applications

Differential Amplifier-Inspired AmpAttention for Multi-View Robotic Manipulation

arXiv:2607.02845v1 Announce Type: cross Abstract: Multi-view robotic manipulation methods with the attention mechanism have recently achieved significant progress in both training efficiency and task

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DIVO: Continuous-time DVL-Inertial-Visual Odometry for Unmanned Underwater Vehicles

DGX agent

arXiv:2607.04615v1 Announce Type: new Abstract: This paper presents a novel acoustic-visual-inertial odometry solution leveraging a continuous-time trajectory estimation framework for unmanned underwa

applicationsarxiv-cs-ro

7 Jul 2026

DS-SAC: Density Search for Sample Consensus

arXiv:2607.03972v1 Announce Type: new Abstract: Robust geometric model estimation is a fundamental problem in computer vision. RANSAC and its variants remain widely used for this task; however, they r

Efficient Cross-Validation for Sparse Linear Regression

arXiv:2306.14851v5 Announce Type: replace-cross Abstract: Given a high-dimensional covariate matrix and a response vector, ridge-regularized sparse linear regression selects a subset of features that

Exploring SAM Supervision for Fine-Grained UAV Target Segmentation under Data Scarcity

arXiv:2607.03754v1 Announce Type: new Abstract: Unmanned aerial vehicle (UAV) target segmentation remains challenging due to the small size of objects, appearance variations, cluttered backgrounds, an

Fine-Grained Computation Offload for Off-the-Shelf Servers in Tens of Lines

arXiv:2607.02630v1 Announce Type: cross Abstract: Hardware accelerators now sit on the critical path of online serving. GPUs, FPGAs, and increasingly remote services such as hardware security modules,

Fixed-Confidence Best-Arm Identification for Causal Mediation Analysis

arXiv:2607.04315v1 Announce Type: cross Abstract: This paper studies the problem of identifying the treatment that maximizes the expected natural direct potential outcome (NDPO), which captures the po

FlatManifold: Robust Continual Learning under Severe Label Noise and Domain Shifts via Intrinsic Manifold Flattening

arXiv:2607.05201v1 Announce Type: new Abstract: In non-stationary streaming environments, simultaneously adapting to complex, non-linear domain shifts via continual learning while mitigating the catas

FlowMark: Mask-Guided Video Watermarking

arXiv:2607.05261v1 Announce Type: new Abstract: We present FlowMark, a video watermarking framework guided by automatically predicted object masks. In contrast to prior region-based approaches that re

From Geometric Labels to Semantic Understanding of Indoor Building Components Using Multimodal Large Language Models

arXiv:2607.03661v1 Announce Type: new Abstract: Point cloud-based understanding has become an important enabler for facility operation and maintenance involving indoor building components. However, ex

FSDC-DETR: A Frequency-Spatial Domain Collaborative DETR for Small Object Detection

arXiv:2607.05176v1 Announce Type: new Abstract: Small object detection (SOD) remains a challenging task in real-world applications. Despite recent advances, existing detectors remain limited by rigid

GDPR-Aware Trajectory Sharing for ISAC-Assisted Robot Navigation: A Case Study on FID-Constrained Collision Prediction

arXiv:2607.03254v1 Announce Type: new Abstract: Integrated sensing and communication (ISAC) enables intelligent wireless infrastructure but raises growing regulatory concern as fine-grained personal t

Geometric Causal Models

arXiv:2607.05153v1 Announce Type: cross Abstract: Scientists often seek to draw causal inferences from structured data that is not independently and identically distributed, such as spatial data, netw

Geometry-Aware Motion Latents for Learning Robust Manipulation Policies

arXiv:2607.04714v1 Announce Type: cross Abstract: Learning motion latents for robotic manipulation heavily relies on extracting motion patterns from visual sequences, yet effective action abstractions

GeoWorld: Providing Full-frame Geometry Features to Facilitate 3D Scene Generation

arXiv:2511.23191v2 Announce Type: replace Abstract: Previous works that leverage video models for image-to-3D scene generation often suffer from geometric distortions and blurry content. Using video g

GlaBoost: A Multimodal Structured Framework for Glaucoma Risk Stratification

arXiv:2508.03750v2 Announce Type: replace-cross Abstract: Early and accurate glaucoma detection is critical to prevent irreversible vision loss, yet existing AI methods often rely on unimodal inputs a

HiSAC: Hierarchical Sparse Activation Compression for Ultra-long Sequence Modeling in Recommenders

arXiv:2602.21009v2 Announce Type: replace-cross Abstract: Modern recommender systems leverage ultra-long user behavior sequences to capture dynamic preferences, but end-to-end modeling is infeasible i

applicationsarxiv-cs-cl

How AWS Finance teams reclaimed hundreds of hours with Amazon Quick

AWS Finance used Amazon Quick chat agents and Flows to automate two major time-consuming workflows: financial target setting and weekly business reviews. The automation reduced target-setting time fro

applicationsaws-ml-blog

HUGS: Guiding Unified Dexterous Grasp Synthesis Across Modes and Scales via Learned Human Priors

arXiv:2607.04554v1 Announce Type: new Abstract: Dexterous grasping across diverse object scales requires contact modes ranging from two-finger pinches to bimanual grasps. Existing dexterous grasp synt

Hybrid Deep Learning for Traceability and Classification of Industrial Slate Tiles

arXiv:2607.04811v1 Announce Type: new Abstract: Applying deep learning to instance-aware reidentification of slate tiles and extraction site classification can improve production efficiency and qualit

I have been playing these world models/games since the first diffusion DOOM, and multiplayer at 20 FPS is pretty neat. 'A dream of rocket le…

applicationsethan-mollick--x

I have been playing these world models/games since the first diffusion DOOM, and multiplayer at 20 FPS is pretty neat. 'A dream of rocket league,' indeed. Introducing MIRA. A playable, multiplayer wor

IBIS: A Hybrid Inception-BiLSTM and SVM Ensemble for Robust Doppler-based Human Activity Recognition

arXiv:2510.24936v3 Announce Type: replace Abstract: Wi-Fi sensing is a leading technology for Human Activity Recognition (HAR), offering a non-intrusive and cost-effective solution for healthcare and

IBM debuts compact z17 mainframes and LinuxONE servers for on-premises enterprise AI

IBM Corp. today announced a massive expansion of its on-premises enterprise infrastructure lineup, with new single-frame and rack-mount versions of its iconic z17 mainframes and more compact LinuxONE

applicationssiliconangle

Identifiability of Relational Queries in Multi-View Pretraining

arXiv:2607.04735v1 Announce Type: cross Abstract: When data sources are integrated through a shared interface, a downstream query may or may not be determined by what the interface exposes: two global

!Imperio, smolVLA: The Implications of Data Poisoning on Open Source Robotics

arXiv:2607.04146v1 Announce Type: cross Abstract: This work establishes that trigger-word data poisoning of vision language action models is practical, while at the same time the open-source robotics

ImputeECG: Deep Learning Reconstruction of Complete 12-Lead Electrocardiograms from Incomplete Recordings for Cardiac Assessment

arXiv:2607.05009v1 Announce Type: cross Abstract: Complete digital 12-lead electrocardiograms (ECGs) are essential for AI-enabled cardiovascular assessment, yet many clinical ECG records, particularly

Invisible Strings: Deriving Puppetry Principles and their Hidden Connections to Robot Behavior Design

arXiv:2607.03289v1 Announce Type: new Abstract: When designing robots' nonverbal behaviors, many researchers have turned to arts-based insights, such as Disney's Animation Principles. Yet, while these

Joint distribution of upstream runoff governs downstream river-discharge prediction uncertainty in distributed ML models

arXiv:2607.03217v1 Announce Type: new Abstract: Uncertainty quantification of hydrological predictions is necessary to inform operational decisions. Recent generative machine-learning methods have adv

karl. -- A Research Vehicle for Automated and Connected Driving

arXiv:2602.08842v3 Announce Type: replace-cross Abstract: As highly automated driving is transitioning from single-vehicle closed-access testing to commercial deployments of public ride-hailing in sel

Knowledge-Centric Information Systems

arXiv:2607.02609v1 Announce Type: cross Abstract: For decades, data engineering has developed mature architectural principles for integrating, governing, validating, cataloging, and serving organizati

Knowledge-Informed Local Causal Discovery of Optimal Adjustment Sets

arXiv:2607.04447v1 Announce Type: new Abstract: Local causal discovery is a scalable alternative to global structure learning. However, it can struggle to identify valid adjustment sets in data-scarce

Labeled-Data-Free Meta-Learning: Efficient Task Generation Using Pre-trained Models and Unlabeled Data

arXiv:2607.02850v1 Announce Type: new Abstract: Meta-learning without labeled data is crucial for real-world applications, where obtaining labeled datasets can be expensive or restricted due to privac

Last Layer Hamiltonian Monte Carlo

arXiv:2507.08905v2 Announce Type: replace-cross Abstract: We explore the use of Hamiltonian Monte Carlo (HMC) sampling as a probabilistic last layer approach for deep neural networks (DNNs). While HMC

Layout-independent actuation allocator for fin-actuated marine robots

arXiv:2607.03204v1 Announce Type: new Abstract: In this study, we propose a layout-independent control allocator capable of zero-shot deployment across diverse actuator configurations. The proposed me

Learning Flexible Generalization in Video Quality Assessment by Bringing Device and Viewing Condition Distributions

arXiv:2607.04643v1 Announce Type: new Abstract: Video quality assessment (VQA) plays a critical role in optimizing video delivery systems. While numerous objective metrics have been proposed to approx

Learning to Discover Iterative Spectral Algorithms

arXiv:2602.09530v2 Announce Type: replace-cross Abstract: We introduce AutoSpec, a neural network framework for discovering iterative spectral algorithms for large-scale numerical linear algebra and n

LLM-Enhanced Hierarchical Heterogeneous Graph Representation Learning for Malicious Python Package Detection

arXiv:2607.03350v1 Announce Type: cross Abstract: Malicious Python packages have become a major threat to software supply chain ecosystems due to the widespread adoption of open-source repositories su

LOTUSim: Multi-Domain Simulator for Marine Robotics

arXiv:2607.03072v1 Announce Type: cross Abstract: Simulation is essential for maritime robotics, supporting operator training, mission rehearsal, and human-vehicle interaction in environments where re

Machine Learning for Depression Screening and Intervention: an Original Circadian Rhythm Score-based Methodology

arXiv:2607.04648v1 Announce Type: cross Abstract: Depression screening from large-scale behavioral data is challenged by fragmented circadian indicators, limited interpretability, and the lack of inte

MACRO: Training-free Multi-plane Attention for Closeup Render Optimization

arXiv:2607.03875v1 Announce Type: new Abstract: Close-up rendering, zooming into a scene well beyond any training camera, is important for virtual production and interactive 3D content, yet remains an

MDL Meets Latent Confounders: LNML-based Causal Discovery

arXiv:2607.04133v1 Announce Type: new Abstract: Causal discovery with nonlinear mechanisms and latent confounders remains challenging. Existing methods often rely on either linear assumptions or causa

Measuring the Robustness of Audio Deepfake Detection under Real-World Corruption

arXiv:2503.17577v2 Announce Type: replace-cross Abstract: Deepfakes have emerged as a widespread and rapidly escalating concern in generative AI, spanning images, audio, and videos. Among these, audio

MetaCaDI: A Meta-Learning Framework for Causal Discovery from Multiple Environments with Unknown Interventions

arXiv:2510.22298v2 Announce Type: replace-cross Abstract: Uncovering the causal mechanisms of complex real-world systems remains a significant challenge, as these systems often entail high data collec

MetricAnything: Scaling Metric Depth Pretraining with Noisy Heterogeneous Sources

arXiv:2601.22054v2 Announce Type: replace-cross Abstract: Scaling has powered recent advances in vision foundation models, yet extending this paradigm to metric depth estimation remains challenging du

MIRAGE: Defending Long-Form RAG Against Misinformation Pollution

arXiv:2607.05069v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) improves factuality by grounding LLMs in external evidence, but real-world retrieval is often polluted: semanticall

applicationsarxiv-cs-cl

MOSAIC: Skill-Centric Manipulation Planning with Physics Simulation

arXiv:2504.16738v3 Announce Type: replace-cross Abstract: Planning long-horizon manipulation motions using a set of predefined skills is a central challenge in robotics; solving it efficiently could e

Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales

arXiv:2607.04972v1 Announce Type: cross Abstract: Deploying robot teams in the real world requires simultaneous adaptation to unseen environments, unknown partners, and varying team sizes, yet existin

Norm Ai nabs 120M at 1.2B valuation to bring AI agents to the law

Nomos Ai Inc., a company building a platform to embed legal operations into artificial intelligence agents, today announced it has raised 120 million in new funding, bringing the company’s valuation t

applicationssiliconangle