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Gap-Free Streaming PCA Beyond Rank-One Updates: Near-Optimal Rates and Applications to Differential Privacy

arXiv:2609.26508v1 Announce Type: new Abstract: Streaming principal component analysis (PCA) seeks to recover a leading spectral subspace in a single pass over a data stream. We give a new analysis of

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Research

Gaussian Flow-Matching Schedules: Implications for Sampling and Training

DGX agent

arXiv:2609.25839v1 Announce Type: new Abstract: Flow-matching schedules affect both sampling dynamics and the variance of the regression target. For centered commuting Gaussians, we show that a direct

researcharxiv-cs-lg

23 Sept 2026

GDLAM: Group-Disentangled Latent Action Model for Highly Disentangled Embodied Pretraining

arXiv:2609.26118v1 Announce Type: new Abstract: Latent action models (LAMs) learn action-related representations from action-free videos via self-supervised future prediction, offering a scalable para

safetyarxiv-cs-ro

Generalized Deep Regression for Repeated Measurements

arXiv:2609.25605v1 Announce Type: cross Abstract: In this paper, we study the estimation of a marginal regression function from independent units with repeated binary, count, or continuous responses u

Generalizing Manipulation Skills with a Local Coding Agent

arXiv:2609.26499v1 Announce Type: new Abstract: Today, progress in open-weight language models enables systems capable of writing, executing and debugging code while still running on a single workstat

local-aiarxiv-cs-ro

Generative Embodied Multiple Behavior Control Systems for Human-like Agents

arXiv:2609.22691v1 Announce Type: new Abstract: An enduring and richly elaborated dichotomy in cognitive neuroscience is that of human behavior control mechanisms, divided into habitual versus goal-di

agentsarxiv-cs-ai

Tutorials

Generative Tutorial: Towards Live Contextualized Visual Instructions for Physical Tasks

arXiv:2609.24955v1 Announce Type: cross Abstract: Visual instructions for physical tasks are typically authored in one context and followed in another, requiring users to translate demonstrated tools,

tutorialsarxiv-cs-ai

GeoComposer: Geometry-Grounded Photographic Composition Instruction

arXiv:2609.26620v1 Announce Type: new Abstract: Photographic composition aims to provide visual guidance for improving the framing, viewpoint, and spatial arrangement of an image. Early methods primar

local-aiarxiv-cs-cv

Geometric and Semantic Coupling for Interaction Understanding in 3D Scenes

arXiv:2609.25247v1 Announce Type: new Abstract: Interaction understanding in 3D scenes requires a joint description of movable parts, their motion, and the regions through which they can be operated.

Geometric Uncertainty for Detecting and Correcting Hallucinations in LLMs

arXiv:2509.13813v3 Announce Type: replace Abstract: Large language models are known to hallucinate, generating linguistically plausible but incorrect answers to questions. Uncertainty quantification h

researcharxiv-cs-cl

Geometry-Aware Hyperbolic Residual Quantization

arXiv:2609.26342v1 Announce Type: new Abstract: Residual Vector Quantization turns continuous representations into discrete, multi-level token sequences. Yet most methods operate in Euclidean space, d

GeoPair: Geometry-Preserving Cross-Layer Factorization for Training-Free Transformer Compression

arXiv:2609.25963v1 Announce Type: new Abstract: Transformer architectures exhibit cross-layer redundancies, yet post-training compression pipelines typically optimize layers in isolation or rely on he

GINIO: A Geometric SO(3)-Equivariant Interface for Neural Inertial Odometry

arXiv:2609.25338v1 Announce Type: cross Abstract: Neural inertial odometry increasingly uses networks as learned measurements inside filtering pipelines. Such measurements should transform consistentl

safetyarxiv-cs-lg

GitScholar: A Dataset for Predicting AI Research Impact from GitHub Engagement

arXiv:2609.26361v1 Announce Type: cross Abstract: With the rapid pace of AI research and the hundreds of daily new publications, staying up-to-date with the latest developments has become increasingly

Glucose-ML: A collection of longitudinal diabetes datasets for development of robust AI solutions

arXiv:2507.14077v2 Announce Type: replace-cross Abstract: Artificial intelligence (AI) algorithms are a critical part of state-of-the-art digital health technology for diabetes management. Yet, access

Goal-driven Variant Categorization

arXiv:2609.22475v1 Announce Type: new Abstract: Process discovery rarely yields a single coherent process structure. For analysis, a common step is to cluster process variants based on structural simi

researcharxiv-cs-ai

Graded Representation Theory of Equivariant Neural Networks

arXiv:2609.25776v1 Announce Type: cross Abstract: Nonlinear activations can create equivariant interactions between irreducible representations that linear maps cannot. We use the Gaussian degree deco

Applications

Graph-Based Inference for Feedback-Driven Word Deduction: A Scalable Framework for the Jotto Problem

arXiv:2609.25056v1 Announce Type: new Abstract: A feedback-based word deduction framework based on the Jotto problem is proposed, and the problem space is represented as a weighted graph where all val

applicationsarxiv-cs-cl

Graph Domain Adaptation Does Not End with Representation Learning

arXiv:2609.25692v1 Announce Type: new Abstract: Graph domain adaptation (GDA) transfers knowledge from a labeled source graph to an unlabeled target graph under shifts in both node attributes and grap

local-aiarxiv-cs-lg

Graph Memory for LLM Agents: At What Cost? A Comparative Evaluation of Query, Ingest, and Update Performance Across Graph Database Engines

model-releasesarxiv-cs-ai

arXiv:2609.23315v1 Announce Type: cross Abstract: Graph databases are frequently positioned as categorically necessary for connected-data workloads, yet the systems dimension along which they actually

Hardware

Greedy Decoding Is Not Precision-Invariant: Cross-Precision Output Divergence in LLM Inference

arXiv:2609.26621v1 Announce Type: new Abstract: Greedy decoding from large language models is commonly treated as deterministic. We show it is not precision-invariant: the same model, prompt, and deco

hardwarearxiv-cs-lg

GRIP: Gaussian Rendering as a Cross-Modal Bridge for Image-to-Point Cloud Registration

arXiv:2609.25966v1 Announce Type: new Abstract: This paper introduces GRIP, a pose-conditioned refinement framework for pixel-to-point matching and 2D to 3D registration. Given an initial coarse pose

GRUET: Quantifying Uncertainty of Agentic Reasoning-and-Acting Processes

arXiv:2609.24831v1 Announce Type: new Abstract: Agents have attracted considerably increasing attention due to the power of executing both Reasoning and Acting (ReAct) in open and dynamic environments

agentsarxiv-cs-ai

GTR: Gated Token Recurrence for Efficient Dense Prediction

arXiv:2609.26590v1 Announce Type: cross Abstract: Self-attention-based vision backbones perform well on dense prediction, but the quadratic computational cost of global softmax attention limits their

gwBenchmarks: Stress-Testing LLM Agents on High-Precision Gravitational Wave Astronomy

model-releasesarxiv-cs-ai

arXiv:2605.11269v2 Announce Type: replace-cross Abstract: Modern gravitational wave astronomy relies on modeling tasks that often require months of graduate-level effort, including building fast wavef

HABILIS Brain 0: Geometry-Change Supervision for Vision-Language-Action and Residual Flow Recovery

arXiv:2609.25558v1 Announce Type: cross Abstract: Vision-language-action policies benefit from geometric supervision, but current-frame geometry alone does not explicitly describe the changes associat

safetyarxiv-cs-lg

Hapi: A Multivariable Land-Surface Transformer for Medium-Range Hydrological Forecasting at Continental Scale

arXiv:2609.22702v1 Announce Type: new Abstract: Accurate flood forecasts several days in advance are essential for flood control, water-resource management, and emergency response. Producing them at h

local-aiarxiv-cs-ai

HARMONY: Hierarchical Agentic Reasoning for MONocular Image-to-Scene Synthesis

arXiv:2609.26793v1 Announce Type: new Abstract: Compositional 3D scene reconstruction has recently been explored from two directions: agentic reasoning that provides semantic understanding of spatial

safetyarxiv-cs-cv

Heating in human-HVAC interaction for smart homes: An interdisciplinary overview

arXiv:2609.23508v1 Announce Type: cross Abstract: As part of HVAC systems, residential heating provides foundational infrastructure for human habitation in cold weather. However, research on how resid

researcharxiv-cs-ai

Hi-OPD: Hierarchy-Aware Open-Prompt Detection for Remote Sensing Images

arXiv:2609.25584v1 Announce Type: new Abstract: Hi-OPD addresses a failure mode left uncontrolled by flat open-prompt training: descendant retrieval need not persist under ancestor queries when multi-

Hierarchical Floorplan-Guided Vision-Language Exploration for Embodied Question Answering

arXiv:2609.26360v1 Announce Type: new Abstract: Embodied Question Answering (EQA) requires an agent to explore a previously unseen environment, gather relevant information, and answer questions about

agentsarxiv-cs-ro

Hierarchical Sparse Bayesian Multitask Learning for Disease Prediction in Pooled Microbiome Studies

arXiv:2502.02552v2 Announce Type: replace Abstract: This paper proposes a hierarchical Bayesian multitask learning model that is applicable to the general multi-task binary classification learning pro

High-Bandwidth Biomimetic Finger for Tactile-Transparent Remote Texture Sensing

arXiv:2609.26256v1 Announce Type: new Abstract: High-fidelity tactile feedback is essential for robotic teleoperation, enabling precise manipulation and critical decision-making. While biomimetic fing

researcharxiv-cs-ro

High-Order Liquid Evidence Modeling for Continuous and Subtle GNSS Spoofing Detection in Autonomous Driving

arXiv:2609.26231v1 Announce Type: new Abstract: Continuous and subtle GNSS spoofing poses a serious threat to autonomous vehicles because forged positions may remain locally plausible while gradually

local-aiarxiv-cs-lg

High-speed Imaging through Turbulence with Event-based Light Fields

arXiv:2603.14023v3 Announce Type: replace Abstract: This work introduces and demonstrates the first system capable of imaging fast-moving extended non-rigid objects through strong atmospheric turbulen

Higher-Order Approximation of Exit Functionals in Sampling-Based Stochastic Model Predictive Control

arXiv:2609.25257v1 Announce Type: cross Abstract: Safety evaluation in sampling-based stochastic model predictive control often requires numerical estimation of exit functionals. The approximation of

safetyarxiv-cs-ro

Hill Sampling for Test-Time Scaling: A Simple and Better Alternative to Repeated Sampling, Evolution, and Training

arXiv:2609.25510v1 Announce Type: new Abstract: Large language models (LLMs) can improve solutions to verifiable scientific and algorithmic problems by spending additional computation at test time. Re

History-Conditioned Flow Matching for Probabilistic Dynamics of Tendon-Driven Continuum Robots

arXiv:2609.25658v1 Announce Type: new Abstract: Deterministic dynamics modeling of tendon-driven continuum robots remains challenging owing to uncertainties in material behavior, tendon transmission,

researcharxiv-cs-ro

HOTICE: Whole-Body Humanoid Object Transportation in Cluttered Environments

arXiv:2609.25363v1 Announce Type: new Abstract: Object transportation is a fundamental capability for humanoid robots operating in real-world, human-centric environments, yet existing methods struggle

safetyarxiv-cs-ro

How Many Pixels Is a Digit Worth? Place-Aware Coordinate Entropy for GUI Agent Confidence Estimation

arXiv:2609.24277v1 Announce Type: new Abstract: GUI agents predict click coordinates as digit-token sequences, but standard text-LLM confidence estimation methods rank correct clicks from wrong ones o

agentsarxiv-cs-ai

How Strongly Should Task State Influence an LLM Agent?

arXiv:2609.25686v1 Announce Type: cross Abstract: Long-horizon assigned work requires an LLM agent to track the state of a task: which steps are done, blocked, cancelled, or open to repetition. Agent

safetyarxiv-cs-cl

Tutorials

How to Estimate Whether You Have Found Several Needles in a Haystack: Measuring Calibration in Multi-Label Text Classification

arXiv:2609.26468v1 Announce Type: new Abstract: A key factor in deciding whether to trust an automatic prediction is its confidence score, which should be calibrated to match the actual probability of

tutorialsarxiv-cs-cl

Human-guided physics-constrained AI agents construct an auditable model of soil-plug evolution

arXiv:2609.23360v1 Announce Type: cross Abstract: Engineering predictions require physical mechanisms to be translated consistently into equations, discretization, code, and validation, yet errors can

local-aiarxiv-cs-ai

HYDRA: Proactive Android Malware Drift Adaptation via Hierarchical Graph Contrastive Learning

arXiv:2609.26352v1 Announce Type: cross Abstract: Concept drift, driven by the rapid evolution of Android malware, severely degrades the performance of machine learning detectors. Current adaptation s

safetyarxiv-cs-lg

Hyperbolic Restricted Boltzmann Machine Neural Quantum State

arXiv:2609.26032v1 Announce Type: cross Abstract: We construct the first type of non-Euclidean non-autoregressive neural quantum state (NQS) in the form of the hyperbolic Restricted Boltzmann Machine

HySparse2: Hybrid Sparse Attention with Two-Level KV Sharing

arXiv:2609.26368v1 Announce Type: new Abstract: Long-horizon and multi-turn agents typically generate short actions and process long observations from tools and environments. This growing context dema

agentsarxiv-cs-cl

ICDAR2026 Competition on Multimodal Reasoning over Documents in Multiple Domains

arXiv:2609.25055v1 Announce Type: new Abstract: In this report we present results of the ICDAR2026 Competition on Multimodal Reasoning over Documents in Multiple Domains. This competition aimed to adv

agentsarxiv-cs-cl

Tutorials

Identifying Intelligent Processes via Online Sequential Testing

arXiv:2609.26193v1 Announce Type: cross Abstract: Active sequential hypothesis testing studies how to identify an unknown hypothesis with a given set of sensing actions. We study this in the setting o

tutorialsarxiv-cs-lg