Search: “applications”

Distribution-Free Stochastic Analysis and Robust Multilevel Vector Field Anomaly Detection

arXiv:2207.06229v3 Announce Type: replace-cross Abstract: Massive vector field datasets are common in multi-spectral optical and radar sensors, among many other emerging areas of application. We devel

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Tutorials

Efficient Traffic Forecasting on Large-Scale Road Network by Regularized Adaptive Graph Convolution

DGX agent

arXiv:2506.07179v2 Announce Type: replace-cross Abstract: Traffic prediction is a critical task in spatial-temporal forecasting with broad applications in travel planning and urban management. To mode

tutorialsarxiv-cs-ai

30 Apr 2026

Featurising Pixels from Dynamic 3D Scenes with Linear In-Context Learners

arXiv:2604.26488v1 Announce Type: new Abstract: One of the most exciting applications of vision models involve pixel-level reasoning. Despite the abundance of vision foundation models, we still lack r

Tools

Grok 4.3 on AI Gateway

Grok 4.3 is now available through Vercel's AI Gateway, enabling developers to integrate xAI's latest language model into their applications via Vercel's unified AI platform. This integration allows us

toolsvercel-blog

Grounding vs. Compositionality: On the Non-Complementarity of Reasoning in Neuro-Symbolic Systems

arXiv:2604.26521v1 Announce Type: new Abstract: Compositional generalization remains a foundational weakness of modern neural networks, limiting their robustness and applicability in domains requiring

researcharxiv-cs-ai

HER: Human-like Reasoning and Reinforcement Learning for LLM Role-playing

arXiv:2601.21459v4 Announce Type: replace-cross Abstract: LLM role-playing, i.e., using LLMs to simulate specific personas, has emerged as a key capability in various applications, such as companionsh

How Vultr Enables Agentic AI Experiences with AMD

Vultr partnered with AMD to provide infrastructure and computing capabilities that support autonomous AI agents and agentic AI applications. The content likely discusses how Vultr's cloud platform, en

hardwarevultr

International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2026

researchapple-ml-research

ICASSP 2026 is a major international conference focused on acoustics, speech, and signal processing research and applications. Apple's machine learning research team is participating in the conference

MARVIS: Modality Adaptive Reasoning over VISualizations

model-releasesarxiv-cs-lg

arXiv:2507.01544v2 Announce Type: replace Abstract: Predictive applications of machine learning often rely on small (sub 1 Bn parameter) specialized models tuned to particular domains or modalities. S

Local Ai

Point Cloud Registration via Probabilistic Self-Update Local Correspondence and Line Vector Sets

arXiv:2604.26318v1 Announce Type: new Abstract: Point cloud registration (PCR) is a fundamental task for integrating 3D observations in remote sensing applications. This paper proposes a fast and effe

local-aiarxiv-cs-cv

Seamless Indoor-Outdoor Mapping for INGENIOUS First Responders

arXiv:2604.26368v1 Announce Type: new Abstract: In several applications it is desired to have 3D models not only from the outdoor spaces but also from inside the building. In the context of First Resp

Speed Up Unreal Engine NNE Inference with NVIDIA TensorRT for RTX Runtime

The TensorRT for RTX plugin provides a runtime for Unreal Engine's Neural Network Engine (NNE), enabling efficient deployment of AI models directly within real-time applications. Developers can see 1.

hardwarenvidia-developer

Value-Guided Iterative Refinement and the DIQ-H Benchmark for Evaluating VLM Robustness

arXiv:2512.03992v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) are essential for embodied AI and safety-critical applications, such as robotics and autonomous systems. However

Video Compression Meets Video Generation: Latent Inter-Frame Pruning with Attention Recovery

arXiv:2603.05811v2 Announce Type: replace Abstract: Current video generation models suffer from high computational latency, making real-time applications prohibitively costly. In this paper, we addres

hardwarearxiv-cs-cv

A Survey on LLM-based Conversational User Simulation

arXiv:2604.24977v1 Announce Type: new Abstract: User simulation has long played a vital role in computer science due to its potential to support a wide range of applications. Language, as the primary

researcharxiv-cs-cl

AI is moving so fast, what should we even build? We're excited about the opportunity for AI to accelerate abundance, help us better understa…

Yohei Nakajima discusses the rapid pace of AI development and the challenge of determining what applications are worth building in this accelerating landscape. The post likely explores the opportuniti

agentsyohei-nakajima--x

Analyzing LLM Reasoning to Uncover Mental Health Stigma

model-releasesarxiv-cs-cl

arXiv:2604.25053v1 Announce Type: new Abstract: While large language models (LLMs) are increasingly being explored for mental health applications, recent studies reveal that they can exhibit stigma to

Command Zero opens its autonomous security operations center platform with APIs and an MCP server

model-releasessiliconangle

Cyber investigations platform provider Command Zero Inc. today released a set of application programming interface endpoints and a Model Context Protocol server for its autonomous security operations

EvoTSC: Evolving Feature Learning Models for Time Series Classification via Genetic Programming

model-releasesarxiv-cs-lg

arXiv:2604.25499v1 Announce Type: new Abstract: Time series classification is an important analytical task across diverse domains. However, its practical application is often hindered by the scarcity

Four ways Google Research scientists have been using Empirical Research Assistance

Google Research scientists have demonstrated applications of Empirical Research Assistance across diverse scientific domains, with the system generating novel, testable hypotheses across scientific an

researchgoogle-research

From Syntax to Emotion: A Mechanistic Analysis of Emotion Inference in LLMs

arXiv:2604.25866v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in emotionally sensitive human-AI applications, yet little is known about how emotion recognition is

researcharxiv-cs-cl

Knowledge-Data Dually Driven Paradigm for Accurate Landslide Susceptibility Prediction under Data-Scarce Conditions Using Geomorphic Priors and Tabular Foundation Model

arXiv:2604.25196v1 Announce Type: new Abstract: Landslide susceptibility prediction is critical for geohazard risk assessment and mitigation. Conventional data-driven paradigm achieves high predictive

Learning-Based Automated Adversarial Red-Teaming for Robustness Evaluation of Large Language Models

arXiv:2512.20677v4 Announce Type: replace-cross Abstract: The increasing deployment of large language models (LLMs) in safety-critical applications raises fundamental challenges in systematically eval

safetyarxiv-cs-cl

Learning from Medical Entity Trees: An Entity-Centric Medical Data Engineering Framework for MLLMs

arXiv:2604.25296v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have shown transformative potential in medical applications, yet their performance is hindered by conventional

safetyarxiv-cs-cl

MCP now available in Thoth

Thoth, a local-first desktop AI assistant, now supports Model Context Protocol (MCP) tools, allowing users to run it fully locally with Ollama or integrate frontier APIs as needed. The application pri

agentsr-ollama

MTPano: Multi-Task Panoramic Scene Understanding via Label-Free Integration of Dense Prediction Priors

arXiv:2602.05330v2 Announce Type: replace Abstract: Comprehensive panoramic scene understanding is critical for immersive applications, yet it remains challenging due to the scarcity of high-resolutio

Safe-Support Q-Learning: Learning without Unsafe Exploration

arXiv:2604.25379v1 Announce Type: new Abstract: Ensuring safety during reinforcement learning (RL) training is critical in real-world applications where unsafe exploration can lead to devastating outc

safetyarxiv-cs-lg

Spectral bandits

arXiv:2604.25272v1 Announce Type: cross Abstract: Smooth functions on graphs have wide applications in manifold and semi-supervised learning. In this work, we study a bandit problem where the payoffs

safetyarxiv-cs-lg

Towards interpretable AI with quantum annealing feature selection

arXiv:2604.25649v1 Announce Type: new Abstract: Deep learning models are used in critical applications, in which mistakes can have serious consequences. Therefore, it is crucial to understand how and

50+ fully managed MCP servers now available for Google Cloud services

model-releasesgoogle-cloud-ai

At Google Cloud Next ‘26, we announced that more than 50 Google-managed Model Context Protocol (MCP) servers are generally available or in preview, with more on the way. Why it matters: To move beyond

6thGrid-Net: Unified Remote Sensing Image Dehazing Based on Color Restoration and Edge-Preserving

model-releasesarxiv-cs-cv

arXiv:2604.24149v1 Announce Type: new Abstract: Remote sensing images are frequently degraded by adverse weather conditions, particularly clouds and haze, which severely impair downstream applications

A Multi-Dimensional Audit of Politically Aligned Large Language Models

arXiv:2604.24429v1 Announce Type: new Abstract: As the application of Large Language Models (LLMs) spreads across various industries, there are increasing concerns about the potential for their misuse

safetyarxiv-cs-cl

A Survey on Split Learning for LLM Fine-Tuning: Models, Systems, and Privacy Optimizations

arXiv:2604.24468v1 Announce Type: cross Abstract: Fine-tuning unlocks large language models (LLMs) for specialized applications, but its high computational cost often puts it out of reach for resource

researcharxiv-cs-cl

A Systematic Approach for Large Language Models Debugging

arXiv:2604.23027v1 Announce Type: new Abstract: Large language models (LLMs) have become central to modern AI workflows, powering applications from open-ended text generation to complex agent-based re

agentsarxiv-cs-ai

Appian adopts MCP protocol and partners with Snowflake to provide more structure and control for AI agents

Business process automation software company Appian Inc. is stepping up its game in agentic artificial intelligence, announcing major updates to its platform focused on AI-assisted application develop

agentssiliconangle

Avionic Main Fuel Pump Simulation and Fault-Diagnosis Benchmark

arXiv:2604.22869v1 Announce Type: cross Abstract: In many cyber-physical systems, especially in critical applications such as aeroplanes, data to train anomaly detection and diagnosis algorithms is la

B-FIRE: Binning-Free Diffusion Implicit Neural Representation for Hyper-Accelerated Motion-Resolved MRI

arXiv:2601.06166v2 Announce Type: replace Abstract: Accelerated dynamic volumetric magnetic resonance imaging (4DMRI) is essential for applications relying on motion resolution. Existing 4DMRI produce

Builders

model-releasesben-s-bites

Builders likely refers to a discussion of AI tools, platforms, or frameworks that enable developers and creators to build applications or solutions using AI technologies. The article probably covers e

Certified geometric robustness -- Super-DeepG

arXiv:2604.24379v1 Announce Type: new Abstract: Safety-critical applications are required to perform as expected in normal operations. Image processing functions are often required to be insensitive t

safetyarxiv-cs-ai

Conditional Imputation for Within-Modality Missingness in Multi-Modal Federated Learning

arXiv:2604.23112v1 Announce Type: new Abstract: Multimodal Federated Learning (MMFL) enables privacy-preserving collaborative training, but real-world clinical applications often suffer from within-mo

safetyarxiv-cs-lg

Cooperative Informative Sensing for Monitoring Dynamic Indoor Environments via Multi-Agent Reinforcement Learning

arXiv:2604.23179v1 Announce Type: cross Abstract: Monitoring human activity in indoor environments is important for applications such as facility management, safety assessment, and space utilization a

safetyarxiv-cs-ai

CRISP: Persistent Concept Unlearning via Sparse Autoencoders

model-releasesarxiv-cs-cl

arXiv:2508.13650v3 Announce Type: replace Abstract: As large language models (LLMs) are increasingly deployed in real-world applications, the need to selectively remove unwanted knowledge while preser

Crystal structure prediction using graph neural combinatorial optimization

arXiv:2604.23921v1 Announce Type: cross Abstract: Crystalline materials are widely used in technological applications, yet their discovery remains a significant challenge. As their properties are driv

hardwarearxiv-cs-ai

DepthKV: Layer-Dependent KV Cache Pruning for Long-Context LLM Inference

arXiv:2604.24647v1 Announce Type: cross Abstract: Long-context reasoning is a critical capability of large language models (LLMs), enabling applications such as long-document understanding, summarizat

researcharxiv-cs-ai

Does Machine Unlearning Preserve Clinical Safety? A Risk Analysis for Medical Image Classification

arXiv:2604.23854v1 Announce Type: new Abstract: The application of Deep Learning in medical diagnosis must balance patient safety with compliance with data protection regulations. Machine Unlearning e

safetyarxiv-cs-ai

EmoBench-M: Benchmarking Emotional Intelligence for Multimodal Large Language Models

arXiv:2502.04424v4 Announce Type: replace-cross Abstract: With the integration of multimodal large language models (MLLMs) into robotic systems and AI applications, embedding emotional intelligence (E

Exploring the Secondary Risks of Large Language Models

arXiv:2506.12382v5 Announce Type: replace-cross Abstract: Ensuring the safety and alignment of Large Language Models is a significant challenge with their growing integration into critical application

Fed-DLoRA: Efficient Wireless Federated Learning with Dynamic Low-Rank Adaptation

arXiv:2604.24103v1 Announce Type: new Abstract: Federated learning (FL) offers a promising distributed learning paradigm for internet of vehicles (IoV) applications. However, it faces challenges from