Search: “applications”

arXiv:2609.38438v1 Announce Type: cross Abstract: Machine learning surrogate models offer a promising path toward accelerating plasma turbulence simulations. We present PreVAE-Turb, a surrogate modeli

hardwarearxiv-cs-lg

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A Rank Graduation metric for Algorithmic fairness

DGX agent

arXiv:2609.39025v1 Announce Type: new Abstract: Fairness assessment in algorithmic decisions that affect individuals, such as credit scoring, often relies on parity measures calculated at the aggregat

safetyarxiv-cs-lg

1 Oct 2026

A Reachability-based Safety Certificate for Dynamical System Motion Policies

arXiv:2609.38421v1 Announce Type: new Abstract: Dynamical Systems (DS) are reactive motion policies representing vector fields trained with theoretical guarantees of stability and convergence. To ensu

safetyarxiv-cs-ro

Airfoil2Vec: Spectral Geometry-Conditioned Neural Surrogate Models for Airfoil Aerodynamics and a Downforce-Generating CFD Dataset

arXiv:2609.38213v1 Announce Type: cross Abstract: We introduce a dataset of approximately 10,000 Reynolds-Averaged Navier-Stokes (RANS) simulations of steady, incompressible, two-dimensional subsonic

An Empirical Study of Architectural Shift from Traditional to AI-Enabled Simulink Controllers

arXiv:2609.38504v1 Announce Type: cross Abstract: Effective AI adoption in cyber-physical systems (CPS) depends on embedding design knowledge into engineering practice. Yet as AI-enabled components in

Auditing Agent Actions through Query-Conditioned Attribution

arXiv:2609.33676v2 Announce Type: replace Abstract: LLM agents increasingly take consequential actions through interactions with users, policies, and external tools. Auditing these agents requires aut

Local Ai

Belief-Aware Multi-Agent Path Finding under Map Uncertainty

arXiv:2609.40269v1 Announce Type: new Abstract: Multi-Agent Path Finding (MAPF) aims to find collision-free paths for multiple agents in a shared environment. Classical MAPF assumes that all static ob

local-aiarxiv-cs-ai

BMASH: Ball-Motion-Aware Soccer Header Spotting

arXiv:2609.39300v1 Announce Type: new Abstract: Recent advances in computer vision have made broadcast sports videos increasingly useful for event analysis, performance assessment, and player-safety a

safetyarxiv-cs-cv

Can Domain Generalization be Guaranteed in Small-Sample Learning?

arXiv:2609.39512v1 Announce Type: new Abstract: The small-sample learning problem remains a fundamental challenge in machine learning because limited training data lead to unstable model estimation an

Certified Approximation for Interpretable Representer Landmarks

arXiv:2609.38901v1 Announce Type: new Abstract: Representer explanations rank the training landmarks that most influence a self-supervised representation. At scale, this ranking rests on up to four st

ChartRevise: A Dataset and Evaluation Protocol for Exact Chart Editing via Code

arXiv:2609.38642v1 Announce Type: new Abstract: Chart editing requires cross-modal edit grounding, realizing a requested visual change in the code that draws it, with necessary related updates and wit

Agents

Composing Task-specific Agent Harnesses at Test Time with Reusable Primitives

arXiv:2609.38912v1 Announce Type: new Abstract: Agent harnesses govern how large language models (LLMs) gather context, invoke tools, verify results, preserve state, and terminate, largely affecting a

agentsarxiv-cs-ai

ContextAdapt: Evaluating Contextual Adaptation and Value Alignment in LLMs

arXiv:2609.38260v1 Announce Type: cross Abstract: Values such as honesty, autonomy, and confidentiality are often regarded as general principles underpinning AI alignment. However, what it means to ac

Agents

cua-speedrun: Standardized Benchmarking of the Speed of Computer-Use Agents

arXiv:2609.40284v1 Announce Type: cross Abstract: Computer use agents (CUAs), which use graphical user interfaces (GUIs) to complete tasks on a computer, have recently surpassed human performance on m

agentsarxiv-cs-ai

Delta-K: Boosting Multi-Instance Generation via Cross-Attention Augmentation

arXiv:2603.10210v2 Announce Type: replace-cross Abstract: While Diffusion Models excel in text-to-image synthesis, they frequently suffer from catastrophic concept omission when generating complex mul

Tutorials

Dynamics-Inspired Diffusion for Foreground-Preserving Document Background Editing

arXiv:2601.21857v2 Announce Type: replace Abstract: We revisit diffusion-based generation for structured visual content and identify a fundamental limitation of existing approaches: foreground preserv

tutorialsarxiv-cs-cv

EHR2Trace: Auditable EHR Data Infrastructure for Patient World Models and Clinical Agents

arXiv:2609.38193v1 Announce Type: cross Abstract: Patient world models and clinical agents aim to predict changes in patients' health and support clinical work. Developing these systems requires relia

ETHER: Aligning Emergent Communication for Hindsight Experience Replay

arXiv:2307.15494v3 Announce Type: replace-cross Abstract: Hindsight Experience Replay (HER) enhances sample efficiency in goal-conditioned reinforcement learning (RL) by relabelling failed trajectorie

EvoDuet: Bilevel Co-Evolution of Web Searching and Task Solving for Scientific Discovery

arXiv:2609.40340v1 Announce Type: new Abstract: Evolutionary search with large language models (LLMs) can stall when progress requires external knowledge the model lacks. Supplying relevant documents

Agents

Fast and Scalable Multi-Agent Distribution Matching via Partitioned Optimal Transport

arXiv:2609.38960v1 Announce Type: cross Abstract: This paper presents a scalable optimal-transport-based framework for terminal distribution matching in multi-agent systems. While optimal transport pr

agentsarxiv-cs-ro

Fast Generalized Neural Tangent Kernel Statistics via Trace Estimation

arXiv:2511.10796v2 Announce Type: replace-cross Abstract: The empirical state-space Neural Tangent Kernel (NTK) describes the local learning geometry of a finite-width neural network, but computing it

Fenchel Tilting: Weighted Correction for Efficient Finetuning of Generative Models

arXiv:2609.40030v1 Announce Type: cross Abstract: Adapting a pretrained generative model to an arbitrary preference expressed as a utility function underlies reward alignment, guided design, and const

Gaussian Stippling: Efficient Sorting-Free 3D Gaussian Rendering through Hybrid Sampling and Spatiotemporal Reconstruction

arXiv:2609.38488v1 Announce Type: cross Abstract: Conventional 3D Gaussian Splatting (3DGS) requires depth sorting and ordered alpha blending to correctly render overlapping Gaussian primitives. Stoch

researcharxiv-cs-cv

GLARE: Generating Listening Heads with Appropriate Reactions

arXiv:2609.40317v1 Announce Type: new Abstract: While talking head generation has advanced rapidly, generating natural listener behavior in dyadic conversations, which know when to react, how to react

safetyarxiv-cs-cv

Hybrid Methods for Robust Tabular Data Imputation

arXiv:2609.39613v1 Announce Type: new Abstract: Missing data are a fundamental challenge in statistical analysis and machine learning, as the choice of imputation method substantially impacts downstre

KVEraser: Learning to Steer KV Cache for Efficient Localized Context Erasing

arXiv:2606.17034v3 Announce Type: replace Abstract: Post-hoc context erasing over the KV cache is challenging because a local edit has a global consequence: once a span has been processed, its influen

Large Language Models are Approximate Survival Estimators

arXiv:2609.38181v1 Announce Type: new Abstract: Survival analysis estimates time-to-event outcomes from patient covariates and is widely used for medical risk assessment. Patients seeking prognostic i

Learning Semantic Inpainting for Animatable Gaussian Head Avatars

arXiv:2609.38343v1 Announce Type: new Abstract: We present SInGA, a novel method for learning Semantic Inpainting for animatable Gaussian head Avatars from a single image. Existing avatar approaches o

researcharxiv-cs-cv

Local-Minimum Escaper: Programmatic Subgoal Generation for Robust Navigation in Unknown Environments

arXiv:2609.38928v1 Announce Type: new Abstract: Mapless navigation in unknown and partially observable environments remains challenging for mobile robots, particularly when local minima prevent the ro

safetyarxiv-cs-ro

MRI Super-Resolution with RCDM/WaveMix and Task-Aware Segmentation

model-releasesarxiv-cs-cv

arXiv:2609.39083v1 Announce Type: new Abstract: Super-resolution and quality enhancement of 1.5,T brain MRI are normally validated with image-fidelity metrics, although their purpose is to improve dow

NAQD Env: A benchmark for selective withdrawal in language agents

arXiv:2609.38460v1 Announce Type: new Abstract: Language agents must revise planned actions when evidence changes, permission is revoked, or a stop instruction arrives. A useful response is selective:

OGPO: One-Step Generative Policy Optimization for Real-Time Robot Control

arXiv:2601.20701v2 Announce Type: replace Abstract: Real-time robot control demands fast action generation. Diffusion and flow matching policies for robot control require multi-step sampling, limiting

safetyarxiv-cs-ro

On the Complexity of Preference-Based Bandits

arXiv:2609.39351v1 Announce Type: new Abstract: We study preference-based bandits with general reward function classes, where a learner sequentially selects pairs of arms and observes binary preferenc

OSWorld-Science: A Benchmark of Computer Use Agents for Learning and Using Scientific Software

arXiv:2609.39903v1 Announce Type: new Abstract: Scientific software presents a demanding test for computer-using agents based on visual language models (VLMs): completing a research workflow requires

Parameterization method of reservoir properties for ensemble-based data assimilation using intermediate latent space of StyleGAN

arXiv:2609.39626v1 Announce Type: cross Abstract: Ensemble smoothers are the most successful and efficient techniques currently available for history matching. However, because these methods rely on G

RainAtlas: A Multi-Continental Dataset for Precipitation Downscaling

arXiv:2609.39833v1 Announce Type: new Abstract: Extreme rainfall events are increasing in intensity and frequency as climate change accelerates. While kilometer-scale precipitation forecasts are criti

Representation Risk in Pretrained Image Encoders

model-releasesarxiv-cs-cv

arXiv:2609.35470v1 Announce Type: cross Abstract: Applied researchers increasingly convert images into features with pretrained encoders, then use those features in a downstream prediction model. The

Searching for BSM Experimental Signatures with Large Lagrangian Models

arXiv:2609.38309v1 Announce Type: cross Abstract: The search for physics Beyond the Standard Model (BSM) is generally limited not by the supply of theory descriptions but by the lack of discriminating

Semantic Misalignment in Vision-Language Models under Perceptual Degradation

arXiv:2601.08355v3 Announce Type: replace Abstract: Vision-Language Models (VLMs) are increasingly deployed in autonomous driving and embodied AI systems, where reliable perception is critical for saf

safetyarxiv-cs-cv

Semantic Watermarking for Malicious Image Manipulation Detection

arXiv:2609.39623v1 Announce Type: new Abstract: The proliferation of high-fidelity generative editing models has made it possible to inject violent or sexual content into otherwise ordinary images whi

researcharxiv-cs-cv

Superficial Reflection or Genuine Thought? A Fine-Grained Cognitive Analysis of Large Reasoning Models

arXiv:2512.00729v2 Announce Type: replace Abstract: Motivated by the observed human-like behaviours in Large Reasoning Models (LRMs), this paper introduces a comprehensive taxonomy to characterise ato

Tutorials

TACIT: Optimization Models that Learn from Their Mistakes

arXiv:2609.38434v1 Announce Type: cross Abstract: Real-world optimization problems are difficult to model accurately because many objectives and constraints reside in domain experts' tacit knowledge,

tutorialsarxiv-cs-ai

TALK-Dem: Benchmarking Embodied Task Planning under Dementia-Associated Communication Patterns

arXiv:2609.38371v1 Announce Type: cross Abstract: Existing LLM-driven robot task planners rely on a taken-for-granted assumption of an ideal user whose instructions are clear, complete, and task-focus

Local Ai

Template-Search Domain Adaptation via Multi-Stage Feature Alignment for Cross-Modal Object Tracking

arXiv:2609.38637v1 Announce Type: cross Abstract: Visual object tracking typically assumes that the initial template and subsequent search frames share the same sensing modality. In practice, sensor a

local-aiarxiv-cs-ai

The Geometry of Randomized Smoothing on Feasible Sets

arXiv:2609.39497v1 Announce Type: new Abstract: Randomized smoothing certifies the probability of a fixed output event as the center of Gaussian noise moves. Feasibility or confidence filtering report

Time-adaptive infinite-dimensional Gaussian process regression on manifolds

arXiv:2603.21144v2 Announce Type: replace-cross Abstract: This paper proposes a new formulation of functional Gaussian Process regression on manifolds, based on an Empirical Bayes approach, in the spa

Token Space: A Category Theory Framework for AI Computations

arXiv:2404.11624v2 Announce Type: replace-cross Abstract: We introduce the Token Space, a categorical framework for AI computations. A Token is a finite tuple whose entries are elements of a carrier s

Tutorials

Towards Open-Ended Visual Scientific Discovery with Sparse Autoencoders

arXiv:2511.17735v2 Announce Type: replace Abstract: Foundation models in several scientific domains, including visual domains, learn representations that capture complex semantics from their respectiv

tutorialsarxiv-cs-cv