Search: “deployment”

EO-VGGT: Orbital Ray-Conditioned 3D Foundation Models for Satellite Multi-View Reconstruction

arXiv:2607.00417v1 Announce Type: cross Abstract: In the era of satellite constellations, multi-view optical satellite imagery is pivotal for Earth Observation (EO) and high-quality Digital Surface Mo

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Research

Flow-Through Tensors: A Unified Computational Graph Architecture for Multi-Layer Transportation Network Optimization

DGX agent

arXiv:2507.02961v2 Announce Type: replace-cross Abstract: Modern transportation network modeling increasingly involves the integration of diverse methodologies including sensor-based forecasting, rein

researcharxiv-cs-ai

2 Jul 2026

Forensic-Oriented Intrusion Detection Using Synthetic Network Traffic Data and Explainable Artificial Intelligence

arXiv:2607.00763v1 Announce Type: cross Abstract: Digital forensic investigations of network intrusions require analytical outputs that are traceable, reproducible, and court-defensible - requirements

Human-Machine Collaboration on Generative Meta-Learning: Model and Algorithm

arXiv:2607.00926v1 Announce Type: cross Abstract: Generalizing machine learning models to environments that differ from their training distribution remains a critical hurdle, particularly when data fr

agentsarxiv-cs-ai

Local Ai

Interact3D: Compositional 3D Generation of Interactive Objects

arXiv:2603.16085v2 Announce Type: replace-cross Abstract: Recent breakthroughs in 3D generation have enabled the synthesis of high-fidelity individual assets. However, generating 3D compositional obje

local-aiarxiv-cs-ai

KungfuBot: Physics-Based Humanoid Whole-Body Control for Learning Highly-Dynamic Skills

arXiv:2506.12851v3 Announce Type: replace-cross Abstract: Humanoid robots are promising to acquire various skills by imitating human behaviors. However, existing algorithms are only capable of trackin

Leveraging Multimodality for Real-Time Classification of Transients and Variables found by the Zwicky Transient Facility

arXiv:2607.00228v1 Announce Type: cross Abstract: Modern time-domain surveys such as the Zwicky Transient Facility (ZTF) generate hundreds of thousands of alerts each night, making real-time decisions

LeVLJEPA: End-to-End Vision-Language Pretraining Without Negatives

arXiv:2607.00784v1 Announce Type: cross Abstract: Vision-language pretraining remains dominated by contrastive objectives, whereas vision-only self-supervised learning has largely adopted non-contrast

Local Ai

MalariAI: A Label-Resilient Decoupled Framework for Universal Cell Segmentation and Explainable Stage Classification in Dense Malaria Blood Smears

arXiv:2607.00385v1 Announce Type: cross Abstract: Automated malaria diagnosis from blood smear microscopy is a critical challenge in global health AI; in resource-limited settings, the scarcity of exp

local-aiarxiv-cs-ai

Mixture of Distributions Matters: Dynamic Sparse Attention for Efficient Video Diffusion Transformers

arXiv:2601.11641v3 Announce Type: replace Abstract: While Diffusion Transformers (DiTs) have achieved notable progress in video generation, this long-sequence generation task remains constrained by th

Multi-Hypothesis Test-Time Adaptation to Mitigate Underspecification

arXiv:2607.00259v1 Announce Type: cross Abstract: Test-Time Adaptation (TTA) seeks to improve model robustness under distribution shifts by adapting parameters using unlabeled target data. However, in

PAPA: Online Personalized Active Preference Alignment

arXiv:2607.00486v1 Announce Type: cross Abstract: Diffusion models are highly effective at modeling complex data distributions, including images and text. However, in applications like personalized re

Real-Time Hard Negative Sampling via LLM-based Clustering for Large-Scale Two-Tower Retrieval

arXiv:2607.00448v1 Announce Type: cross Abstract: The two-tower model has been widely used for large-scale recommendation systems, particularly in the retrieval stage. Industry standards for training

RetailSMV: Exocentric vs. Egocentric Adaptation of Foundation Video World Models in Retail

arXiv:2607.00310v1 Announce Type: cross Abstract: Foundation video diffusion models are increasingly viewed as world simulators for embodied agents, yet their pretraining on internet-scale generic vid

Rethinking Visual Privacy: A Compositional Privacy Risk Framework for Severity Assessment with VLMs

arXiv:2603.21573v2 Announce Type: replace Abstract: Existing visual privacy benchmarks largely treat privacy as a binary property, labeling images as private or non-private based on visible sensitive

RoboWorld: Fast and Reliable Neural Simulators for Generalist Robot Policy Evaluation

arXiv:2607.01060v1 Announce Type: new Abstract: Video world models are emerging as a scalable alternative for evaluating generalist robot policies, bypassing the physical constraints and engineering b

safetyarxiv-cs-ro

SemiScope: Disentangling Classifier Tuning and Joint Optimization in Semi-Supervised Security Classification

arXiv:2607.00113v1 Announce Type: new Abstract: Background. Labeled data for security classification is scarce. Semi-supervised learning (SSL) propagates labels from a small labeled pool to larger unl

Towards Developing a Multimodal Chat Assistant for University Stakeholders: RAG-based Approach

arXiv:2607.01115v1 Announce Type: cross Abstract: University stakeholders often face difficulties in accessing timely and reliable information, especially in developing countries, where there are very

Towards Robust Driving Perception: A Flexible Scale-Driven Family for Self-Supervised Monocular Depth Estimation

arXiv:2607.00736v1 Announce Type: new Abstract: Self-Supervised Monocular Depth Estimation (MDE) has garnered attention in recent years due to its independence from ground truth. However, most existin

A Lifecycle and Application-Stack Survey of Large Language Model Vulnerabilities: Attacks, Risks, Defenses, and Open Problems

arXiv:2606.31639v1 Announce Type: cross Abstract: Large language models are no longer only text generators. They are increasingly embedded in retrieval pipelines, enterprise assistants, coding environ

A Scalable Whole-body Motion Transfer via Implicit Kinodynamic Motion Retargeting

arXiv:2509.15443v2 Announce Type: replace-cross Abstract: Human-to-humanoid imitation learning presents a promising pathway to address the severe data scarcity bottleneck in robotics by utilizing abun

A Single Rewrite Suffices: Empirical Lessons from Production Skill Description Optimization

arXiv:2606.30775v1 Announce Type: cross Abstract: Enterprise AI agents route user queries to specialized skills by matching queries against natural language skill descriptions. When two skills share o

agentsarxiv-cs-ai

A Tutorial on Autonomous Fault-Tolerant Control Using Knowledge-Grounded LLM Agents

arXiv:2606.31635v1 Announce Type: cross Abstract: Fault recovery in process plants still relies heavily on plant operators, especially when faults fall outside predefined supervisory logic. Operators

Adapting Generalist Robot Policies with Semantic Reinforcement Learning

arXiv:2606.31958v1 Announce Type: new Abstract: Generalist robot policies learn a diverse repertoire of behaviors from large-scale pretraining. In principle, this makes them excellent priors for downs

safetyarxiv-cs-ro

Auditing Generalization in AI-Generated Video Detection: A Six-Control Protocol and the VidAudit Toolkit

arXiv:2606.31004v1 Announce Type: new Abstract: AI-generated video detection benchmarks such as GenVidBench and AIGVDBench are the de facto leaderboards, yet most evaluation protocols leave uncontroll

Bridging Information Asymmetry: A Hierarchical Framework for Deterministic Blind Face Restoration

arXiv:2601.19506v4 Announce Type: replace Abstract: Blind face restoration remains a persistent challenge due to the inherent ill-posedness of reconstructing holistic structures from severely constrai

safetyarxiv-cs-cv

Calibrating the Evaluator: Does Probability Calibration Mitigate Preference Coupling in LLM Agent Feedback Loops?

arXiv:2606.31371v1 Announce Type: cross Abstract: When large language model (LLM) agents adapt their behavior through evaluator feedback, systematic evaluator biases propagate into the agent's learned

Certified Speculative Execution for Untrusted AI Agents

arXiv:2606.31023v1 Announce Type: cross Abstract: Hard-constrained sequential decision systems have no certified way to spend the test-time compute of modern AI: executing the multi-step drafts of a l

safetyarxiv-cs-lg

CLOUDADV: Decision-Aligned Instance Sizing with Zero-Shot Foundation Models under Drift

arXiv:2606.31470v1 Announce Type: new Abstract: Cloud virtual machines are often overprovisioned, creating avoidable cost and operational inefficiency. We present CLOUDADV, an interactive engineer-fac

Cross-lingual Relation Extraction with Large Language Models: Zero-Shot, Few-Shot, and Fine-Tuned Evaluation on Romanian

arXiv:2606.31718v1 Announce Type: cross Abstract: Relation extraction (RE) for low-resource languages is typically constrained by the lack of annotated corpora. We investigate the feasibility of cross

DriveWeaver: Point-Conditioned Video Inpainting for Controllable Vehicle Insertion in Autonomous Driving Simulation

arXiv:2606.31918v1 Announce Type: new Abstract: A pivotal step in autonomous driving simulation involves inserting foreground vehicles with predefined trajectories into simulated scenes. This process

agentsarxiv-cs-cv

E-VLA: Event-Augmented Vision-Language-Action Model for Dark and Blurred Scenes

model-releasesarxiv-cs-cv

arXiv:2604.04834v2 Announce Type: replace Abstract: Robotic Vision-Language-Action (VLA) models generalize well for open-ended manipulation, but their perception is fragile under sensing-stage degrada

ERA: Entropy-Guided Visual Token Pruning with Rectified Attention for Efficient MLLMs

arXiv:2606.31982v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) incur prohibitive inference costs due to long visual token sequences. Training-free visual token reduction prov

safetyarxiv-cs-cv

From Search to Synthesis: Training LLMs as Zero-Shot Workflow Generators

arXiv:2606.30704v1 Announce Type: cross Abstract: Large language models (LLMs) excel across a wide range of tasks, yet their instance-specific solutions often lack the structural consistency needed fo

Keep Policy Gradient in Charge: Sibling-Guided Credit Distillation for Long-Horizon Tool-Use Agents

arXiv:2606.12634v2 Announce Type: replace-cross Abstract: Long-horizon tool-use reinforcement learning learns from outcome verification, but trajectory-level advantages are broadcast over reasoning, A

LabGuard: Grounding Natural-Language Laboratory Rules into Runtime Guards for Embodied Laboratory Agents

arXiv:2606.31045v1 Announce Type: new Abstract: Scientific embodied agents are increasingly capable of carrying out laboratory procedures, but executing these procedures safely in dynamic laboratory e

LiteMatch: Lightweight Zero-Shot Stereo Matching via Cost Volume Stabilization

arXiv:2606.31636v1 Announce Type: new Abstract: Despite rapid progress in learning-based stereo matching, high accuracy is often achieved at the cost of heavy backbones and computationally intensive 3

Moral Safety in LLMs: Exposing Performative Compliance with Puzzled Cues

model-releasesarxiv-cs-cl

arXiv:2606.31644v1 Announce Type: new Abstract: As large language models take on morally consequential roles in healthcare, legal, and hiring contexts, we need to examine whether their ethical behavio

Multimodal Benchmark for Safety Assessment in Industrial Inspection Scenarios

model-releasesarxiv-cs-cv

arXiv:2601.21173v2 Announce Type: replace-cross Abstract: With the rapid development of industrial intelligence and unmanned inspection, reliable perception and safety assessment for AI systems in com

Optimization Algorithms for Joint OFDM Waveform Design and RIS Configuration in 6G Networks: From Convex Relaxation to Foundation Models

arXiv:2606.31334v1 Announce Type: new Abstract: Joint OFDM-RIS optimization for 6G is a mixed-integer nonlinear programming (MINLP) problem covering sum-rate maximization, energy efficiency, max-min f

PGUDA: Pressure-Guided Unsupervised Domain Adaptation with Cross-Modal Knowledge Distillation for sEMG-Based Gesture Recognition

arXiv:2606.31349v1 Announce Type: cross Abstract: Surface electromyography (sEMG)-based gesture recognition has emerged as a promising technology for natural human-computer interaction. However, its p

PiLoT v2: Pixel-to-Orthogonal Map Alignment for Free-view UAV Geo-localization

arXiv:2606.31098v1 Announce Type: new Abstract: Real-time, drift-free UAV geo-localization is essential for autonomous missions in GNSS-denied environments. The pioneering system, PiLoT, achieves high

safetyarxiv-cs-cv

Prompting Robot Teams with Natural Language

arXiv:2509.24575v2 Announce Type: replace-cross Abstract: This paper presents a framework to prompt multi-robot teams with high-level tasks using natural language expressions. Our objective is to use

safetyarxiv-cs-lg

Quality-Controlled Active Learning via Gaussian Processes for Robust Structure-Property Learning in Autonomous Microscopy

arXiv:2603.29135v2 Announce Type: replace Abstract: Autonomous experimental systems are increasingly used in materials research to accelerate scientific discovery, but their performance is often limit

agentsarxiv-cs-lg

Quantum Bayesian Networks Can Speed up Reinforcement Learning in Partially Observable Environments

arXiv:2507.18606v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) provides a principled framework for decision-making in partially observable environments, which can be modeled as

Applications

RAISE: LLM-based Automated Heuristic Design with Robust Adversary Instance Search

arXiv:2606.31801v1 Announce Type: new Abstract: Automated Heuristic Design (AHD) with Large Language Models (LLMs) has shown remarkable progress in discovering high-quality heuristics. However, existi

applicationsarxiv-cs-ai

REMSA: Foundation Model Selection for Remote Sensing via a Constraint-Aware Agent

arXiv:2511.17442v3 Announce Type: replace-cross Abstract: Foundation Models (FMs) are increasingly integrated into remote sensing (RS) pipelines. These models include unimodal vision encoders and mult

Revisiting Parameter Redundancy in Vision-Language-Action Models: Insights from VLM-to-VLA Adaptation

model-releasesarxiv-cs-ro

arXiv:2606.31382v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have made significant strides in embodied intelligence by integrating the powerful representations of pre-trained Vi