Search: “tools”

Analytical Standard Errors for Exploratory Factor Solutions

arXiv:1811.05336v2 Announce Type: replace-cross Abstract: Inference for factor models is often hampered by the lack of tractable and accurate variance estimates, which can materially distort downstrea

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Anthropic brings Cowork out of the desktop and onto web and mobile

DGX agent

Anthropic PBC today announced it’s bringing its Claude Cowork agentic artificial intelligence assistant to mobile and the web, breaking it free from the desktop. Cowork allows users to harness the com

model-releasessiliconangle

7 Jul 2026

AppAgent: Multimodal Agents as Smartphone Users

arXiv:2312.13771v3 Announce Type: replace Abstract: Recent advancements in large language models (LLMs) have led to the creation of intelligent agents capable of performing complex tasks. This paper i

agentsarxiv-cs-cv

Automated Data Readiness for Scientific AI

arXiv:2607.02771v1 Announce Type: new Abstract: Leadership computing facilities steward large-scale scientific datasets that routinely require substantial transformation before serving as AI training

Autonomous Information Seeking: A Roadmap for Agentic Recommender Systems

arXiv:2607.04433v1 Announce Type: cross Abstract: The rapid integration of large language model-based agents into recommender systems has driven a shift from static, ranking-based pipelines toward aut

safetyarxiv-cs-cl

Beyond Heuristics: A Standardized Real2Sim Pipeline for Physical Human Robot Interaction in Human-in-the-Loop Simulation

arXiv:2607.03017v1 Announce Type: new Abstract: The aging global population drives demand for assistive robots, yet the safety risks and costs of physical testing make Human-in-the-Loop (HITL) simulat

safetyarxiv-cs-ro

Biological Motifs for Agentic Control

arXiv:2607.04240v1 Announce Type: new Abstract: The transition of Large Language Models (LLMs) from passive generators to autonomous agents has introduced significant challenges in reliability, securi

Build a serverless image editing agent with Amazon Bedrock AgentCore harness

This post walks through building a serverless image editor where users upload a photo, describe an edit in plain English, and receive the result in seconds. The agent runs on AgentCore harness without

agentsaws-ml-blog

Applications

CARL: Constraint-Aware Reinforcement Learning for Planning with LLMs

arXiv:2607.04854v1 Announce Type: new Abstract: Despite their strong reasoning capabilities and extensive world knowledge, Large Language Models (LLMs) frequently generate plans that violate task cons

applicationsarxiv-cs-ai

Chronos: The AI Co-Historian

arXiv:2604.03553v2 Announce Type: replace Abstract: AI is increasingly supporting, accelerating, and automating scientific discovery across subjects. Yet, the adoption of AI in historical research rem

CLABTOOLKIT: An Open-Source Toolkit for Routine Processing, Manipulation, and Visualization of Neuroimaging Data

arXiv:2607.02638v1 Announce Type: new Abstract: Neuroimaging research requires manipulating heterogeneous data structures, including raw MRI volumes, volumetric parcellations, cortical surface meshes,

ClinOCR-Bench: A Comprehensive Clinical Scanned Document Dataset for Optical Character Recognition Model Evaluation

arXiv:2607.03650v1 Announce Type: cross Abstract: Extracting textual information from scanned medical documents, such as external laboratory reports and manually filled forms, has been a major challen

CoGen3D: An Agentic Human-AI Co-Design Pipeline for 3D Asset Generation for Virtual Reality

arXiv:2607.03731v1 Announce Type: cross Abstract: Creating 3D assets for virtual reality requires modeling expertise, which restricts the authorship of immersive experiences. Existing generative AI to

Consistent but Miscalibrated: Evaluating LLM Limitations for Risk Communication in Natural Language

arXiv:2607.03882v1 Announce Type: cross Abstract: LLMs are increasingly deployed as post-hoc explainers of AI-generated outputs, yet it remains unclear whether they can reliably communicate probabilis

researcharxiv-cs-ai

Deep Learning-Based Characterization of Detonation-Cell Size Distributions in Soot-Foil Records

arXiv:2607.03764v1 Announce Type: cross Abstract: The geometric size and regularity of detonation cells are key physical parameters for characterizing detonation waves. Traditional manual measurement

Tutorials

Diagnosing Aerial-View Object Detectors with Foundational Image Generative Models

arXiv:2607.02718v1 Announce Type: cross Abstract: Recent advances in large-scale image generative models enable photorealistic scene synthesis with controllable attributes. Beyond data augmentation, t

tutorialsarxiv-cs-ai

Diffusion learning reveals viable parameter manifolds and compensation geometry in biological dynamical systems

model-releasesarxiv-cs-lg

arXiv:2607.03671v1 Announce Type: cross Abstract: Models of complex systems often have many parameters, yet are constrained by far fewer experimentally accessible observables: similar activity can eme

Distribution Matching Distillation Meets Reinforcement Learning

arXiv:2511.13649v5 Announce Type: replace Abstract: Distribution Matching Distillation (DMD) facilitates efficient inference by distilling multi-step diffusion models into few-step variants. Concurren

researcharxiv-cs-cv

Don't Blame the Large Language Model: How Scaffolding Evolution Shapes Coding Agent Quality

arXiv:2607.03691v1 Announce Type: cross Abstract: Coding agents, autonomous systems that use large language models (LLMs) to resolve software engineering tasks, rely on agentic scaffolding: a middlewa

Efficient privacy loss accounting for subsampling and random allocation

arXiv:2602.17284v2 Announce Type: replace Abstract: We consider the privacy amplification properties of a sampling scheme in which a user's data isused in k steps chosen randomly and uniformly from a

evalci: A Python Library for Statistically Rigorous Comparison of Language Model Evaluations

arXiv:2607.04429v1 Announce Type: cross Abstract: The dominant practice in language model evaluation is to report a single accuracy number per model and declare the higher one better, without testing

Explainable AI for Screening Abuse-Related Trauma in Bangladeshi Children: A Training-Free Multimodal Framework Evaluated on Noise-Aware Synthetic Data

arXiv:2607.04010v1 Announce Type: new Abstract: Bangladesh has an estimated 1.17 mental-health professionals per 100,000 population and only six child psychiatrists nationwide. No Bengali-language, cu

Tutorials

Explainable Bayesian deep learning through input-skip Latent Binary Bayesian Neural Networks

arXiv:2503.10496v2 Announce Type: replace-cross Abstract: Modeling natural phenomena with artificial neural networks (ANNs) often provides highly accurate predictions. However, ANNs often suffer from

tutorialsarxiv-cs-ai

Hardware

Fast Asymptotically Optimal Kinodynamic Planning via Vectorization

arXiv:2607.03987v1 Announce Type: new Abstract: Sampling-based motion planners have been shown to be effective for systems with complex kinodynamic constraints and high dimensionality. However, these

hardwarearxiv-cs-ro

FOI-O: An NZ-first ontology and verification methods package for Freedom of Information process modelling

arXiv:2607.02947v1 Announce Type: cross Abstract: Public official-information request records contain process signals. They can support research, workflow review, and human-supervised agent help. Yet

agentsarxiv-cs-cl

From Regulation to Requirements: An Automated Requirement Derivation and Explanation Pipeline

arXiv:2607.04448v1 Announce Type: cross Abstract: Ensuring software compliance with regulations such as the General Data Protection Regulation (GDPR) and the Artificial Intelligence Act (EU AI Act) po

Fun-TSG: A Function-Driven Multivariate Time Series Generator with Variable-Level Anomaly Labeling

arXiv:2604.14221v2 Announce Type: replace Abstract: Reliable evaluation of anomaly detection methods in multivariate time series remains an open challenge, largely due to the limitations of existing b

GLOW-FDG: Generalized cancer LesiOn Whole-body segmentation model for ^{18}F-FDG-PET/CT

arXiv:2607.03931v1 Announce Type: cross Abstract: Whole-body fluorodeoxyglucose positron emission tomography combined with computed tomography is widely used in cancer care, but manual lesion delineat

Governed Individuation: Cryptographically Decoupling an Agent's Learning from Its Authority

arXiv:2607.04613v1 Announce Type: new Abstract: Autonomous agents are moving from sandboxed text generators to operators of code, data, and physical infrastructure, and they increasingly learn while d

Tutorials

Hierarchical Anti-Aesthetics: Protecting Facial Privacy against Customized Diffusion Models

arXiv:2607.02038v2 Announce Type: replace Abstract: The rise of customized diffusion models has fueled a boom in personalized visual content creation, but it also introduces serious risks of malicious

tutorialsarxiv-cs-cv

HVR-Met: A Hypothesis-Verification-Replanning Agentic System for Extreme Weather Diagnosis

arXiv:2603.01121v2 Announce Type: replace Abstract: While deep learning-based weather forecasting paradigms have made significant strides, addressing extreme weather diagnostics remains a formidable c

Inclusive KL Gradient Flows: Otto-Wasserstein, Fisher-Rao-Gaussian, and Local-Estimator Dynamics

arXiv:2411.00214v2 Announce Type: replace-cross Abstract: Otto's Wasserstein gradient flow of the inclusive (forward) Kullback--Leibler (KL) divergence offers a principled framework for analyzing stat

Inelastic Constitutive Kolmogorov-Arnold Networks: A generalized framework for automated discovery of interpretable inelastic material models

arXiv:2602.17750v2 Announce Type: replace-cross Abstract: A key problem of solid mechanics is the identification of the constitutive law of a material, that is, the relation between strain history and

researcharxiv-cs-ai

Interpretable Human-Label-Free Deep Learning for Real-Bogus Classification with Uncertainty Quantification

arXiv:2607.05393v1 Announce Type: cross Abstract: Time-domain surveys generate many transient candidates, making Real-Bogus classification a critical step in automated discovery pipelines. Reliable la

IRC-Bench: Recognizing Entities from Contextual Cues in First-Person Reminiscences

arXiv:2605.06142v2 Announce Type: replace-cross Abstract: When people recount personal memories, they often refer to people, places, and events indirectly, relying on con-textual cues rather than expl

Applications

Measuring the Robustness of Audio Deepfake Detection under Real-World Corruption

arXiv:2503.17577v2 Announce Type: replace-cross Abstract: Deepfakes have emerged as a widespread and rapidly escalating concern in generative AI, spanning images, audio, and videos. Among these, audio

applicationsarxiv-cs-ai

Local Ai

Missing Data Imputation under Manifold Hypothesis

arXiv:2607.03641v1 Announce Type: cross Abstract: The manifold hypothesis posits that high-dimensional data are concentrated near a low-dimensional embedded manifold. Recent advances in mixture variat

local-aiarxiv-cs-lg

Hardware

MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems

arXiv:2607.02558v1 Announce Type: cross Abstract: As machine learning shifts from laboratory curiosity to critical infrastructure, the systems that sustain it span an extraordinary range, from sub-mil

hardwarearxiv-cs-lg

MMEarth-Bench: Global Model Adaptation via Multimodal Test-Time Training

arXiv:2602.06285v2 Announce Type: replace Abstract: Recent research in geospatial machine learning has demonstrated that models pretrained with self-supervised learning on Earth observation data can p

MorphQuad: Morphable Quadrotor for Superhuman Maneuverability, Manipulation, and Resiliency

arXiv:2607.02764v1 Announce Type: new Abstract: Infrastructure maintenance, contact-based inspection, and emergency response can benefit from aerial vehicles that act as a flying human hand with extre

researcharxiv-cs-ro

NRT-Bench: Benchmarking Multi-Turn Red-Teaming of LLM Operator Agents in Safety-Critical Control Rooms

arXiv:2606.20408v3 Announce Type: replace-cross Abstract: Large language model (LLM) agents are increasingly proposed as supervisory components for safety-critical systems, yet their robustness under

Physiological Noise Augmentation Improves Non-Invasive Brain-to-Speech

arXiv:2607.05165v1 Announce Type: new Abstract: Non-invasive brain-to-speech decoding aims to restore communication to patients suffering from neurodegenerative disease, without the risks of neurosurg

Position: Use Sparse Autoencoders to Discover Unknowns

arXiv:2506.23845v2 Announce Type: replace-cross Abstract: While sparse autoencoders (SAEs) have generated significant excitement, a series of negative results have added to skepticism about their usef

safetyarxiv-cs-ai

Predicting Biased Human Decision-Making with Large Language Models in Conversational Settings

arXiv:2601.11049v2 Announce Type: replace-cross Abstract: We examine whether large language models (LLMs) can predict biased decision-making in conversational settings, and whether their predictions c

Pretraining Curricula Enable Selective Fine-tuning

arXiv:2607.04846v1 Announce Type: cross Abstract: Transformers follow implicit curricula whereby some tasks are learned before others. However, how explicit pretraining curricula influence learning, g

safetyarxiv-cs-ai

Privacy-Preserving Industrial Ergonomics: mmWave-Based Automated REBA Scoring and Pose Estimation

arXiv:2607.02611v1 Announce Type: new Abstract: Work-related Musculoskeletal Disorders (WMSDs) require continuous ergonomic assessments. While Rapid Entire Body Assessment (REBA) is a gold-standard ob

researcharxiv-cs-cv

ProLaViT: Learning Progressive Latent Visual Thoughts in Structured Latent Space

arXiv:2607.02907v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable progress but still struggle with complex visual reasoning tasks requiring multi-step

researcharxiv-cs-cl

Robust Sparse Bayesian Learning Based on Minimum Error Entropy for Noisy High-Dimensional Brain Activity Decoding

model-releasesarxiv-cs-lg

arXiv:2508.11657v2 Announce Type: replace-cross Abstract: Objective: Sparse Bayesian learning provides an effective framework to solve high-dimensional problems in brain signal decoding. However, conv