Search: “applications”

arXiv:2604.17013v1 Announce Type: new Abstract: With the development of robotics, skeleton-based action recognition has become increasingly important, as human-robot interaction requires understanding

safetyarxiv-cs-cv

TrianguLang: Geometry-Aware Semantic Consensus for Pose-Free 3D Localization

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DGX agent

arXiv:2603.08096v3 Announce Type: replace Abstract: Localizing objects and parts from natural language in 3D space is essential for robotics, AR, and embodied AI, yet existing methods face a trade-off

local-aiarxiv-cs-cv

21 Apr 2026

Unveiling Deepfakes: A Frequency-Aware Triple Branch Network for Deepfake Detection

arXiv:2604.17477v1 Announce Type: new Abstract: Advanced deepfake technologies are blurring the lines between real and fake, presenting both revolutionary opportunities and alarming threats. While it

Upper Approximation Bounds for Neural Oscillators

arXiv:2512.01015v2 Announce Type: replace Abstract: Neural oscillators, originating from second-order ordinary differential equations (ODEs), have demonstrated strong performance in stably learning ca

VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planning

arXiv:2402.13243v2 Announce Type: replace Abstract: Learning a human-like driving policy from large-scale driving demonstrations is promising, but the uncertainty and non-deterministic nature of plann

VLM-3R: Vision-Language Models Augmented with Instruction-Aligned 3D Reconstruction

model-releasesarxiv-cs-cl

arXiv:2505.20279v4 Announce Type: replace-cross Abstract: The rapid advancement of Large Multimodal Models (LMMs) for 2D images and videos has motivated extending these models to understand 3D scenes,

Wasserstein-p Central Limit Theorem Rates: From Local Dependence to Markov Chains

arXiv:2601.08184v3 Announce Type: replace-cross Abstract: Non-asymptotic central limit theorem (CLT) rates play a central role in modern machine learning and operations research. In this paper, we stu

Safety

When Choices Become Risks: Safety Failures of Large Language Models under Multiple-Choice Constraints

arXiv:2604.16916v1 Announce Type: new Abstract: Safety alignment in large language models (LLMs) is primarily evaluated under open-ended generation, where models can mitigate risk by refusing to respo

safetyarxiv-cs-cl

A methodology to rank importance of frequencies and channels in electromyography data with Decision Tree classifiers

arXiv:2604.15353v1 Announce Type: cross Abstract: This study presents a methodology for identifying the most informative frequencies and channels in electromyography (EMG) data to evaluate muscle reco

tutorialsarxiv-cs-lg

A PennyLane-Centric Dataset to Enhance LLM-based Quantum Code Generation using RAG

arXiv:2503.02497v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) offer powerful capabilities in code generation, natural language understanding, and domain-specific reasoning. Th

A Structure-Preserving Graph Neural Solver for Parametric Hyperbolic Conservation Laws

arXiv:2604.15617v1 Announce Type: cross Abstract: Hyperbolic conservation laws govern a wide range of transport-driven dynamics featuring shocks, contact discontinuities, and complex wave interactions

Safety

Adaptive multi-fidelity optimization with fast learning rates

arXiv:2604.16239v1 Announce Type: cross Abstract: In multi-fidelity optimization, biased approximations of varying costs of the target function are available. This paper studies the problem of optimiz

safetyarxiv-cs-lg

AdaVFM: Adaptive Vision Foundation Models for Edge Intelligence via LLM-Guided Execution

arXiv:2604.15622v1 Announce Type: new Abstract: Language-aligned vision foundation models (VFMs) enable versatile visual understanding for always-on contextual AI, but their deployment on edge devices

local-aiarxiv-cs-cv

Agents

AgentV-RL: Scaling Reward Modeling with Agentic Verifier

arXiv:2604.16004v1 Announce Type: cross Abstract: Verifiers have been demonstrated to enhance LLM reasoning via test-time scaling (TTS). Yet, they face significant challenges in complex domains. Error

agentsarxiv-cs-ai

AISysRev -- LLM-based Tool for Title-abstract Screening

arXiv:2510.06708v3 Announce Type: replace-cross Abstract: Conducting systematic reviews is laborious. In the screening or study selection phase, the number of papers can be overwhelming. Recent resear

Art3D: Training-Free 3D Generation from Flat-Colored Illustration

arXiv:2504.10466v2 Announce Type: replace Abstract: Large-scale pre-trained image-to-3D generative models have exhibited remarkable capabilities in diverse shape generations. However, most of them str

BAGEL: Benchmarking Animal Knowledge Expertise in Language Models

arXiv:2604.16241v1 Announce Type: cross Abstract: Large language models have shown strong performance on broad-domain knowledge and reasoning benchmarks, but it remains unclear how well language model

ChemGraph-XANES: An Agentic Framework for XANES Simulation and Analysis

arXiv:2604.16205v1 Announce Type: cross Abstract: Computational X-ray absorption near-edge structure (XANES) is widely used to probe local coordination environments, oxidation states, and electronic s

Creating and Evaluating Personas Using Generative AI: A Scoping Review of 81 Articles

arXiv:2504.04927v2 Announce Type: replace-cross Abstract: As generative AI (GenAI) is increasingly applied in persona development to represent real users, understanding the implications and limitation

researcharxiv-cs-cl

cuNNQS-SCI: A Fully GPU-Accelerated Framework for High-Performance Configuration Interaction Selection withNeural Network QQantum States

arXiv:2604.15768v1 Announce Type: cross Abstract: AI-driven methods have demonstrated considerable success in tackling the central challenge of accurately solving the Schrodinger equation for complex

Industry

Dataset 2: Drift, named after Drift Diffusion Modeling. https://huggingface.co/datasets/DJLougen/drift-preview-5k This is a bit of different…

Dataset 2 (Drift) is a 5,000-sample preview dataset hosted on Hugging Face, named after drift diffusion modeling concepts. The dataset appears to represent a novel or experimental approach to data col

industryclem-delangue--x

DB-FGA-Net: Dual Backbone Frequency Gated Attention Network for Multi-Class Brain Tumor Classification with Grad-CAM Interpretability

arXiv:2510.20299v3 Announce Type: replace-cross Abstract: Brain tumors are a challenging problem in neuro-oncology, where early and precise diagnosis is important for successful treatment. Deep learni

DeepKeep rolls out Vibe AI Red Teaming to test AI apps and agents

Artificial intelligence security platform company DeepKeep Ltd. today announced the launch of Vibe AI Red Teaming, a capability designed for human-steered, dynamic testing and attack simulation on AI

tutorialssiliconangle

DepCap: Adaptive Block-Wise Parallel Decoding for Efficient Diffusion LM Inference

arXiv:2604.15750v1 Announce Type: cross Abstract: Diffusion language models (DLMs) have emerged as a promising alternative to autoregressive language generation due to their potential for parallel dec

DINOv3 Beats Specialized Detectors: A Simple Foundation Model Baseline for Image Forensics

arXiv:2604.16083v1 Announce Type: new Abstract: With the rapid advancement of deep generative models, realistic fake images have become increasingly accessible, yet existing localization methods rely

local-aiarxiv-cs-cv

Tools

Download the Cursor CLI: http://cursor.com/cli

Cursor offers a command-line interface (CLI) tool that can be downloaded from their website, enabling developers to use Cursor's AI-powered code editing capabilities from the terminal. The CLI allows

toolscursor--x

EchoVLM: Dynamic Mixture-of-Experts Vision-Language Model for Universal Ultrasound Intelligence

arXiv:2509.14977v2 Announce Type: replace Abstract: Ultrasound imaging has become the preferred imaging modality for early cancer screening due to its advantages of non-ionizing radiation, low cost, a

researcharxiv-cs-cv

Estimating Joint Interventional Distributions from Marginal Interventional Data

arXiv:2409.01794v2 Announce Type: replace-cross Abstract: In this paper we show how to exploit interventional data to acquire the joint conditional distribution of all the variables using the Maximum

tutorialsarxiv-cs-lg

Evaluating quality in synthetic data generation for large tabular health datasets

arXiv:2604.15961v1 Announce Type: new Abstract: There is no consensus in the field of synthetic data on concise metrics for quality evaluations or benchmarks on large health datasets, such as historic

From Benchmarking to Reasoning: A Dual-Aspect, Large-Scale Evaluation of LLMs on Vietnamese Legal Text

arXiv:2604.16270v1 Announce Type: cross Abstract: The complexity of Vietnam's legal texts presents a significant barrier to public access to justice. While Large Language Models offer a promising solu

Fusing Cellular Network Data and Tollbooth Counts for Urban Traffic Flow Estimation

arXiv:2604.15782v1 Announce Type: new Abstract: Traffic simulations, essential for planning urban transit infrastructure interventions, require vehicle-category-specific origin-destination (OD) data.

tutorialsarxiv-cs-lg

GaussianFlow SLAM: Monocular Gaussian Splatting SLAM Guided by GaussianFlow

arXiv:2604.15612v1 Announce Type: cross Abstract: Gaussian splatting has recently gained traction as a compelling map representation for SLAM systems, enabling dense and photo-realistic scene modeling

tutorialsarxiv-cs-cv

Graph self-supervised learning based on frequency corruption

arXiv:2604.15699v1 Announce Type: new Abstract: Graph self-supervised learning can reduce the need for labeled graph data and has been widely used in recommendation, social networks, and other web app

local-aiarxiv-cs-lg

Industry

🚀 GROK APP JUST HIT AN ALL-TIME HIGH! 📈 Total sessions hit their highest point ever nearing 300 million last month on the AppStore 🔥

The Grok app reached an all-time high in user sessions, approaching 300 million total sessions in the most recent month according to App Store data. This milestone represents significant growth in ado

industryelon-musk--x

Hierarchical Active Inference using Successor Representations

arXiv:2604.15679v1 Announce Type: cross Abstract: Active inference, a neurally-inspired model for inferring actions based on the free energy principle (FEP), has been proposed as a unifying framework

tutorialsarxiv-cs-ai

HiPreNets: High-Precision Neural Networks through Progressive Training

model-releasesarxiv-cs-lg

arXiv:2506.15064v3 Announce Type: replace Abstract: Deep neural networks are powerful tools for solving nonlinear problems in science and engineering, but training highly accurate models becomes chall

HyCal: A Training-Free Prototype Calibration Method for Cross-Discipline Few-Shot Class-Incremental Learning

arXiv:2604.15678v1 Announce Type: new Abstract: Pretrained Vision-Language Models (VLMs) like CLIP show promise in continual learning, but existing Few-Shot Class-Incremental Learning (FSCIL) methods

HyperGVL: Benchmarking and Improving Large Vision-Language Models in Hypergraph Understanding and Reasoning

model-releasesarxiv-cs-cl

arXiv:2604.15648v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) consistently require new arenas to guide their expanding boundaries, yet their capabilities with hypergraphs remain

IA-CLAHE: Image-Adaptive Clip Limit Estimation for CLAHE

arXiv:2604.16010v1 Announce Type: new Abstract: This paper proposes image-adaptive contrast limited adaptive histogram equalization (IA-CLAHE). Conventional CLAHE is widely used to boost the performan

Agents

Integrating Graphs, Large Language Models, and Agents: Reasoning and Retrieval

arXiv:2604.15951v1 Announce Type: new Abstract: Generative AI, particularly Large Language Models, increasingly integrates graph-based representations to enhance reasoning, retrieval, and structured d

agentsarxiv-cs-ai

Tools

Kimi K2.6 on AI Gateway

Vercel's AI Gateway now supports Kimi K2.6, a language model that developers can access through Vercel's unified AI platform. This integration allows users to leverage Kimi K2.6's capabilities alongsi

toolsvercel-blog

KRONE: Scalable LLM-Augmented Log Anomaly Detection via Hierarchical Abstraction

arXiv:2602.07303v3 Announce Type: replace-cross Abstract: Log anomaly detection is crucial for uncovering system failures and security risks. Although logs originate from nested component executions w

Agents

LangSmith Insights Agent helps Credit Genie interpret feedback from customers at scale, and continuously improve their product. https://www.…

LangSmith Insights Agent helps Credit Genie interpret feedback from customers at scale, and continuously improve their product. https://www.langchain.com/blog/credit-genie-insights-agent-financial-ass

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Hardware

Mitigating Indirect AGENTS.md Injection Attacks in Agentic Environments

NVIDIA researchers discovered a vulnerability in AI coding assistants where malicious software dependencies can inject harmful instructions into AGENTS.md configuration files, allowing attackers to re

hardwarenvidia-developer

Model page https://ollama.com/library/kimi-k2.6 More integrations https://docs.ollama.com/integrations

Ollama has made the Kimi K2.6 model available in its library, allowing users to run this model locally through the Ollama platform. The announcement highlights expanded integration options documented

local-aiollama--x

Neuromorphic Parameter Estimation for Power Converter Health Monitoring Using Spiking Neural Networks

model-releasesarxiv-cs-lg

arXiv:2604.15714v1 Announce Type: cross Abstract: Always-on converter health monitoring demands sub-mW edge inference, a regime inaccessible to GPU-based physics-informed neural networks. This work se

Opportunities and Challenges of Large Language Models for Low-Resource Languages in Humanities Research

arXiv:2412.04497v5 Announce Type: replace-cross Abstract: Low-resource languages serve as invaluable repositories of human history, embodying cultural evolution and intellectual diversity. Despite the

researcharxiv-cs-ai

Optimizing Korean-Centric LLMs via Token Pruning

model-releasesarxiv-cs-cl

arXiv:2604.16235v1 Announce Type: new Abstract: This paper presents a systematic benchmark of state-of-the-art multilingual large language models (LLMs) adapted via token pruning - a compression techn