Search: “applications”

VG-TIE: An interpretable tabular-to-image encoding method based on visibility graphs

arXiv:2609.29650v1 Announce Type: new Abstract: Tabular-to-image encoding methods enable the application of models based on both convolutional neural networks and vision transformers to tabular data,

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25 Sept 2026

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When Fancy Eviction Fails: Rethinking Cache Replacement For LLM Prefix Reuse

DGX agent

arXiv:2609.28870v1 Announce Type: cross Abstract: Long-running LLM applications repeatedly send growing context, making prefix caching critical for reducing prefill cost. Yet prefix-cache behavior und

agentsarxiv-cs-lg

25 Sept 2026

Accenture leverages Oracle’s Deep Data Security for database-driven trust boundaries

Oracle Corp.’s Deep Data Security offers a basic premise on enterprise security: When the application layer is an AI agent, the trust boundary must move somewhere else. The trust boundary can be reloc

agentssiliconangle

AI agents creating a new insider security risk: theCUBE’s Oktane keynote analysis

AI agent security now depends on knowing what agents can do after they gain access. Agents can act across applications, pass work to other agents and make changes faster than security teams can review

agentssiliconangle

DEAL-Grasp: Decoupled Alignment Representation for Geometry-Aware Dexterous Grasp Generation

arXiv:2609.28131v1 Announce Type: new Abstract: Synthesizing realistic articulated hand-object interactions is a fundamental problem in virtual reality, embodied intelligence, and digital human applic

local-aiarxiv-cs-ro

Exact Feedback Is Not Control: Evaluating Text-based Closed-Loop Revision in LLMs

arXiv:2609.28150v1 Announce Type: new Abstract: Closed-loop revision is increasingly used in large language model (LLM) applications, but failures may reflect incomplete feedback or ineffective respon

researcharxiv-cs-cl

FDE-Bench: Evaluating LLM Agents for Deployment Environment Configuration

model-releasesarxiv-cs-ai

arXiv:2609.27571v1 Announce Type: cross Abstract: Deployment requires an agent to turn application code into a running system whose services connect, become ready, and remain observable. FDE-Bench eva

Google launches two benchmark-topping speech generation models

model-releasessiliconangle

Google LLC today made two new text-to-speech models, Gemini 3.8 Flash TTS and Gemini 3.8 Flash-Lite TTS, available through its cloud platform. The algorithms have highly similar application programmin

Learning Holographic Reduced Representations with Clifford Variational Autoencoders

model-releasesarxiv-cs-ai

arXiv:2609.28409v1 Announce Type: cross Abstract: Vector Symbolic Algebras project data structures into a hyperdimensional vector space through the application of their vector algebras to randomly gen

Need some suggestion

Guys I have a M4-mac air with 24 GB unified memory and I wanna run some local LLM model on my machine Currently I am working on building and RAG application which is mostly and QnA system but I wanna

local-air-ollama

ODPure: Backdoor Purification for Object Detection via Ensemble Corruption Consensus

arXiv:2609.28239v1 Announce Type: new Abstract: With the development of applications like autonomous driving, object detection has gained significant attention, while also highlighting critical vulner

agentsarxiv-cs-cv

PRISM-VLM: A Multi-Axis Discriminative Benchmark for Compact Vision-Language Models

model-releasesarxiv-cs-cl

arXiv:2609.27395v1 Announce Type: new Abstract: Compact vision-language models (VLMs) now power a growing share of multimodal applications. The benchmarks used to compare them, however, inherit a fron

Relative Discharge Stage (RDS) Classification: A Practical Indicator of Battery Discharge Progress

arXiv:2609.27986v1 Announce Type: new Abstract: Accurate remaining discharge time (RDT) prediction is challenging in real-world battery applications because future load profiles are unknown and highly

Statistical Properties of Deep Neural Networks with Dependent Data

arXiv:2410.11113v4 Announce Type: replace-cross Abstract: This paper develops theory for deep neural network (DNN) estimators under dependent data. To provide theory applicable to a variety of DNN-bas

The three things today's hottest startups are looking for in their AI stack

model-releasesgoogle-cloud-ai

Google Cloud has become the platform of choice for startups building AI. Our uniquely complete stack — including a choice of first- and third-party compute and models; our platform for building and ma

CacheDyG: Decoupling Temporal Propagation for Efficient Dynamic Graph Learning

arXiv:2609.25814v1 Announce Type: new Abstract: Dynamic graphs are widely used to model time-evolving relational systems in real-world applications. Dynamic graph neural networks provide an effective

Deep Reinforcement Learning on Item-Compatibility Graphs for One-Dimensional Bin Packing

arXiv:2609.25397v1 Announce Type: new Abstract: The one-dimensional bin packing problem (1D-BPP) is a classical NP-hard combinatorial optimization problem with applications ranging from logistics and

Dynamic Deep Prompt Optimization for Defending Against Jailbreak Attacks on LLMs

arXiv:2609.26185v1 Announce Type: cross Abstract: Large Language Models (LLMs) demonstrate impressive capabilities across many applications but remain vulnerable to jailbreak attacks, which elicit har

safetyarxiv-cs-cl

EDGEGEN: Improving Tool-Calling Agents Beyond Happy Paths with Synthetic Edge Case Generation

model-releasesarxiv-cs-ai

arXiv:2609.24115v1 Announce Type: new Abstract: Tool-calling LLM agents are increasingly deployed in enterprise applications. However, effective evaluation and optimization require high-quality, diver

Federating Quantum and Classical Computing: A Privacy-Preserving Hybrid Approach

arXiv:2609.25082v1 Announce Type: new Abstract: Quantum machine learning (QML) is increasingly recognized as one of the most promising near-term applications of quantum computing, viewed as a next-fro

Hierarchical Sparse Bayesian Multitask Learning for Disease Prediction in Pooled Microbiome Studies

arXiv:2502.02552v2 Announce Type: replace Abstract: This paper proposes a hierarchical Bayesian multitask learning model that is applicable to the general multi-task binary classification learning pro

HYDRA: Proactive Android Malware Drift Adaptation via Hierarchical Graph Contrastive Learning

arXiv:2609.26352v1 Announce Type: cross Abstract: Concept drift, driven by the rapid evolution of Android malware, severely degrades the performance of machine learning detectors. Current adaptation s

NaCR: Visual Localization via NeRF-aided Camera Ray Regression

arXiv:2609.25907v1 Announce Type: new Abstract: Visual localization (VL) is a fundamental technology for vision applications such as virtual reality. Recently, a novel VL paradigm, Camera Ray Regressi

local-aiarxiv-cs-cv

Optimal Sequential Annotations for Off-Policy Evaluation

arXiv:2609.26707v1 Announce Type: cross Abstract: Offline reinforcement learning and off-policy evaluation evaluates dynamic treatment rules based on retrospectively collected data prior to deployment

Oracle shifts agent controls toward data-layer security

Data-layer security is becoming more important as automated systems gain broader access to sensitive information and business processes. Controls designed for predictable applications may not be enoug

agentssiliconangle

Pinocchio: Fast Uncertainty Estimates for Black-Box Language Models

arXiv:2609.24881v2 Announce Type: new Abstract: In high-stakes decision-making applications of large language models (LLMs), practitioners require not only accurate LLMs but also uncertainty estimates

researcharxiv-cs-ai

Shaft-Configuration-Adaptive Catheter Tip Position Estimation via Motor-History Conditioned Residual Learning

arXiv:2609.26304v1 Announce Type: new Abstract: Tendon-driven continuum manipulators are widely used in medical applications, where accurate tip-position estimation is essential for precise navigation

researcharxiv-cs-ro

SuperPCA: subspace analysis and an efficient algorithm for high-dimensional PCA

arXiv:2609.26406v1 Announce Type: cross Abstract: Principal component analysis (PCA) is a fundamental tool to reduce the dimensionality of the data in many applications. PCA finds a few signal directi

Towards Systematic Qualification of Vision-Language Models for Automotive Perception Systems

arXiv:2609.25945v1 Announce Type: new Abstract: The field of Artificial Intelligence has been adopted for many application domains. Vision Language Models are one of the recently advanced AI technique

safetyarxiv-cs-cv

Visual Jev: Accurate and Efficient Decisions from Shared Visual Context

arXiv:2609.25845v1 Announce Type: cross Abstract: Many vision applications ask several independent, forced-choice questions about the same image. Visual Jev encodes the image and public context once,

Bayesian Filtering in Physical Systems via Test-time Trained Flow Matching

arXiv:2609.23383v1 Announce Type: cross Abstract: Bayesian filtering provides a principled framework for online state estimation under uncertainty, yet its application to systems with high-dimensional

Blind Deconvolution of Binary and Pattern Images with Pixel Intensity Constraints and Sparse Gradient Prior

arXiv:2609.23268v1 Announce Type: new Abstract: Blind image deconvolution (BID) is a prominent research topic in the field of imaging sciences, given its significant practical applications. Most exist

researcharxiv-cs-cv

CHART: A Harness-Rotation Curriculum for Harness-Robust Search Agents

arXiv:2609.22247v1 Announce Type: new Abstract: Search agents are usually trained under a single harness. But once an agent is deployed in a real application, its harness is frequently updated (e.g.,

local-aiarxiv-cs-lg

Computationally efficient safe exploration in reinforcement learning

arXiv:2609.22919v1 Announce Type: new Abstract: Reinforcement learning in real-life applications requires safety guarantees during exploration. Typical reinforcement learning algorithms do not provide

Defusing Explosive Prompts: Understanding and Preventing Trigger-Based Prompt Injections in LLM Agents

arXiv:2609.22510v1 Announce Type: cross Abstract: As LLM applications integrate with external tools, they are increasingly exposed to indirect prompt injection (IPI), where adversarial instructions ar

DiFA: Dual Evidence Fusion and Aggregation for Token-Level Text Anomaly Detection

arXiv:2609.22136v1 Announce Type: new Abstract: Text anomaly detection, the task of identifying text instances that deviate from normal language patterns, is crucial for language-driven applications.

researcharxiv-cs-cl

Dynamic Thermal Gaussians: Multimodal 4D Gaussian Splatting

model-releasesarxiv-cs-cv

arXiv:2609.24531v1 Announce Type: new Abstract: Thermography plays a vital role in military and broader thermal analysis applications. Recent progress in 3D thermal reconstruction has extended tempera

Label Propagation for Physics-Informed Neural Networks and Physics-Informed Gaussian Processes

arXiv:2404.05817v2 Announce Type: replace Abstract: We present a series of empirical results of the application of semi-supervised label propagation techniques in training physics-informed machine lea

LLM-based Conversational AI Knowledge Assistant for MyBuddy Humanoid Robot

arXiv:2609.24742v1 Announce Type: new Abstract: Humanoid robots are increasingly being popular and developed for human-centered applications, yet their ability to provide intelligent conversations and

researcharxiv-cs-ro

NaRPA: Navigation and Rendering Pipeline for Astronautics

arXiv:2211.01566v2 Announce Type: replace-cross Abstract: This paper presents the applications of scientific ray-tracing in modeling and simulating light transport for space-borne image data generatio

researcharxiv-cs-cv

NVIDIA Isaac ROS 5.0 Advances Agentic, Open Source Robotics Development

model-releasesnvidia-blog

To build and deploy sophisticated robotics applications that can perceive, reason and act in dynamic environments, developers need new physical AI models and tools. The ROS open framework is a project

PADiff: Predictive and Adaptive Diffusion Policies for Ad Hoc Teamwork

arXiv:2511.07260v3 Announce Type: replace-cross Abstract: Ad hoc teamwork (AHT) requires agents to collaborate with previously unseen teammates, which is crucial for many real-world applications. The

Prediction of Nonlinear Oscillations in a Jumping Quarter-Car Model Using Reservoir Computing

arXiv:2609.22205v1 Announce Type: new Abstract: Reliable prediction of vehicle dynamics is essential for smart driving applications such as autonomous control and advanced driver-assistance systems. O

agentsarxiv-cs-lg

SmallSatSim: A GPU-Accelerated Microgravity Robotics Toolkit for Planning, Control, and Policy Learning

arXiv:2603.14598v2 Announce Type: replace Abstract: Microgravity rendezvous and close proximity operations (RPO) is a growing area of interest for applications spanning in-space assembly and manufactu

safetyarxiv-cs-ro

Speech-to-SOAP: End-to-End Summarization of Medical Dialogues: KIT@BeTraC 2026

arXiv:2608.24327v2 Announce Type: replace Abstract: With the advent of Large Language Models and its instruction following capabilities a promising application is the task of summarization. Within thi

researcharxiv-cs-cl

Stochastic Flow Map for Count Data

arXiv:2609.23290v1 Announce Type: cross Abstract: High-dimensional count data are common in scientific applications, but most diffusion and flow models are designed for continuous or categorical data,

local-aiarxiv-cs-lg

Toward Mission-Critical ISAC: Reliable Energy-Aware Coordination in UAV Swarms

arXiv:2609.22292v1 Announce Type: cross Abstract: Unmanned aerial vehicle (UAV) swarms deployed in mission-critical applications must simultaneously track a mobile aerial target and maintain reliable

agentsarxiv-cs-ro

User-Level Handover Decision Making Based on Machine Learning Approaches

arXiv:2609.22593v1 Announce Type: new Abstract: This letter covers a broad comparison of methods for classification and regression applications for a user-level handover decision making in scenarios w