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Galilean State Estimation for Inertial Navigation Systems with Unknown Time Delay

model-releasesarxiv-cs-ro

arXiv:2605.13266v1 Announce Type: new Abstract: Many Inertial Navigation Systems (INS) use Global Navigation Satellite System (GNSS) position as the primary measurement to drive filter performance and

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Human DGX agent

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Local Ai

GenCape: Structure-Inductive Generative Modeling for Category-Agnostic Pose Estimation

DGX agent

arXiv:2605.13151v1 Announce Type: new Abstract: Category-agnostic pose estimation (CAPE) aims to localize keypoints on query images from arbitrary categories, using only a few annotated support exampl

local-aiarxiv-cs-cv

14 May 2026

Generating synthetic computed tomography for radiotherapy: SynthRAD2025 challenge report

arXiv:2605.13555v1 Announce Type: cross Abstract: Radiation therapy (RT) requires precise dose delivery over multiple fractions, with CT fundamental for treatment planning due to its electron density

Generative Modeling by Minimizing the Wasserstein-2 Loss

arXiv:2406.13619v4 Announce Type: replace-cross Abstract: This paper develops a generative model by minimizing the second-order Wasserstein loss (the W_2 loss) through a distribution-dependent ordinar

Generative Modeling from Black-box Corruptions via Self-Consistent Stochastic Interpolants

arXiv:2512.10857v2 Announce Type: replace-cross Abstract: Transport-based methods have emerged as a leading paradigm for building generative models from large, clean datasets. However, in many scienti

Generative Modeling of Approximately Periodic Time Series by a Posterior-Weighted Gaussian Process

arXiv:2605.13150v1 Announce Type: cross Abstract: Discrete automated processes in industrial and cyber-physical systems often exhibit a repetitive structure in which successive repetitions follow a co

Generative Motion In-betweening by Diffusion over Continuous Implicit Representations

arXiv:2605.12778v1 Announce Type: cross Abstract: Recent advances in generative models have yielded impressive progress on motion in-betweening, allowing for more complex, varied, and realistic motion

Generative Texture Diversification of 3D Pedestrians for Robust Autonomous Driving Perception

arXiv:2605.13755v1 Announce Type: new Abstract: In recent years, autonomous driving has significantly in creased the demand for high-quality data to train 2D and 3D perception models for safety-critic

safetyarxiv-cs-cv

GeoFlowVLM: Geometry-Aware Joint Uncertainty for Frozen Vision-Language Embedding

arXiv:2605.13352v1 Announce Type: new Abstract: Standard dual-encoder vision-language models that map images and text to deterministic points on a shared unit hypersphere through ell_2 normalization t

Hardware

Geometric Autoencoder Priors for Bayesian Inversion: Learn First Observe Later

arXiv:2509.19929v4 Announce Type: replace-cross Abstract: Uncertainty Quantification (UQ) is paramount for inference in engineering. A common inference task is to recover full-field information of phy

hardwarearxiv-cs-lg

Geometric Preconditioning and Curriculum Optimization for Trainable Variational Quantum Regression

arXiv:2601.11942v3 Announce Type: replace Abstract: Variational quantum circuits are increasingly studied as continuous-function approximators, but quantum regression remains difficult to train when g

GeomHair: Reconstruction of Hair Strands from Colorless 3D Scans

arXiv:2505.05376v3 Announce Type: replace Abstract: We propose a novel method that reconstructs hair strands directly from colorless 3D scans by leveraging multi-modal hair orientation extraction. Hai

GHGbench: A Unified Multi-Entity, Multi-Task Benchmark for Carbon Emission Prediction

arXiv:2605.13743v1 Announce Type: new Abstract: Open datasets and benchmarks for entity-level carbon-emission prediction remain fragmented across access, scale, granularity, and evaluation. We introdu

Local Ai

GLASS: Global-Local Aggregation for Inference-time Sparsification of LLMs

arXiv:2508.14302v2 Announce Type: replace-cross Abstract: Inference-time sparsification is a promising path to deploy large language models (LLMs) on resource-constrained devices, yet existing trainin

local-aiarxiv-cs-ai

GRACE: Gradient-aligned Reasoning Data Curation for Efficient Post-training

arXiv:2605.13130v1 Announce Type: new Abstract: Existing reasoning data curation pipelines score whole samples, treating every intermediate step as equally valuable. In reality, steps within a trace c

safetyarxiv-cs-ai

Gradual Domain Adaptation for Graph Learning

arXiv:2501.17443v4 Announce Type: replace Abstract: Existing machine learning literature lacks graph-based domain adaptation techniques capable of handling large distribution shifts, primarily due to

Graph-Based Financial Fraud Detection with Calibrated Risk Scoring and Structural Regularization

arXiv:2605.12782v1 Announce Type: new Abstract: Financial transaction fraud prevention faces challenges such as complex relationship structures, concealed behavioral patterns, and dynamically changing

safetyarxiv-cs-lg

Applications

Graph Neural Networks with Triangle-Based Messages for the Multicut Problem

arXiv:2605.13673v1 Announce Type: new Abstract: The multicut problem is an NP-hard combinatorial optimization problem with diverse applications in fields such as bioinformatics, data mining and comput

applicationsarxiv-cs-lg

GraphIP-Bench: How Hard Is It to Steal a Graph Neural Network, and Can We Stop It?

arXiv:2605.12827v1 Announce Type: cross Abstract: Graph neural networks (GNNs) deployed as cloud services can be stolen through model-extraction attacks, which train a surrogate from query responses t

Tutorials

GraphThinker: Reinforcing Temporally Grounded Video Reasoning with Event Graph Thinking

arXiv:2602.17555v3 Announce Type: replace Abstract: Video reasoning requires a fine-grained understanding of the temporal dependencies and event-level relations between objects and events in videos. C

tutorialsarxiv-cs-cv

Grid-Orch: An LLM-Powered Orchestrator for Distribution Grid Simulation and Analytics

arXiv:2605.12728v1 Announce Type: cross Abstract: The power distribution engineering workforce faces a projected shortage of up to 1.5 million engineers by 2030, creating urgent demand for more access

Local Ai

GRIP-VLM: Group-Relative Importance Pruning for Efficient Vision-Language Models

arXiv:2605.13375v1 Announce Type: cross Abstract: In Vision-Language Models (VLMs), processing a massive number of visual tokens incurs prohibitive computational overhead. While recent training-aware

local-aiarxiv-cs-ai

Agents

GTA: Advancing Image-to-3D World Generation via Geometry Then Appearance Video Diffusion

arXiv:2605.12957v1 Announce Type: new Abstract: Recent developments in generative models and large-scale datasets have substantially advanced 3D world generation, facilitating a broad range of domains

agentsarxiv-cs-cv

GuardMarkGS: Unified Ownership Tracing and Edit Deterrence for 3D Gaussian Splatting

arXiv:2605.12919v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) is becoming a practical representation for novel view synthesis, but its growing adoption, together with rapid advances in

Guide, Think, Act: Interactive Embodied Reasoning in Vision-Language-Action Models

arXiv:2605.13632v1 Announce Type: cross Abstract: In this paper, we propose GTA-VLA(Guide, Think, Act), an interactive Vision-Language-Action (VLA) framework that enables spatially steerable embodied

Guidestar-Free Adaptive Optics with Asymmetric Apertures

arXiv:2602.07029v3 Announce Type: replace-cross Abstract: This work introduces the first closed-loop adaptive optics (AO) system capable of optically correcting aberrations in real-time without a guid

GUIGuard-Bench: Toward a General Evaluation for Privacy-Preserving GUI Agents

arXiv:2601.18842v3 Announce Type: replace-cross Abstract: As GUI agents increasingly rely on screenshots to perceive and operate digital environments, they may inadvertently expose sensitive informati

HADAR-Based Thermal Infrared Hyperspectral Image Restoration

arXiv:2605.13664v1 Announce Type: new Abstract: Thermal-infrared (TIR) hyperspectral imagery (HSI) provides critical scene information for various applications. However, its practical utility is sever

HarmoGS: Robust 3D Gaussian Splatting in the Wild via Conflict-Aware Gradient Harmonization

arXiv:2605.13073v1 Announce Type: new Abstract: In-the-wild 3D Gaussian Splatting remains challenging due to transient distractors and illumination-induced cross-view appearance inconsistencies. Exist

Agents

Harnessing Agentic Evolution

arXiv:2605.13821v1 Announce Type: new Abstract: Agentic evolution has emerged as a powerful paradigm for improving programs, workflows, and scientific solutions by iteratively generating candidates, e

agentsarxiv-cs-ai

HCSG: Human-Centric Semantic-Geometric Reasoning for Vision-Language Navigation

model-releasesarxiv-cs-ro

arXiv:2605.13321v1 Announce Type: new Abstract: VLN has achieved remarkable progress by scaling data and model capacity. However, the assumption of a static environment breaks down in real-world indoo

Hessian Matching for Machine-Learned Coarse-Grained Molecular Dynamics

arXiv:2605.12823v1 Announce Type: new Abstract: Coarse-grained (CG) molecular dynamics enables simulations of atomic systems such as biomolecules at timescales inaccessible to all-atom (AA) methods, b

HetScene: Heterogeneity-Aware Diffusion for Dense Indoor Scene Generation

arXiv:2605.13586v1 Announce Type: cross Abstract: Generating controllable and physically plausible indoor scenes is a pivotal prerequisite for constructing high-fidelity simulation environments for em

Hierarchical Attacks for Multi-Modal Multi-Agent Reasoning

arXiv:2605.13213v1 Announce Type: new Abstract: Multi-modal multi-agent systems (MM-MAS) have gained increasing attention for their capacity to enable complex reasoning and coordination across diverse

Hierarchical Transformer Preconditioning for Interactive Physics Simulation

arXiv:2605.13343v1 Announce Type: cross Abstract: Neural preconditioners for real-time physics simulation offer promising data-driven priors, but they often fail to capture long-range couplings effici

High-Dimensional Analysis of Bootstrap Ensemble Classifiers

arXiv:2505.14587v2 Announce Type: replace-cross Abstract: Bootstrap methods have long been the cornerstone of ensemble learning in machine learning. This paper presents a theoretical analysis of boots

High-Order Epistasis Detection Using Factorization Machine with Quadratic Optimization Annealing and MDR-Based Evaluation

arXiv:2601.01860v2 Announce Type: replace Abstract: Detecting high-order epistasis is a fundamental challenge in genetic association studies due to the combinatorial explosion of candidate locus combi

High-Rate Quantized Matrix Multiplication I

arXiv:2601.17187v2 Announce Type: replace-cross Abstract: This paper investigates the problem of quantized matrix multiplication (MatMul), which has become crucial for the efficient deployment of larg

High-Rate Quantized Matrix Multiplication II

arXiv:2605.13768v1 Announce Type: cross Abstract: This is the second part of the work investigating quantized matrix multiplication (MatMul). In part I we considered the case of calibration-free quant

Higher-order Linear Attention

arXiv:2510.27258v2 Announce Type: replace-cross Abstract: The quadratic cost of scaled dot-product attention is a central obstacle to scaling autoregressive language models to long contexts. Linear-ti

HIR-ALIGN: Enhancing Hyperspectral Image Restoration via Diffusion-Based Data Generation

arXiv:2605.13581v1 Announce Type: new Abstract: Hyperspectral image (HSI) restoration is crucial for reliable analysis, as real HSIs suffer from degradations like noise, blur, and resolution loss. How

safetyarxiv-cs-cv

History Anchors: How Prior Behavior Steers LLM Decisions Toward Unsafe Actions

arXiv:2605.13825v1 Announce Type: new Abstract: Frontier LLMs are increasingly deployed as agents that pick the next action after a long log of prior tool calls produced by the same or a different mod

safetyarxiv-cs-ai

HLS-Seek: QoR-Aware Code Generation for High-Level Synthesis via Proxy Comparative Reward Reinforcement Learning

arXiv:2605.13536v1 Announce Type: cross Abstract: High-Level Synthesis (HLS) compiles algorithmic C/C++ descriptions into hardware, with Quality of Results (QoR) -- latency and resource utilization --

(How) Do Large Language Models Understand High-Level Message Sequence Charts?

arXiv:2605.13773v1 Announce Type: cross Abstract: Large Language Models (LLMs) are being employed widely to automate tasks across the software development life-cycle. It is, however, unclear whether t

Tutorials

How Do Transformers Learn to Associate Tokens: Gradient Leading Terms Bring Mechanistic Interpretability

arXiv:2601.19208v2 Announce Type: replace-cross Abstract: Semantic associations such as the link between 'bird' and 'flew' are foundational for language modeling as they enable models to go beyond mem

tutorialsarxiv-cs-lg

How to Interpret Agent Behavior

arXiv:2605.13625v1 Announce Type: new Abstract: Autonomous agents such as Claude Code and Codex now operate for hours or even days. Understanding their runtime behavior has become critical for downstr

How Well Do Large-Scale Chemical Language Models Transfer to Downstream Tasks?

arXiv:2602.11618v4 Announce Type: replace Abstract: Chemical Language Models (CLMs) pre-trained on large scale molecular data are widely used for molecular property prediction. However, the common bel

Human face perception reflects inverse-generative and naturalistic discriminative objectives

arXiv:2605.12619v1 Announce Type: cross Abstract: The perceptual representations supporting our ability to recognize faces remain a computational mystery. Deep neural networks offer mechanistic hypoth