applications

An Algebraic View of the Expressivity of Recurrent Language Models

arXiv:2606.01765v1 Announce Type: cross Abstract: What formal languages can a recurrent neural language model recognize? Formal results in the literature conflict: some authors report Turing-completen

Applications

Another thing about AI writing is that while a single instance of AI writing on a topic may be fine, any situation where lots of people use …

DGX agent

Another thing about AI writing is that while a single instance of AI writing on a topic may be fine, any situation where lots of people use AI to respond to a particular prompt (comments sections, hom

applicationsethan-mollick--x

2 Jun 2026

Anyscale on Azure Enters Public Preview: Build and Deploy AI at Scale Inside Your Own Azure Tenant

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applicationsanyscale-ray

Are Large Reasoning Models Interruptible?

arXiv:2510.11713v4 Announce Type: replace Abstract: Real-world applications of Large Reasoning Models (LRMs) often require reasoning about changing prompts or environments. In this work, we challenge

Auteur: Language-Driven Cinematographic Framing for Human-Centric Video Generation

arXiv:2606.01900v1 Announce Type: new Abstract: Generative video models have achieved remarkable visual fidelity and temporal coherence, yet intentional camera control remains elusive. Existing framew

AutoForest: Automatically Generating Forest Plots from Biomedical Studies with End-to-End Evidence Extraction and Synthesis

arXiv:2606.02403v1 Announce Type: cross Abstract: Systematic reviews rely on forest plots to synthesise quantitative evidence across biomedical studies, but generating them remains a fragmented and la

Bayesian meta-learning for modeling Alzheimer's disease progression

arXiv:2606.02228v1 Announce Type: cross Abstract: Predicting whether an individual with Alzheimer's disease will experience mild or severe disease progression is essential for personalized treatment.

Beyond parsing X12: Closing the gap for revenue cycle workflows in healthcare

This article discusses how healthcare organizations can move beyond basic X12 EDI parsing to implement more comprehensive revenue cycle management workflows using data analytics platforms. It likely a

applicationsdatabricks

Building apps has never been easier. With Sites, Codex can turn your work, ideas, and plans into an interactive website or app your team can…

Building apps has never been easier. With Sites, Codex can turn your work, ideas, and plans into an interactive website or app your team can explore, use, and share with a URL. Rolling out to Business

applicationsopenai--x

c-TPE: Tree-structured Parzen Estimator with Inequality Constraints for Expensive Hyperparameter Optimization

arXiv:2211.14411v5 Announce Type: replace-cross Abstract: Hyperparameter optimization (HPO) is crucial for strong performance of deep learning algorithms and real-world applications often impose some

CardioLens: Revealing the Clinical Reality Gap of MLLMs via Multi-Sequence Cardiac MRI Evaluations

arXiv:2606.00123v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have shown strong performance on public medical benchmarks, yet existing evaluations often remain weak proxie

Cellwise and Casewise Robust Covariance in High Dimensions

arXiv:2505.19925v2 Announce Type: replace-cross Abstract: The sample covariance matrix is a cornerstone of multivariate statistics, but it is highly sensitive to outliers. These can be casewise outlie

ChronosAD: Leveraging Time Series Foundation Models for Accurate Anomaly Detection

arXiv:2606.01300v1 Announce Type: cross Abstract: Time series anomaly detection is a crucial task in various domains, including finance, healthcare, and industry. However, existing methods often strug

CLSP-REQA: A Real-Time Quality-Aware Closed-Loop Seizure Prediction Framework with Mamba-BiLSTM and Confidence-Gated Intervention

arXiv:2606.00074v1 Announce Type: cross Abstract: Reliable seizure prediction is a prerequisite for closed-loop neurostimulation therapy, yet existing methods rarely account for the variability in EEG

Computer-use agents are moving from the cloud to your local machine. Fast. When we launched Holo3 two months ago, the production feedback wa…

applicationsclem-delangue--x

Computer-use agents are moving from the cloud to your local machine. Fast. When we launched Holo3 two months ago, the production feedback was clear: digital agents need to be blazing fast, cost-effect

Conditional Collapse in Sign Language Production: A Diagnostic and a Scaling Argument

arXiv:2606.01643v1 Announce Type: new Abstract: Sign Language Production (SLP) is the task of generating avatar sign language motion from natural language text. The quality of the generated motion is

Contrastive Augmented Transformer with Domain-specific Enhancement for Robust Multi-scenario Metal Surface Defect Detection

arXiv:2606.01962v1 Announce Type: new Abstract: Metal surface defect detection is critical for maintaining product quality in industrial manufacturing. However, it faces significant challenges, includ

Cooperation of Experts: Fusing Heterogeneous Information with Large Margin

arXiv:2505.20853v3 Announce Type: replace-cross Abstract: Fusing heterogeneous information remains a persistent challenge in modern data analysis. While significant progress has been made, existing ap

Coupling Language Models with Physics-based Simulation for Synthesis of Inorganic Materials

arXiv:2606.00315v1 Announce Type: new Abstract: Modern generative machine learning (ML) models can propose novel inorganic crystalline materials with targeted properties; however, synthesis planning o

Custom model training is bringing enterprise AI from experimentation to production

As artificial intelligence moves from proof of concept into enterprise production, custom model training on governed data is emerging as the critical unlock for organizations that need domain-specific

applicationssiliconangle

Degeneration of Sliding-Window Factor Graph Optimization into Iterated Extended Kalman Filtering

arXiv:2511.00306v2 Announce Type: replace Abstract: Sliding window factor graph optimization (SW-FGO) is widely recognized for its robustness, yet its theoretical relationship with the extended Kalman

applicationsarxiv-cs-ro

Digital-to-Physical Transfer of Adversarial Patches for Aerial Vehicle Detection

arXiv:2606.00159v1 Announce Type: cross Abstract: Deep neural network (DNN)-based object detectors are widely used for analyzing aerial and satellite imagery in applications such as environmental moni

Discovering Nonlinear Static Relationships in Unlabeled Dataset using Autoencoder with Ordered Variance

arXiv:2402.14031v2 Announce Type: replace-cross Abstract: This paper presents an autoencoder with ordered variance (AEO), in which the conventional reconstruction loss is augmented by a variance-based

Distributed GNEP Algorithms without Multiplier Sharing and Applications to Multi-Robot Coordination and Contextual Bandit-Based Active Learning

arXiv:2606.00759v1 Announce Type: new Abstract: Recent advances in artificial intelligence have expanded the focus from classical optimization to include equilibrium analysis in noncooperative games.

EnergyMamba: An Uncertainty-Aware Graph-Enhanced Selective State Space Model for Energy Consumption Prediction

arXiv:2606.00506v1 Announce Type: new Abstract: Energy consumption prediction is essential for efficient grid management, demand-side optimization, and sustainable energy planning. Although advanced m

Enhancing BiGRU with a KAN Block for Legal Document Classification and Summarization

arXiv:2606.00116v1 Announce Type: cross Abstract: This study introduces a novel architecture of KAN-based BiGRU model for the task of classification and summarization of legal documents in a low-resou

Evaluating Bivariate Causal Statements Based on Mutual Compatibility

arXiv:2606.00278v1 Announce Type: new Abstract: For many real-world systems, causal ground truth is difficult to obtain, making claims about causal effects hard to assess. We develop methods for evalu

Evolving to the Aesthetics of a Vision-Language Model

arXiv:2606.00112v1 Announce Type: cross Abstract: Evolutionary systems have demonstrated remarkable results in creative domains, with recent applications in generative typography, design, and music. H

Exploiting weight-space symmetries for approximating curvature

arXiv:2606.00442v1 Announce Type: new Abstract: Many machine learning techniques rely on approximating a loss function's curvature, but this is notoriously hard to do at the scale of modern deep netwo

Fine-Tuning Without Forgetting In-Context Learning: A Theoretical Analysis of Linear Attention Models

arXiv:2602.23197v2 Announce Type: replace Abstract: Transformer-based large language models exhibit in-context learning, enabling adaptation to downstream tasks via few-shot prompting with demonstrati

For organizations already using Azure and Fabric, this means a much faster path from governed data to internal software. • Build apps secure…

For organizations already using Azure and Fabric, this means a much faster path from governed data to internal software. • Build apps securely on top of governed Fabric data • Use existing authenticat

applicationsreplit--x

From Capability Models to Automated Planning: An AAS-Native Approach for Automatic PDDL Generation

arXiv:2606.02167v1 Announce Type: new Abstract: Engineers designing production systems need to verify that a given layout supports all required production sequences. Automated planning techniques can

From Human Videos to Robot Manipulation: A Survey on Scalable Vision-Language-Action Learning with Human-Centric Data

arXiv:2606.00054v1 Announce Type: cross Abstract: Recent progress in generalizable embodied control has been driven by large-scale pretraining of Vision-Language-Action (VLA) models. However, most exi

From Rashomon Theory to PRAXIS: Efficient Decision Tree Rashomon Sets

arXiv:2606.00202v1 Announce Type: cross Abstract: Standard machine learning pipelines often admit many near-optimal models. These 'Rashomon sets' pose a range of challenges and opportunities for uncer

FW-NKF: Frequency-Weighted Neural Kalman Filters

arXiv:2606.02251v1 Announce Type: cross Abstract: Robust state estimation is central to robotic autonomy, yet classical Kalman filters struggle with frequency-dependent disturbances and model mismatch

GIFT: Geometry-Induced Functional Transfer for Category-level Object Manipulation

arXiv:2503.15371v2 Announce Type: replace-cross Abstract: Robotic manipulation of unfamiliar objects in new environments is challenging due to limited generalisation capabilities. We propose a new ski

Graph-Augmented Retrieval for Cross-Entity Financial Sentiment Analysis: A Comparative Study

arXiv:2606.00062v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has become foundational for grounding large language models in domain-specific corpora, yet conventional vector-bas

GraspGen-X: Cross-Embodiment 6-DOF Diffusion-based Grasping

arXiv:2606.00998v1 Announce Type: new Abstract: We study cross-embodiment 6-DOF robot grasping. Unlike prior works, we require the model not only to generalize to novel objects / scenes but also to no

applicationsarxiv-cs-ro

Here's the paper, which confirms that big changes are happening very quickly. Some really interesting approaches to teasing out what is happ…

applicationsethan-mollick--x

Here's the paper, which confirms that big changes are happening very quickly. Some really interesting approaches to teasing out what is happening in the software development cycle as well: https://pap

HPE posts huge earnings beat thanks to AI servers, sending its stock skyward

Hewlett Packard Enterprise Co.’s artificial intelligence servers sold like crazy during its fiscal second quarter, powering the company to an impressive earnings and revenue beat, and the company’s st

applicationssiliconangle

Hybrid Neural Ordinary Differential Equations for Data-Efficient Polymerization Modeling with Incomplete Kinetics

arXiv:2606.02145v1 Announce Type: new Abstract: Accurate prediction of polymerization dynamics is essential for process design, control, and optimization. Yet, purely mechanistic models require labor-

I have seen senior managers outpace ICs, and I have seen ICs run circles around the org chart. Titles tell you almost nothing about who is a…

applicationsallie-k--miller--x

I have seen senior managers outpace ICs, and I have seen ICs run circles around the org chart. Titles tell you almost nothing about who is actually going to operate well in the next few years (and mig

IBM to invest $10 billion in quantum computing

IBM announced a $10 billion investment in quantum computing to advance the development and commercialization of quantum technologies. The investment aims to accelerate quantum hardware improvements, e

applicationsibm-research

ImagineUAV: Aerial Vision-Language Navigation via World-Action Modeling and Kinodynamic Planning

arXiv:2606.01205v1 Announce Type: new Abstract: Vision-language navigation (VLN) for UAVs demands grounding free-form instructions into 6-DoF flight under partial observability. While Vision-Language-

applicationsarxiv-cs-ro

Improving Hospital Process Management through Process Mining: A Case Study on COVID-19 Clinical Pathways

arXiv:2606.00041v1 Announce Type: cross Abstract: This study analyzes COVID-19 care pathways using the COVID Data for Shared Learning dataset. We build a transparent, reproducible pipeline that transf

Incentives, Equilibria, and the Limits of Healthcare AI: A Game-Theoretic Perspective

arXiv:2603.28825v2 Announce Type: replace-cross Abstract: Using a stylised coordination problem drawn from inpatient capacity management, three archetypal forms of AI deployment are described: effort-

InfoAtlas: A Foundation Model for Zero-Shot Statistical Dependence Estimate

arXiv:2606.00241v1 Announce Type: cross Abstract: Measuring statistical dependency between high-dimensional random variables is a fundamental task in data science and machine learning. Neural mutual i

InfoMerge: Information-aware Token Compression for Efficient Video Large Language Models

arXiv:2606.02161v1 Announce Type: cross Abstract: Video Large Language Models (Video-LLMs) achieve strong performance in video understanding, but their excessive visual tokens bring substantial comput