

Try it on Comfy Cloud https://cloud.comfy.org/?template=api_luma_uni_1_image_create

ComfyUI announced a cloud-based template for API integration with Luma AI's unified image creation model, accessible through their Comfy Cloud platform. The template (api_luma_uni_1_image_create) enab

Try it on Comfy Cloud https://cloud.comfy.org/?template=api_topaz_astra2

Comfy Cloud is offering an online interface to try ComfyUI's API with the Topaz Astra2 template pre-configured, allowing users to test the model without local installation. This represents Comfy's eff

Ultrafast On-chip Online Learning via Spline Locality in Kolmogorov-Arnold Networks

arXiv:2602.02056v2 Announce Type: replace-cross Abstract: Ultrafast online learning is essential for high-frequency systems, such as controls for quantum computing and nuclear fusion, where adaptation

UnGAP: Uncertainty-Guided Affine Prompting for Real-Time Crack Segmentation

arXiv:2605.02380v1 Announce Type: new Abstract: Real-time crack segmentation is vital for structural health monitoring but is plagued by aleatoric uncertainties arising from varying lighting, blur, an

v0.23.1

Ollama v0.23.0 was released on May 3, 2026 , with v0.23.1 appearing as a patch release shortly after. The v0.23.0 release added support for Claude Desktop through Ollama Launch, with Claude Cowork and

local-aiollama-releases

VERGE: Formal Refinement and Guidance Engine for Verifiable LLM Reasoning

arXiv:2601.20055v2 Announce Type: replace Abstract: Despite the syntactic fluency of Large Language Models (LLMs), ensuring their logical correctness in high-stakes domains remains a fundamental chall

Z-image Turbo Upscaling and fixing artifacts

local-air-stablediffusion

Z-Image Turbo upscaling involves using latent upscaling followed by a second sampling step to refine images after the initial upscale. Common artifacts in Z-Image Turbo generation can result from usin

Zero-Shot Confidence Estimation for Small LLMs: When Supervised Baselines Aren't Worth Training

arXiv:2605.02241v1 Announce Type: cross Abstract: How reliably can a small language model estimate its own correctness? The answer determines whether local-to-cloud routing-escalating queries a cheap

A Comparative Analysis of Machine Learning Models for Intrusion Detection in Intelligent Transport Systems

arXiv:2605.00279v1 Announce Type: cross Abstract: AI-powered edge computing security is moving Intelligent Transportation Systems (ITS) from passive, rule-based protections to proactive, smart, zero-t

A Model-based Visual Contact Localization and Force Sensing System for Compliant Robotic Grippers

arXiv:2605.00307v1 Announce Type: cross Abstract: Grasp force estimation can help prevent robots from damaging delicate objects during manipulation and improve learning-based robotic control. Integrat

A Unified Deep Learning Framework for Motion Correction in Medical Imaging

arXiv:2409.14204v4 Announce Type: replace-cross Abstract: Deep learning has shown significant value in medical image registration for motion correction, however, current techniques are either limited

AirFM-DDA: Air-Interface Foundation Model in the Delay-Doppler-Angle Domain for AI-Native 6G

arXiv:2605.00020v1 Announce Type: new Abstract: The success of large foundation models is catalyzing a new paradigm for AI-native 6G network design: wireless foundation models for physical layer desig

Apply here: https://docs.google.com/forms/d/e/1FAIpQLSdCrLN2UBKjeqz30__wMjTAXoVqhypTTq1Gl08y2nvKaEf98A/viewform

I cannot provide a factual summary without access to the actual form content. This appears to be an application form shared by ComfyUI on X (Twitter), likely for a program, position, or opportunity re

b9014

llama.cpp enables LLM inference in C/C++ , and release b9014 represents a build revision or commit snapshot from the llama.cpp repository on GitHub. This release would include bug fixes, feature impro

b9015

The search results show recent llama.cpp releases but not the specific b9015 release details. Based on the pattern found (b9010 is mentioned as the latest release from the search results), b9015 is li

b9016

Release b9016 is a build of llama.cpp, an LLM inference implementation in C/C++ . This build designation represents a specific intermediate version in the project's development cycle, similar to other

b9018

B9018 is the latest version of llama.cpp released on May 4, 2026. Llama.cpp is a project for LLM inference in C/C++ , providing efficient large language model execution with broad hardware support inc

b9019

b9019 is a release of llama.cpp, a C/C++ implementation for LLM inference. As a release tag from the ggml-org/llama.cpp repository, it represents a specific commit or version of the project that inclu

b9020

b9020 is a build release of llama.cpp (a C/C++ implementation of LLM inference) released on May 4, 2026, with precompiled binaries available for multiple platforms including macOS, Android, OpenEuler,

b9022

B9022 is a release of llama.cpp created on May 4, 2026, with commit d8794ee signed with GitHub's verified signature. The llama.cpp project is the main playground for developing new features for the gg

b9025

b9025 is a release from llama.cpp, a C/C++ project for LLM inference . The release uses a build numbering system for intermediate versions of the library. As a llama.cpp release, it likely includes up

Bayesian Optimization in Linear Time

arXiv:2605.00237v1 Announce Type: new Abstract: Bayesian optimization is a sequential method for minimizing objective functions that are expensive to evaluate and about which few assumptions can be ma

Been noticing a lot of 'slow responses' today: models do not inherently more slow, rate limiting more likely.

A Reddit discussion from the Ollama community addresses reports of slow model responses, clarifying that the models themselves are not inherently slower but that rate limiting is a more likely cause o

local-air-ollama

Block-wise Codeword Embedding for Reliable Multi-bit Text Watermarking

arXiv:2605.00348v1 Announce Type: cross Abstract: Recent multi-bit watermarking methods for large language models (LLMs) prioritize capacity over reliability, often conflating decoding with detection.

Characterizing the Expressivity of Local Attention in Transformers

arXiv:2605.00768v1 Announce Type: new Abstract: The transformer is the most popular neural architecture for language modeling. The cornerstone of the transformer is its global attention mechanism, whi

Cloud Is Closer Than It Appears: Revisiting the Tradeoffs of Distributed Real-Time Inference

arXiv:2605.00005v1 Announce Type: new Abstract: The increasing deployment of deep neural networks (DNNs) in cyber-physical systems (CPS) enhances perception fidelity, but imposes substantial computati

Comparative Analysis of Polygon-Based and Global Machine Learning Models for Bus Occupancy Prediction

arXiv:2605.00083v1 Announce Type: new Abstract: Accurate forecasting of bus ridership (passengers numbers) is crucial for efficient management and optimization of public transport systems. Traditional

Depth-Guided Privacy-Preserving Visual Localization Using 3D Sphere Clouds

arXiv:2605.00562v1 Announce Type: new Abstract: The emergence of deep neural networks capable of revealing high-fidelity scene details from sparse 3D point clouds has raised significant privacy concer

Did they shut down deep seek cloud for free users?

DeepSeek V3 and R1 API free tier includes 500M tokens per month , indicating free access remains available for API users. The search results focus on a major service outage in March 2026 and the recen

local-air-ollama

E^2DT: Efficient and Effective Decision Transformer with Experience-Aware Sampling for Robotic Manipulation

arXiv:2605.00159v1 Announce Type: new Abstract: In reinforcement learning (RL) for robotic manipulation, the Decision Transformer (DT) has emerged as an effective framework for addressing long-horizon

local-aiarxiv-cs-ro

EGREFINE: An Execution-Grounded Optimization Framework for Text-to-SQL Schema Refinement

arXiv:2605.00628v1 Announce Type: cross Abstract: Text-to-SQL enables non-expert users to query databases in natural language, yet real-world schemas often suffer from ambiguous, abbreviated, or incon

Federated Distillation for Whole Slide Image via Gaussian-Mixture Feature Alignment and Curriculum Integration

arXiv:2605.00578v1 Announce Type: new Abstract: Federated learning (FL) offers a promising framework for collaborative digital pathology by enabling model training across institutions. However, real-w

FedKPer: Tackling Generalization and Personalization in Medical Federated Learning via Knowledge Personalization

arXiv:2605.00698v1 Announce Type: cross Abstract: Federated learning (FL) holds great potential for medical applications. However, statistical heterogeneity across healthcare institutions poses a majo

From Birdsong to Rumbles: Classifying Elephant Calls with Out-of-Species Embeddings

arXiv:2605.00225v1 Announce Type: cross Abstract: We show that pretrained acoustic embeddings classify elephant vocalisations at a level approaching that of end-to-end supervised neural networks, with

Gated Differential Linear Attention: A Linear-Time Decoder for High-Fidelity Medical Segmentation

arXiv:2603.02727v4 Announce Type: replace Abstract: Medical image segmentation requires models that preserve fine anatomical boundaries while remaining practical for clinical deployment. Transformers

Hyperspherical Forward-Forward with Prototypical Representations

arXiv:2605.00082v1 Announce Type: new Abstract: The Forward-Forward (FF) algorithm presents a compelling, bio-inspired alternative to backpropagation. However, while efficient in training, it has a co

i thought on device ai was stupid but now my local voice model turns 4x faster on my corporate m4 max laptop than my m2 max personal laptop …

i thought on device ai was stupid but now my local voice model turns 4x faster on my corporate m4 max laptop than my m2 max personal laptop now i want to have a beefier computer to run the transcripti

local-aiclem-delangue--x