Search: “local-ai”

Posterior Contraction of Levy Adaptive B-spline Regression in Besov Spaces

arXiv:2605.19610v1 Announce Type: cross Abstract: We investigate the asymptotic properties of the Levy Adaptive B-spline (LABS) regression model, a Bayesian nonparametric method that incorporates B-sp

PRISM-SLAM: Probabilistic Ray-Grounded Inference for Scale-aware Metric SLAM

DGX agent

arXiv:2605.19257v1 Announce Type: new Abstract: Monocular SLAM historically suffers from scale ambiguity and tracking failure in dynamic environments. While recent vision foundation models (VFMs) prov

local-aiarxiv-cs-ro

20 May 2026

Query-Conditioned Graph Retrieval for Contextualized LLM Reasoning in Personalized Wearable Data

arXiv:2605.18763v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly applied to analyzing wearable sensing data, which are long-term, multimodal, and highly personalized. A

Real-Time Parallel Counterfactual Regret Minimization

arXiv:2605.19928v1 Announce Type: cross Abstract: Counterfactual Regret Minimization (CFR) is the dominant algorithmic family for solving large imperfect-information games, underpinning breakthroughs

Rethinking Visual Attribution for Chest X-ray Reasoning in Large Vision Language Models

arXiv:2605.20158v1 Announce Type: cross Abstract: Large Vision Language Models (LVLMs) show promise in medical applications, but their inability to faithfully ground responses in visual evidence raise

Slot-MLLM: Object-Centric Visual Tokenization for Multimodal LLM

arXiv:2505.17726v3 Announce Type: replace-cross Abstract: Recently, multimodal large language models (MLLMs) have emerged as a key approach in achieving artificial general intelligence. In particular,

StableGrad: Backward Scale Control without Batch Normalization

arXiv:2605.19856v1 Announce Type: cross Abstract: Training very deep neural networks requires controlling the propagation of magnitudes across depth. Without such control, activations and gradients ma

STRIDE: Learnable Stepwise Language Feedback for LLM Reasoning

arXiv:2605.18851v1 Announce Type: new Abstract: Recent advances in Reinforcement Learning (RL) have underscored its potential for incentivizing reasoning capabilities of Large Language Models (LLMs).

Tango3D: Towards Alignment for Global and Local 2D-3D Correspondence

arXiv:2605.19727v1 Announce Type: new Abstract: Existing 3D foundation models typically align point clouds to frozen vision-language spaces like CLIP, which achieve strong cross-modal retrieval by com

The Trends Reshaping the Future of AI Infrastructure

This article examines key emerging trends that are transforming AI infrastructure, likely covering topics such as distributed computing, edge AI deployment, GPU optimization, and evolving cloud infras

local-aivultr

Thinking in Scales: Accelerating Gigapixel Pathology Image Analysis via Adaptive Continuous Reasoning

arXiv:2605.19491v1 Announce Type: new Abstract: Traditional whole slide image (WSI) analysis methods typically rely on the multiple instance learning (MIL) paradigm, which extracts patch-level feature

Understanding and Exploiting Weight Update Sparsity for Communication-Efficient Distributed RL

arXiv:2602.03839v2 Announce Type: replace Abstract: Bandwidth-constrained distributed reinforcement learning (RL) post-training of large language models is bottlenecked by two channels: weight synchro

Using Aristotle API for AI-Assisted Theorem Proving in Lean 4: A Formalisation Case Study of the Grasshopper Problem

arXiv:2605.20120v1 Announce Type: new Abstract: AI-assisted theorem proving can now generate substantial Lean developments for olympiad-level mathematics, but the evidential status of such development

Using Seedance 2.0, a simple performance shot can become a cinematic scene no matter where it was shot. Workflow link below.

Seedance 2.0 is a ComfyUI tool that transforms basic performance footage into cinematic-quality scenes through an automated workflow, regardless of the original shooting location. The technique appear

local-aicomfyui--x

What hardware actually powers open-source AI? Not benchmarks. Not vendor marketing. Real-world community usage. We’re launching @huggingface…

local-aigeorgi-gerganov--x

What hardware actually powers open-source AI? Not benchmarks. Not vendor marketing. Real-world community usage. We’re launching @huggingface Hardware: → trending GPUs & CPUs → VRAM distribution → infe

What is the best image anime upscaler currently?

local-air-stablediffusion

LetsEnhance with its Digital Art model is considered best for quality, delivering sharp lines and clearest eye detail with the highest output resolution ceiling. For a free desktop option, Upscayl off

Your Neighbors Know: Leveraging Local Neighborhoods for Backdoor Detection in Decentralized Learning

arXiv:2605.19969v1 Announce Type: new Abstract: Decentralized learning (DL) is an emerging machine learning paradigm where nodes collaboratively train models without a central server. However, the col

AdaptiveLoad: Towards Efficient Video Diffusion Transformer Training

arXiv:2605.17923v1 Announce Type: cross Abstract: In video generation models, particularly world models, training large-scale video diffusion Transformers (such as DiT and MMDiT) poses significant com

ADMEDTAGGER: an annotation framework for distillation of expert knowledge for the Polish medical language

arXiv:2601.09722v2 Announce Type: replace-cross Abstract: In this work, we present an annotation framework that demonstrates how a multilingual LLM pretrained on a large corpus can be used as a teache

Agentmw: Open-source middleware for AI agents — catches mid-run failures,compresses stale context, and grows a reasoning library across runs. Any model, any framework.

Agentmw is an open-source middleware framework designed to enhance AI agent reliability and efficiency across different models and frameworks. It addresses key operational challenges including mid-run

local-air-ollama

ALIGN: A Vision-Language Framework for High-Accuracy Accident Location Inference through Geo-Spatial Neural Reasoning

arXiv:2511.06316v3 Announce Type: replace Abstract: In low- and middle-income countries, public safety and urban planning initiatives frequently face a critical shortage of accurate, location-specific

ANNEAL: Adapting LLM Agents via Governed Symbolic Patch Learning

arXiv:2605.16309v1 Announce Type: new Abstract: LLM-based agents can recover from individual execution errors, yet they repeatedly fail on the same fault when the underlying process knowledge--operato

AtlasVid: Efficient Ultra-High-Resolution Long Video Generation via Decoupled Global-Local Modeling

arXiv:2605.16649v1 Announce Type: new Abstract: Recent diffusion-based video generators have achieved remarkable visual fidelity and prompt controllability, yet scaling them to ultra-high-resolution (

Attend Locally, Remember Linearly: Linear Attention as Cross-Frame Memory for Autoregressive Video Diffusion

arXiv:2605.16579v1 Announce Type: new Abstract: Autoregressive (AR) video diffusion is a powerful paradigm for streaming and interactive video generation. However, its reliance on softmax self-attenti

Aurora: Unified Video Editing with a Tool-Using Agent

arXiv:2605.18748v1 Announce Type: new Abstract: Recent video editing models have converged on a unified conditioning design: a single diffusion transformer jointly consumes text, source video, and ref

Axial-Relation Guided Fusion State Space Model for Optical-Elevation Sensing Image Segmentation

arXiv:2605.16768v1 Announce Type: new Abstract: Semantic segmentation of multi-source remote sensing images is a fundamental task for Earth observation applications. Existing methods often struggle wi

b9222

local-aillama-cpp-releases

B9222 is a llama.cpp release that adds support for the TRI (Triangle) operation in the Hexagon HTP backend with HVX kernel additions . The release includes optimizations for Hexagon hardware accelerat

Beyond Inference-Time Search: Reinforcement Learning Synthesizes Reusable Solvers

arXiv:2605.18374v1 Announce Type: cross Abstract: Large language models (LLMs) typically approach combinatorial optimization as an inference-time procedure, solving each instance separately through sa

Beyond the Cartesian Illusion: Testing Two-Stage Multi-Modal Theory of Mind under Perceptual Bottlenecks

arXiv:2605.18194v1 Announce Type: new Abstract: While Multi-Modal Large Language Models (MLLMs) demonstrate impressive capabilities in general reasoning, their embodied spatial intelligence remains ha

BLAgent: Agentic RAG for File-Level Bug Localization

arXiv:2605.17965v1 Announce Type: cross Abstract: Bug localization remains a key bottleneck in downstream software maintenance tasks, including root cause analysis, triage, and automated program repai

CanViT: Toward Active-Vision Foundation Models

arXiv:2603.22570v2 Announce Type: replace Abstract: Active computer vision promises efficient, biologically plausible perception through sequential, localized glimpses, but lacks scalable general-purp

Causal Attribution via Activation Patching

arXiv:2603.13652v2 Announce Type: replace Abstract: Attribution methods for Vision Transformers (ViTs) aim to identify image regions that influence model predictions, but producing faithful and well-l

CheckSupport: A Local LLM-Powered Tool for Automated Manuscript Submission Checklist Selection and Completion

arXiv:2605.16377v1 Announce Type: cross Abstract: Transparent and standardized reporting is essential for reproducible scientific research, yet adherence to reporting guidelines remains inconsistent b

CMAG: Concept-Scaffolded Retrieval for Marketplace Avatar Generation

arXiv:2605.18680v1 Announce Type: new Abstract: Metaverse platforms rely on creator-driven marketplaces where avatars are assembled from discrete, taxonomy-labeled 3D assets (e.g., tops, bottoms, shoe

Conservative AI for Safety-Sensitive Medical Image Restoration: Residual-Bounded CT-CTA Enhancement for Intracranial Aneurysm-Relevant Signal Recovery

arXiv:2605.16458v1 Announce Type: cross Abstract: Image restoration models are increasingly applied to degraded medical scans, but in safety-sensitive settings they must improve image quality without

Constrained Code Generation with Discrete Diffusion

arXiv:2605.16829v1 Announce Type: new Abstract: Discrete diffusion models are a powerful, emerging paradigm for code generation. They construct programs through iterative refinement of partially corru

local-aiarxiv-cs-cl

CounterCount: A Diagnostic Framework for Counting Bias in Vision Language Models

arXiv:2605.17826v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) excel at multimodal reasoning, yet it remains unclear whether their answers are grounded in visual evidence or driven by

Cross-Source Supervision for Bone Infection Segmentation in Dual-Modality PET-CT

arXiv:2605.16373v1 Announce Type: cross Abstract: Early and accurate diagnosis and lesion localization of bone infections are crucial for clinical treatment. PET-CT integrates anatomical information f

Diagnosing Korean-Language LLM Political Bias via Census-Grounded Agent Simulation

arXiv:2605.18395v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit systematic political biases in voter simulations, but their underlying mechanisms and cross-lingual generalizatio

Diffeomorphic Cortical Alignment via Direct Warping of Streamline Endpoints

arXiv:2605.16742v1 Announce Type: new Abstract: Cortical surface registration is often driven by local geometric descriptors (e.g., sulcal depth and curvature). While this approach achieves geometric

Edge-AI-Driven Learning-to-Rank for Decentralized Task Allocation in Circular Smart Manufacturing

arXiv:2605.16433v1 Announce Type: cross Abstract: Task allocation in smart manufacturing systems needs to operate under decentralized decision-making, dynamic workloads, and shared resource constraint

EgoKit: Towards Unified Low-Cost Egocentric Data Collection with Heterogeneous Devices

arXiv:2605.16797v1 Announce Type: new Abstract: Egocentric video is increasingly used as a data source for robot learning, activity understanding, and embodied AI research, but collecting it at scale

Enhancing Cloud Network Resilience via a Robust LLM-Empowered Multi-Agent Reinforcement Learning Framework

arXiv:2601.07122v2 Announce Type: replace-cross Abstract: While virtualization and resource pooling empower cloud networks with structural flexibility and elastic scalability, they inevitably expand t

FastOCR: Dynamic Visual Fixation via KV Cache Pruning for Efficient Document Parsing

arXiv:2605.17447v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have shown strong promise on Optical Character Recognition (OCR), yet the sheer number of visual tokens required to enco

local-aiarxiv-cs-cl

Federated Learning by Utility-Constrained Stochastic Aggregation for Improving Rational Participation

arXiv:2605.18020v1 Announce Type: new Abstract: Federated Learning (FL) algorithms implicitly assume that clients passively comply with server-side orchestration by sharing local model updates upon se

FedSDR: Federated Self-Distillation with Rectification

arXiv:2605.18028v1 Announce Type: cross Abstract: Federated fine-tuning of Large Language Models faces severe statistical heterogeneity. However, existing model-level defenses often overlook the root

FishBack: Pullback Fisher Geometry for Optimal Activation Steering in Transformers

arXiv:2605.17231v1 Announce Type: cross Abstract: Activation steering methods modify intermediate representations of language models to control output behavior, but universally assume the activation s

local-aiarxiv-cs-cl

FrequencyBooster: Full-Frequency Modeling for High-Fidelity Pixel Diffusion

arXiv:2605.17759v1 Announce Type: new Abstract: To circumvent the inherent fidelity bottlenecks and optimization misalignment of VAE-based latent diffusion, pixel-space diffusion models have emerged a