Search: “applications”

FlowGuard: Flow Matching for Identity-Independent Detection of Data-Free Model Stealing Attacks on Energy System Intrusion Detection Systems

arXiv:2606.03430v1 Announce Type: cross Abstract: Artificial Intelligence (AI)-based Intrusion Detection Systems (IDS) deployed in energy infrastructure are vulnerable to model theft attacks, which al

researcharxiv-cs-ai

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Agents

FORGE: Multi-Agent Graduated Exploitation and Detection Engineering

DGX agent

arXiv:2606.03453v1 Announce Type: cross Abstract: Vulnerability disclosure volumes now far exceed organizational assessment capacity, yet three adjacent research communities (proof-of-concept generati

agentsarxiv-cs-ai

3 Jun 2026

From Prompt to Service: An SLM-Based Agent Orchestration Gateway for AI-Driven Virtual Worlds

arXiv:2606.03557v1 Announce Type: new Abstract: As generative AI capabilities expand, AI-driven virtual worlds face a growing architectural challenge. Users interact through in-world interfaces in mul

GN0: Toward a Unified Paradigm for Generation, Evaluation, and Policy Learning in Visual-Language Navigation

model-releasesarxiv-cs-ro

arXiv:2606.03682v1 Announce Type: new Abstract: Embodied navigation connects intelligent agents with the physical world and is fundamental for general robotic intelligence. Limited availability and qu

Tutorials

GS-ROR^2: Bidirectional-guided 3DGS and SDF for Reflective Object Relighting and Reconstruction

arXiv:2406.18544v4 Announce Type: replace Abstract: 3D Gaussian Splatting (3DGS) has shown a powerful capability for novel view synthesis due to its detailed expressive ability and highly efficient re

tutorialsarxiv-cs-cv

Honesty in Causal Forests: When It Helps and When It Hurts

arXiv:2506.13107v4 Announce Type: replace Abstract: Causal forests estimate how treatment effects vary across individuals, guiding personalized interventions in areas like marketing, operations, and p

How Kodiak trains the brain behind 28 driverless trucks

Twenty-eight trucks, and no humans in the cab. As of March 31, 2026, Kodiak's autonomous driving system, the Kodiak Driver, runs commercial freight on public roads across long-haul trucking, and indus

safetylambda-labs

How Much of a Model Do We Need? Redundancy and Slimmability in Remote Sensing Foundation Models

arXiv:2601.22841v2 Announce Type: replace Abstract: Large-scale foundation models (FMs) in remote sensing (RS) (denoted as RS FMs) are developed following paradigms established in computer vision (CV)

researcharxiv-cs-cv

How Wasmer used Codex to build a Node.js runtime for the edge

Wasmer leveraged OpenAI's Codex to develop a Node.js runtime optimized for edge computing environments. The project demonstrates how AI-assisted code generation can accelerate the creation of speciali

model-releasesopenai

'Important You should give me full credits!': Exploring Prompt Injection Attacks on LLM-Based Automatic Grading Systems

arXiv:2606.03090v1 Announce Type: cross Abstract: The emergence of large language models (LLMs) has significantly accelerated recent research on LLM-based automatic grading (AG) systems. Benefiting fr

Agents

Inducing Reasoning Primitives from Agent Traces

arXiv:2606.02994v1 Announce Type: new Abstract: ReAct-style LLM agents often rediscover the same reasoning routines across problems, yet leave those routines trapped in transient scratchpads. We intro

agentsarxiv-cs-ai

Instant Personalized Large Language Model Adaptation via Hypernetwork

model-releasesarxiv-cs-cl

arXiv:2510.16282v2 Announce Type: replace Abstract: Personalized large language models (LLMs) tailor content to individual preferences using user profiles or histories. However, existing parameter-eff

Inverting the Generation Process of Denoising Diffusion Implicit Models: Empirical Evaluation and a Novel Method

arXiv:2606.03111v1 Announce Type: new Abstract: This paper studies the problem of inverting the DDIM image generation process to recover latent variables, particularly the initial noise map, from a ge

researcharxiv-cs-cv

It seems there is an entirely different set of rules for Republicans and Democrats.

Yann LeCun's post suggests a perceived double standard in how political rules or standards are applied differently to Republicans versus Democrats. The statement implies inconsistent enforcement or tr

researchyann-lecun--x

Large Byte Model: Teaching Language Models About Compiled Code

arXiv:2606.02834v1 Announce Type: cross Abstract: Malware analysis starts with the raw bytes of an executable program, and tools to 'lift' these to higher-level representations, such as assembly, are

researcharxiv-cs-ai

Localized, High-resolution Geographic Representations with Slepian Functions

arXiv:2602.00392v2 Announce Type: replace Abstract: Geographic data is fundamentally local. Disease outbreaks cluster in population centers, ecological patterns emerge along coastlines, and economic a

safetyarxiv-cs-lg

Low-Frequency Shortcuts in Texture-Driven Visual Learning

model-releasesarxiv-cs-cv

arXiv:2606.03493v1 Announce Type: new Abstract: Neural networks suffer from shortcut learning, where learned features generalize well to the training set but not to in-distribution (ID) or out-of-dist

MedCUA-Bench: A Screenshot-Only Benchmark for Clinical Computer-Use Agents

arXiv:2606.03203v1 Announce Type: new Abstract: Computer-use agents could automate repetitive screen-based clinical work, but their reliability in medical graphical user interfaces remains largely unv

MLSkip: Data Skipping for ML Filters via Lightweight Metadata

arXiv:2606.03946v1 Announce Type: cross Abstract: Database vendors recently released AI functions that can be used in filter predicates. As such functions often rely on costly, black-box ML models, th

Hardware

NVIDIA Isaac Sim: Enabling Scalable, GPU-Accelerated Simulation for Robotics

arXiv:2606.03551v1 Announce Type: new Abstract: Simulation has become a core infrastructure for robotics research. Unlike previous simulators, NVIDIA Isaac Sim leverages GPU acceleration to enable lar

hardwarearxiv-cs-ro

OMP: One-step Meanflow Policy with Directional Alignment

arXiv:2512.19347v3 Announce Type: replace Abstract: Robot manipulation has increasingly adopted data-driven generative policy frameworks, yet the field faces a persistent trade-off: diffusion models s

safetyarxiv-cs-ro

On The Computational Complexity of Minimum Aerial Photographs for Planar Region Coverage

arXiv:2512.18268v3 Announce Type: replace Abstract: With the popularity of drone technologies, aerial photography has become prevalent in many daily scenarios such as environment monitoring, structure

researcharxiv-cs-ro

One Transit Is All You Need: Detecting Exoplanets Through Learned Stellar Behaviour with EXOVEIL

arXiv:2606.02778v1 Announce Type: cross Abstract: I present EXOVEIL, a transit detection system that learns what a star's brightness should look like and flags when reality disagrees. Unlike existing

Tutorials

Oscillatory State-Space Models as Inductive Biases for Physics-Informed Neural PDE Solvers

arXiv:2606.02623v1 Announce Type: cross Abstract: Solving time-dependent partial differential equations (PDEs) is an important problem in computational science and engineering. Physics-informed neural

tutorialsarxiv-cs-ai

PatchScene: Patch-based Voxel Diffusion for Large-Scale Scene Completion

model-releasesarxiv-cs-cv

arXiv:2606.03915v1 Announce Type: new Abstract: We propose PatchScene, a novel diffusion-based framework for large-scale LiDAR scene completion. Unlike existing methods that rely on global latent repr

PHAF-Personalized Hand Avatars in a Flash

arXiv:2606.03420v1 Announce Type: new Abstract: We present PHAF-Personalized Hand Avatars in a Flash, a personalized photo-realistic hand avatar which provides high quality multi-view renders from jus

safetyarxiv-cs-cv

Pixel Cube: Diffusion-based Portrait Video Relighting Through Realistic Lighting Reproduction

arXiv:2606.02919v1 Announce Type: new Abstract: We present a diffusion-based method for relighting dynamic portrait videos with photorealism and temporal consistency. Our method is fueled by a hybrid

researcharxiv-cs-cv

PSViT: A Methodology for Structurally Pruning Spiking Vision Transformers

arXiv:2606.03257v1 Announce Type: cross Abstract: Spiking Vision Transformer (SViT) models are promising low-power ViT models for solving vision-based tasks with state-of-the-art performance. However,

researcharxiv-cs-ai

Qift: Shift-Friendly No-Zero W2 Post-Training Quantization for Rotated W2A4/KV4 LLM Inference

arXiv:2606.02823v1 Announce Type: new Abstract: Two-bit weight quantization is attractive for memory-efficient LLM inference, but the standard W2 level set {-2,-1,0,+1} often collapses under aggressiv

Agents

Seg2Track++: Probabilistic Track Validation and Data Association for Multi-Object Tracking and Segmentation

arXiv:2606.03875v1 Announce Type: new Abstract: Autonomous systems require robust Multi-Object Tracking and Segmentation (MOTS) to operate reliably in dynamic environments, ensuring consistent object

agentsarxiv-cs-cv

SeSE: Black-Box Uncertainty Quantification for Large Language Models Based on Structural Information Theory

arXiv:2511.16275v4 Announce Type: replace-cross Abstract: Reliable uncertainty quantification (UQ) is essential for deploying large language models (LLMs) in safety-critical scenarios, as it enables t

Set-Preserving Calibration from Conformal P-Values to E-Values

arXiv:2606.03600v1 Announce Type: cross Abstract: Standard conformal prediction (CP) procedures are typically formulated in terms of p-values, but reliance on p-values alone limits flexibility, for ex

Skill-RM: Unifying Heterogeneous Evaluation Criteria via Agent Skill

model-releasesarxiv-cs-cl

arXiv:2606.03980v1 Announce Type: cross Abstract: Reward models (RMs) provide critical feedback signals for LLM post-training, notably in reinforced fine-tuning (RFT) and reinforcement learning (RL) p

Speech Emotion Recognition using Attention-based LSTM-Network with Residual Connection

arXiv:2606.03359v1 Announce Type: cross Abstract: Speech emotion recognition is an important component of modern human-computer interaction systems. However, many state-of-the-art approaches rely on l

researcharxiv-cs-cl

Testing Most Influential Sets

arXiv:2510.20372v4 Announce Type: replace-cross Abstract: Small influential data subsets can dramatically impact model conclusions, with a few data points overturning key findings. While recent work i

The Efficiency vs. Accuracy Trade-off: Optimizing RAG-Enhanced LLM Recommender Systems Using Multi-Head Early Exit

arXiv:2501.02173v2 Announce Type: replace-cross Abstract: The deployment of Large Language Models (LLMs) in recommender systems for predicting Click-Through Rates (CTR) necessitates a delicate balance

Topology-Aware Gaussian Graph Repair for Robust Graph Neural Networks

arXiv:2606.03462v1 Announce Type: new Abstract: Graph neural networks have achieved strong performance on graph-structured data, but their effectiveness depends heavily on the quality of the observed

Training a Predictive Coding Network on ImageNet using Equilibrium Propagation

arXiv:2606.03584v1 Announce Type: new Abstract: Equilibrium Propagation (EP) is a physics-based training framework that has primarily been employed in energy-based models, including continuous Hopfiel

Local Ai

TripoSplat: TripoSplat converts a single 2D image into high-quality and variable number of 3D Gaussians, developed by TripoAI (open weights, link to github repo)

local-air-stablediffusion

TripoSplat is an open-source tool developed by TripoAI that converts single 2D images into 3D Gaussian representations with variable density and high quality. The method enables efficient 3D reconstru

Using Reward Uncertainty to Induce Diverse Behaviour in Reinforcement Learning

arXiv:2606.03962v1 Announce Type: cross Abstract: Classical reinforcement learning (RL) typically seeks a deterministic policy that maximizes the expected sum of a scalar reward. Yet, modern applicati

VidMsg: A Benchmark for Implicit Message Inference in Short Videos

arXiv:2606.03635v1 Announce Type: cross Abstract: Understanding short online videos involves more than identifying visible objects and actions; video makers often include an underlying message or purp

Hardware

What’s new in serverless Managed Service for Apache Spark

Whether you use it for data preparation, real-time interactive queries, AI model training, or something entirely different, running Apache Spark at scale is demanding — you shouldn’t have to manage th

hardwaregoogle-cloud-ai

Local Ai

What's the most unhinged thing you've used an uncensored Ollama model for? Also... what are the best uncensored models right now?

This Reddit discussion from r/ollama explores user experiences with uncensored Ollama language models, featuring anecdotal accounts of unusual or extreme use cases and recommendations for popular unce

local-air-ollama

WISE: A World Knowledge-Informed Semantic Evaluation for Text-to-Image Generation

arXiv:2503.07265v4 Announce Type: replace-cross Abstract: Text-to-Image (T2I) models are capable of generating high-quality artistic creations and visual content. However, existing research and evalua

Tutorials

Your Autoregressive Model Already Reveals the Causal Graph

arXiv:2602.01135v3 Announce Type: replace Abstract: Autoregressive models trained via next-token prediction implicitly learn the conditional independence structure of their data-generating process. We

tutorialsarxiv-cs-lg

A Lightweight Hybrid MLP-Based Framework for Real-Time Phishing URL Detection Using Structural URL Features

arXiv:2606.00889v1 Announce Type: cross Abstract: Phishing attacks remain a major cybersecurity threat, exploiting deceptive URLs to steal sensitive user information. Traditional blacklist and rule-ba

2 Jun 2026

A Monosemantic Attribution Framework for Stable Interpretability in Clinical Neuroscience Transformer-Based Language Models

arXiv:2601.17952v2 Announce Type: replace-cross Abstract: Interpretability remains a key challenge for deploying language models (LM) in clinical settings such as progression diagnosis of Alzheimer di

2 Jun 2026

A Per-Component Diagnostic Protocol for Neural HJB-PIDE Solvers under Control-Dependent Levy Jumps

arXiv:2606.01122v1 Announce Type: new Abstract: We propose a five-step diagnostic protocol for residual-trained neural HJB-PIDE solvers with control-dependent Levy jumps, targeting a general failure m