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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

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DGX agent

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

model-releasesarxiv-cs-ai

14 May 2026

HADAR-Based Thermal Infrared Hyperspectral Image Restoration

model-releasesarxiv-cs-cv

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

researcharxiv-cs-lg

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

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

Humanwashing -- It Should Leave You Feeling Dirty

arXiv:2605.13723v1 Announce Type: cross Abstract: The phrase 'human in the loop' is increasingly used to imply a sense of safety in relation to AI decision systems. It shouldn't. There are contexts wh

Agents

IdeaForge: A Knowledge Graph-Grounded Multi-Agent Framework for Cross-Methodology Innovation Analysis and Patent Claim Generation

arXiv:2605.13311v1 Announce Type: new Abstract: Current AI-assisted innovation systems typically apply a single ideation methodology (such as TRIZ or Design Thinking) using sequential prompt-based wor

agentsarxiv-cs-ai

Identification of Non-Transversal Bifurcations of Linkages

arXiv:2605.13094v1 Announce Type: new Abstract: The local analysis is an established approach to the study of singularities and mobility of linkages. Key result of such analyses is a local picture of

researcharxiv-cs-ro

Agents

Identifying AI Web Scrapers Using Canary Tokens

arXiv:2605.13706v1 Announce Type: cross Abstract: From pre-training to query-time augmentation, web-scraped data helps to improve the quality and contextual relevancy of content generated by large lan

agentsarxiv-cs-ai

Identifying the nonlinear string dynamics with port-Hamiltonian neural networks

arXiv:2605.12785v1 Announce Type: new Abstract: Hybrid machine learning combines physical knowledge with data-driven models to enhance interpretability and performance. In this context, Port-Hamiltoni

IGT-OMD: Implicit Gradient Transport for Decision-Focused Learning under Delayed Feedback

arXiv:2605.12693v1 Announce Type: new Abstract: Decision-focused learning trains predictive models end-to-end against downstream decision loss, but online settings suffer delayed feedback: outcomes ma

researcharxiv-cs-lg

ImageAttributionBench: How Far Are We from Generalizable Attribution?

model-releasesarxiv-cs-cv

arXiv:2605.12967v1 Announce Type: new Abstract: The rapid advancement of generative AI has enabled the creation of highly realistic and diverse synthetic images, posing critical challenges for image p

Img2CADSeq: Image-to-CAD Generation via Sequence-Based Diffusion

arXiv:2605.13293v1 Announce Type: new Abstract: Boundary Representation (BRep) is the standard format for Computer-Aided Design (CAD), yet reconstructing high-quality BReps from single-view images rem

Implicit Behavioral Decoding from Next-Step Spike Forecasts at Population Scale

arXiv:2605.12999v1 Announce Type: cross Abstract: Closed-loop brain-computer interfaces often require both a forecast of upcoming neural population activity and a readout of the animal's behavioral st

Imposing Boundary Conditions on Neural Operators via Learned Function Extensions

arXiv:2602.04923v2 Announce Type: replace Abstract: Neural operators have emerged as powerful surrogates for the solution of partial differential equations (PDEs), yet their ability to handle general,

Improved monocular depth prediction using distance transform over pre-semantic contours with self-supervised neural networks

arXiv:2605.08320v1 Announce Type: cross Abstract: Monocular depth estimation (MDE) with self-supervised training approaches struggles in low-texture areas, where photometric losses may lead to ambiguo

Improving Classifier-Free Guidance of Flow Matching via Manifold Projection

arXiv:2601.21892v2 Announce Type: replace-cross Abstract: Classifier-free guidance (CFG) is a widely used technique for controllable generation in diffusion and flow-based models. Despite its empirica

Improving Code Translation with Syntax-Guided and Semantic-aware Preference Optimization

arXiv:2605.13229v1 Announce Type: new Abstract: LLMs have shown immense potential for code translation, yet they often struggle to ensure both syntactic correctness and semantic consistency. While pre

Improving Diffusion Posterior Samplers with Lagged Temporal Corrections for Image Restoration

arXiv:2605.12573v1 Announce Type: cross Abstract: Diffusion-based posterior sampling (PS) is a leading framework for imaging inverse problems, combining learned priors with measurement constraints. Ye

Improving Reproducibility in Evaluation through Multi-Level Annotator Modeling

arXiv:2605.13801v1 Announce Type: cross Abstract: As generative AI models such as large language models (LLMs) become more pervasive, ensuring the safety, robustness, and overall trustworthiness of th

In-Situ Behavioral Evaluation for LLM Fairness, Not Standardized-Test Scores

arXiv:2605.12530v1 Announce Type: cross Abstract: LLM fairness should be evaluated through in-situ conversational behavior rather than standardized-test Q&A benchmarks. We show that the standardized-t

IndicMedDialog: A Parallel Multi-Turn Medical Dialogue Dataset for Accessible Healthcare in Indic Languages

arXiv:2605.13292v1 Announce Type: cross Abstract: Most existing medical dialogue systems operate in a single-turn question--answering paradigm or rely on template-based datasets, limiting conversation

Inducing Overthink: Hierarchical Genetic Algorithm-based DoS Attack on Black-Box Large Language Reasoning Models

arXiv:2605.13338v1 Announce Type: cross Abstract: Large Reasoning Models (LRMs) are increasingly integrated into systems requiring reliable multi-step inference, yet this growing dependence exposes ne

Tutorials

Inference-Time Dynamic Modality Selection for Incomplete Multimodal Classification

arXiv:2601.22853v3 Announce Type: replace Abstract: Multimodal deep learning (MDL) has achieved remarkable success across various domains, yet its practical deployment is often hindered by incomplete

tutorialsarxiv-cs-cv

Inference-Time Machine Unlearning via Gated Activation Redirection

arXiv:2605.12765v1 Announce Type: new Abstract: Large Language Models memorize vast amounts of training data, raising concerns regarding privacy, copyright infringement, and safety. Machine unlearning

Information as Maximum-Caliber Deviation: A bridge between Integrated Information Theory and the Free Energy Principle

arXiv:2605.12536v1 Announce Type: cross Abstract: The Free Energy Principle (FEP) is a leading framework for mathematically modeling self-organization and learning, while Integrated Information Theory

Tutorials

Inline Critic Steers Image Editing

arXiv:2605.12724v1 Announce Type: cross Abstract: Instruction-based image editing exhibits heterogeneous difficulty not only across cases but also across regions of an image, motivating refinement app

tutorialsarxiv-cs-ai

Integration of an Agent Model into an Open Simulation Architecture for Scenario-Based Testing of Automated Vehicles

arXiv:2605.13539v1 Announce Type: new Abstract: Simulative and scenario-based testing are crucial methods in the safety assurance for automated driving systems. To ensure that simulation results are r

safetyarxiv-cs-ro

Interpretable Machine Learning for Antepartum Prediction of Pregnancy-Associated Thrombotic Microangiopathy Using Routine Longitudinal Laboratory Data

arXiv:2605.13786v1 Announce Type: new Abstract: Background: Pregnancy-associated thrombotic microangiopathy (P-TMA) is rare but life-threatening. Early risk prediction before overt clinical presentati

researcharxiv-cs-lg

interwhen: A Generalizable Framework for Steering Reasoning Models with Test-time Verification

arXiv:2602.11202v3 Announce Type: replace-cross Abstract: Reasoning models produce long traces of intermediate decisions and tool calls, making test-time verification important for ensuring correctnes