Search: “applications”

Reaction-network reasoning with frontier models for experimentally confirmed catalyst-selectivity hypotheses

arXiv:2607.08003v1 Announce Type: cross Abstract: Catalysts are essential for sustainable chemical manufacturing, yet discovering novel architectures remains a bottleneck dominated by trial-and-error

10 Jul 2026

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Applications

Deployment Risk Assessment Using Diff-Aware Features: A Case Study at Prime Video

DGX agent

arXiv:2607.06766v1 Announce Type: cross Abstract: At Amazon Prime Video, we face the critical operational challenge of managing code deployments during live events and rapid feature releases without c

applicationsarxiv-cs-lg

9 Jul 2026

Prior-aware and Context-guided Group Sampling for Active Probabilistic Subsampling

arXiv:2607.07083v1 Announce Type: cross Abstract: Subsampling significantly reduces the number of measurements, thereby streamlining data processing and transfer overhead, and shortening acquisition t

QIZ Security raises $17M seed round for post-quantum readiness platform

Cybersecurity startup QIZ Security Ltd. today announced it has raised 17 million in seed funding to expand a platform that discovers and governs the encryption buried across enterprise systems ahead o

applicationssiliconangle

Model Releases

Safely run AI-generated code in Cloud Run sandboxes

model-releasesgoogle-cloud-ai

Here’s a question we hear often at Google Cloud: How do you safely run AI-generated code or untrusted binaries without putting your host application, data, and cloud credentials at risk? In other word

Tensorized algorithms and scalable filtering methods for hidden Markov and factorial hidden Markov models

arXiv:2607.07008v1 Announce Type: cross Abstract: A common method for the representation and analysis of time-series data is the hidden Markov model (HMM), where each observation is associated with a

Try Grok 4.5 for free, an all new Opus-class model that is fast and low cost. Great for real-world coding and engineering tasks.

Grok 4.5 is a new Opus-class AI model released by xAI that offers improved speed and cost efficiency compared to previous versions. The model is positioned as particularly well-suited for real-world c

applicationselon-musk--x

VultronRetriever: Open Visual Document Retrieval Models Built for Scale

Introducing VultronRetriever, a family of open visual document retrieval models built on Vultr. Achieve state-of-the-art retrieval performance with smaller indexes, higher throughput, and support for

applicationsvultr

We evaluated 30+ frontier embodied AI models. The result is clear: current generalist robot policies are still far from robust real-world ma…

applicationsyohei-nakajima--x

A comprehensive evaluation of over 30 frontier embodied AI models reveals that current generalist robot policies lack the robustness needed for reliable real-world manipulation tasks. The analysis dem

Medix: Out-of-Distribution Detection from Unlabeled Wild Data via Robust Gradient Statistics

arXiv:2510.06505v2 Announce Type: replace-cross Abstract: Out-of-distribution (OOD) detection plays a crucial role in ensuring the robustness of machine learning systems deployed in real-world applica

MorphGS: Morphology-Adaptive Articulated 3D Motion Transfer from Videos

arXiv:2601.02716v3 Announce Type: replace Abstract: Transferring articulated motion from monocular videos to rigged 3D characters is challenging due to pose ambiguity in 2D observations and morphologi

Prior-First, Condition-Second: Scalable and Controllable Hand Motion Completion

arXiv:2607.05938v1 Announce Type: cross Abstract: Synthesizing hand motion that matches the full body motion and the semantic labels is a difficult task due to their high degrees of freedom and the la

The GenAI Skill Bypass: Mapping Divergent Pathways of University Students and Staff AI Literacy

arXiv:2607.05411v1 Announce Type: cross Abstract: Higher education institutions are increasingly expected to ensure that both students and staff develop Generative AI (GenAI) literacies. In response,

Model Releases

20 questions for the Agentic Enterprise (and how Agent Platform can help)

model-releasesgoogle-cloud-ai

If you’re an IT leader, you might be getting a lot of questions about how to build and deploy agents. The pressure to move fast is intense, but the engineering reality is incredibly complex. Where do

Advances in Neural Controlled Differential Equations

arXiv:2607.05280v1 Announce Type: new Abstract: Many real-world systems evolve continuously, yet most machine learning models interpret time series as discrete sequences. Continuous-time approaches in

AnyDesign: Versatile Area Fashion Editing via Mask-Free Diffusion

arXiv:2408.11553v5 Announce Type: replace Abstract: Fashion image editing aims to modify a person's appearance based on a given instruction. Existing methods require auxiliary tools like segmenters an

Aperture-aware Dispersion 5-D Light-field Imaging Spectrometer

arXiv:2607.04635v1 Announce Type: new Abstract: Enhancing perceptual dimensions while miniaturizing imaging systems presents significant challenges for high-dimensional visual sensing. Conventionally,

Agents

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

Boosting Automatic Exercise Evaluation Through Musculoskeletal Simulation-Based IMU Data Augmentation

arXiv:2505.24415v2 Announce Type: replace-cross Abstract: Automated evaluation of movement quality can enhance physiotherapeutic treatment and sports training by providing objective, real-time feedbac

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

Data-Driven Soft Labeling Scales DNA Read Classification to Whole-Body Cell-Type Deconvolution

arXiv:2607.04987v1 Announce Type: new Abstract: Cell-type deconvolution, the task of estimating the proportions of constituent cell types in a heterogeneous biological sample, is a core problem in com

Exploring SAM Supervision for Fine-Grained UAV Target Segmentation under Data Scarcity

arXiv:2607.03754v1 Announce Type: new Abstract: Unmanned aerial vehicle (UAV) target segmentation remains challenging due to the small size of objects, appearance variations, cluttered backgrounds, an

Invisible Strings: Deriving Puppetry Principles and their Hidden Connections to Robot Behavior Design

arXiv:2607.03289v1 Announce Type: new Abstract: When designing robots' nonverbal behaviors, many researchers have turned to arts-based insights, such as Disney's Animation Principles. Yet, while these

Knowledge-Informed Local Causal Discovery of Optimal Adjustment Sets

arXiv:2607.04447v1 Announce Type: new Abstract: Local causal discovery is a scalable alternative to global structure learning. However, it can struggle to identify valid adjustment sets in data-scarce

MDL Meets Latent Confounders: LNML-based Causal Discovery

arXiv:2607.04133v1 Announce Type: new Abstract: Causal discovery with nonlinear mechanisms and latent confounders remains challenging. Existing methods often rely on either linear assumptions or causa

One Framework for All: Cross-Modal Membership Inference for Generative Models

arXiv:2607.04339v1 Announce Type: cross Abstract: Large generative models across text-to-text, text-to-image, and image-to-text modalities have been shown to pose significant privacy risks. One fundam

P^3: Toward Versatile Embodied Agents

arXiv:2508.07033v2 Announce Type: replace Abstract: Embodied agents have shown promising generalization capabilities across diverse physical environments, making them essential for a wide range of rea

REAL-OW: Rehearsal-free Open World Object Detection with Low-Rank Adaptation and Dual-Stage Objectness Modeling

arXiv:2607.03004v1 Announce Type: new Abstract: Open-World Object Detection (OWOD) requires detectors to identify previously unseen objects as unknown and incrementally incorporate them into the set o

SAVER: Mitigating Hallucinations in Large Vision-Language Models via Style-Aware Visual Early Revision

arXiv:2508.03177v2 Announce Type: replace Abstract: Large Vision-Language Models (LVLMs) recently achieve significant breakthroughs in understanding complex visual-textual contexts. However, hallucina

The Bayesian Approach to Continual Learning: An Overview

arXiv:2507.08922v3 Announce Type: replace-cross Abstract: Continual learning is an online paradigm where a learner continually accumulates knowledge from different tasks encountered over sequential ti

Unveiling the Unborn: Advancing Fetal Health Classification through Machine Learning

arXiv:2310.00505v3 Announce Type: replace-cross Abstract: Fetal health classification is a critical task in obstetrics, enabling early identification and management of potential health problems. Howev

Walma: Learning to See Memory Corruption in WebAssembly

arXiv:2603.24167v2 Announce Type: replace-cross Abstract: WebAssembly's (Wasm) monolithic linear memory turns a single memory-corruption bug into a bidirectional threat: a compromised module can attac

How Should Transformers Encode Numeric Values in Electronic Health Records?

arXiv:2607.01391v1 Announce Type: cross Abstract: How do we encode numeric values in transformer-based sequence processing, particularly in electronic health record (EHR) data? We systematically compa

Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming

arXiv:2601.03946v3 Announce Type: replace-cross Abstract: We consider the densest submatrix problem, which seeks the submatrix of fixed size of a given binary matrix that contains the most nonzero ent

Robust Image Processing Techniques for Construction Environment Monitoring Using Underwater Robots

arXiv:2607.01915v1 Announce Type: cross Abstract: This paper proposes a robust image processing framework for underwater robot-based construction environment monitoring, targeting complex degradations

Agents

Vercel's Andrew Qu on why agents are a new kind of software

Andrew Qu from Vercel discusses how AI agents represent a fundamentally different category of software compared to traditional applications, exploring their unique characteristics and implications for

agentslatent-space

Constrained Bayesian Optimisation with Multiple Information Sources

arXiv:2607.00865v1 Announce Type: new Abstract: Bayesian Optimisation (BO) under unknown constraints is particularly challenging when feasible regions are small. In such settings, existing methods tha

LLMs in the Real World: Evaluating 'AI' in Emergency Contexts

arXiv:2607.00019v1 Announce Type: cross Abstract: This paper offers a call to action. We urge our colleagues in the research community to play a greater role in the articulation of our findings to the

Stitched Embeddings: A Unified Latent Space for 3D Garments and 2D Patterns

arXiv:2607.00829v1 Announce Type: new Abstract: While garments are essential for realistic digital humans, their topological variety makes them much harder to model than parametric bodies. Traditional

SuperFlex: Deformable Superquadrics for Point Cloud Decomposition

arXiv:2607.01015v1 Announce Type: new Abstract: Superquadrics have proven to provide a compact, geometrically meaningful representation for 3D objects. However, existing methods suffer from limited re

The MMM Data Model -- A Normative Specification for Knowledge Interoperability in a Decentralisable Knowledge Commons

arXiv:2607.00032v1 Announce Type: new Abstract: Many information systems are built around documents: self-contained units optimised for print production and linear reading. While effective for large-s

Adapting Foundation ASR Models to Dysarthric Speech: A Case Study

arXiv:2606.31722v1 Announce Type: new Abstract: Automatic speech recognition (ASR) systems often perform poorly in dysarthric speech, limiting their usefulness to affected speakers in everyday communi

applicationsarxiv-cs-cl

Deep Spectral Models for Robust Dental Shape Generation

arXiv:2606.31293v1 Announce Type: new Abstract: Accurate modeling of dental crown morphology is fundamental for diagnosis, orthodontic planning, and computer-aided restoration design. However, dataset

Few-Shot Synthetic Image Attribution: Identifying Unseen Generators with Limited Samples

arXiv:2509.25682v2 Announce Type: replace Abstract: AI-generated image (AIGI) attribution presents a pressing challenge that goes beyond mere AIGI detection, aiming to identify the source model or tec

From Materials Database to Materials Bank: Assetizing Data for AI Driven Materials Innovation

arXiv:2606.31366v1 Announce Type: cross Abstract: Driven by high-throughput experimentation, computational modeling, and artificial intelligence (AI), materials data has expanded at an unprecedented r

On Optimal Data Splitting for Split Conformal Prediction

arXiv:2606.31600v1 Announce Type: cross Abstract: Conformal prediction and its variants, including the split conformal prediction, provide a distribution-free framework for uncertainty quantification

Registering the 4D Millimeter Wave Radar Point Clouds Via Generalized Method of Moments

arXiv:2508.02187v3 Announce Type: replace-cross Abstract: 4D millimeter wave radars (4D radars) are new emerging sensors that provide point clouds of objects with both position and radial velocity mea

Connectivity Estimation using Stochastic Graph Heat Modelling

arXiv:2606.29098v1 Announce Type: cross Abstract: A growing number of techniques leverage the spatial structures that underlie many real-world datasets. Despite these advances, the complementary task