Search: “models”

An LLM-Explainable DRL Framework for Passenger-Directed Autonomous Driving

arXiv:2606.20640v1 Announce Type: cross Abstract: Autonomous vehicles offer the potential for safer and more efficient mobility, yet public trust remains limited due to the lack of transparency in the

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Anatomically Consistent TMJ Disc Segmentation via Semantic Anchoring and Clinical Priors

DGX agent

arXiv:2606.21177v1 Announce Type: cross Abstract: Segmenting the temporomandibular joint (TMJ) disc from MRI is essential for accurate diagnosis of internal derangement, yet it remains unreliable in p

local-aiarxiv-cs-cv

23 Jun 2026

Any-Body Guard: Universal Safeguarding for Manipulation Policies via Action Masking

arXiv:2606.22278v1 Announce Type: cross Abstract: Ensuring safety of learning-enabled robotic manipulation across diverse embodiments and tasks still requires significant manual engineering. Existing

Approximating velocity fields with planted attractors via Neural-ODEs for classification purposes

arXiv:2606.23550v1 Announce Type: cross Abstract: In this work, Neural ODEs equipped with a curated collection of equilibrium points have been successfully employed for classification tasks.The plante

Artic-O: End-to-End Articulated Object Reconstruction via Latent Geometry Learning

arXiv:2606.21938v1 Announce Type: new Abstract: Reconstructing articulated objects from sparse images requires recovering complete geometry, movable parts, and motion parameters. Recent methods typica

researcharxiv-cs-cv

Tutorials

Asymmetric physics enables efficient learning in quadrupedal robot swarms

arXiv:2606.23153v1 Announce Type: new Abstract: Animal collectives navigate cluttered environments through local coordination, yet robot swarms still struggle to reproduce this capability in the physi

tutorialsarxiv-cs-ro

Autonomous Subsea Cable Search and Tracking with Graph-Optimised Priors and Visual Tracking

arXiv:2606.23606v1 Announce Type: cross Abstract: Global communications rely on subsea cable infrastructure that remains vulnerable to damage from natural hazards and human activity. Autonomous underw

agentsarxiv-cs-cv

b9771

local-aillama-cpp-releases

llama.cpp release b9771 addresses Vulkan optimization by making mul_mm ALIGNED a spec constant, reducing shader variant explosion and binary size. This release is part of the ongoing development of ll

Hardware

BAC-JEPA: Label-Efficient Breast Arterial Calcification Segmentation via Synthetic Mammography-Guided Supervision

arXiv:2606.22089v1 Announce Type: new Abstract: Breast arterial calcification (BAC) on screening mammograms is an emerging cardiovascular risk biomarker, but quantitative use requires reproducible seg

hardwarearxiv-cs-cv

BayesFP: Posterior Estimation for Flow-Based Policies via Feynman-Kac Sampling

arXiv:2606.21014v1 Announce Type: new Abstract: Robots must generate trajectories that remain faithful to learned expert behavior while satisfying safety constraints and task-specific objectives speci

safetyarxiv-cs-ro

Applications

Beyond a Single Light: A Large-Scale Aerial Dataset for Urban Scene Reconstruction Under Varying Illumination

arXiv:2512.14200v2 Announce Type: replace Abstract: Recent advances in Neural Radiance Fields and 3D Gaussian Splatting have demonstrated strong potential for large-scale UAV-based 3D reconstruction t

applicationsarxiv-cs-cv

BLENDS: Bayesian Learning-Enhanced Deep Smoothing for GNSS-Denied Environments

arXiv:2606.22456v1 Announce Type: new Abstract: Maintaining accurate navigation during GNSS outages remains a significant challenge for autonomous systems relying on low-cost inertial sensors. While c

safetyarxiv-cs-ro

Tutorials

Brain-Inspired Stochastic Joint Embedding Representation Learning

arXiv:2505.11129v2 Announce Type: replace Abstract: Representation learning is one of the key research topics in machine learning, and the framework of self-supervised learning (SSL) has revolutionize

tutorialsarxiv-cs-cv

Breaking chains with trees: Deep learning with O(log N) parallel time complexity

arXiv:2606.21497v1 Announce Type: new Abstract: Modern deep neural network architectures are trained via backpropagation, which requires errors to be sequentially propagated through all layers before

local-aiarxiv-cs-lg

Applications

Bridging Single Distortion Artifacts and Multifactorial Clinical Quality: Few-shot Biparametric MRI Quality Assessment via Distortion-trained Prototypical Networks

arXiv:2606.18872v2 Announce Type: replace Abstract: Clinical prostate multi-parametric MRI relies heavily on high-quality diffusion-weighted imaging (DWI), yet reading DWI is frequently compromised by

applicationsarxiv-cs-cv

Tutorials

Build a protein research copilot with Amazon Bedrock AgentCore

This post shows you how to build a conversational protein research assistant that combines three capabilities: Natural language query parsing to extract structured search parameters, vector similarity

tutorialsaws-ml-blog

Hardware

Build an AI Scientist for Life Science Discovery with NVIDIA BioNeMo Agent Toolkit

The NVIDIA BioNeMo Agent Toolkit enables AI scientists to use structure prediction, molecular generation, docking, sequence analysis, design, and genomics as callable tools , allowing AI agents to exe

hardwarenvidia-developer

Build Once, Monitor Continuously: Persistent Semantic Mapping via Autonomous Exploration and Open-Vocabulary Object Updates

arXiv:2409.15493v4 Announce Type: replace-cross Abstract: Persistent semantic monitoring of indoor spaces such as warehouses, hospitals, and offices requires a robot to repeatedly monitor an environme

local-aiarxiv-cs-cv

Bypassing Minimization Bias: A Shift-Invariant Variance Estimator for Off-Equilibrium Local Learning Coefficients

arXiv:2606.22389v1 Announce Type: new Abstract: Singular Learning Theory leverages the Local Learning Coefficient (LLC) to quantify the geometry of neural network loss landscapes. However, mean-energy

Can Single-View Mesh Reconstruction Generalize to Robot Camera Rotation?

arXiv:2606.22987v1 Announce Type: new Abstract: Single-view mesh reconstruction predicts object meshes and spatial layouts from a single observation, making it attractive for fast robot spatial reason

researcharxiv-cs-cv

Chain-of-Goals Hierarchical Policy for Long-Horizon Offline Goal-Conditioned RL

arXiv:2602.03389v2 Announce Type: replace Abstract: Offline goal-conditioned reinforcement learning remains challenging for long-horizon tasks. While hierarchical approaches mitigate this issue by dec

Circuit realization and hardware linearization of monotone operator equilibrium networks

arXiv:2509.13793v2 Announce Type: replace-cross Abstract: It is shown that the port behavior of a resistor-diode network corresponds to the solution of a ReLU monotone operator equilibrium network (a

Circuit Synchronization Precedes Generalization: A Causal Precursor to Grokking

arXiv:2606.12966v2 Announce Type: replace Abstract: Grokking is the delayed generalisation phenomenon where a transformer trained on modular arithmetic abruptly transitions from near-chance to near-pe

Hardware

CITADEL: CSI-Based Jamming Detection and Open-Set Classification for IIoT Networks

arXiv:2606.22939v1 Announce Type: cross Abstract: Radio frequency jamming poses a critical threat to the availability of wireless Industrial Internet of Things (IIoT) networks. Existing detection and

hardwarearxiv-cs-lg

CLAR: Learning 3D Representations for Robotic Manipulation by Fusing Masked Reconstruction with Multi-Level Contrastive Alignment

arXiv:2507.08262v2 Announce Type: replace-cross Abstract: The spatial information inherent in 3D point clouds is crucial for robotic manipulation. However, existing 3D pre-training methods face a fund

Combinatorial Allocation Bandits with Nonlinear Arm Utility

arXiv:2603.07005v2 Announce Type: replace Abstract: A matching platform is a system that matches participants of different types, such as companies and job-seekers. In such a platform, maximizing matc

Configurable Algorithms for Histopathologic Cancer Detection on Quantum Hardware

arXiv:2606.21752v1 Announce Type: cross Abstract: Histopathologic cancer detection is challenging due to tissue variability, staining differences, and subtle visual distinctions between disease classe

local-aiarxiv-cs-cv

Continuous Behavioral Authentication via Multi-Expert BERT Log Analysis for Secure Data Sharing

arXiv:2606.21900v1 Announce Type: cross Abstract: Continuous authentication for mobile and zero-trust systems requires nonintrusive evidence confirming the enrolled user-device context remains valid a

CQD-SHAP: Explainable Complex Query Answering via Shapley Values

arXiv:2510.15623v2 Announce Type: replace Abstract: Complex query answering (CQA) goes beyond the widely studied link prediction task by addressing more sophisticated queries that require multi-hop re

CrediBench: Building Web-Scale Network Datasets for Information Integrity

arXiv:2509.23340v4 Announce Type: replace-cross Abstract: Automatically assessing the credibility of online sources presents an invaluable tool for navigating today's information ecosystem. However, e

D2HDMap: Non-visible Driveline Map Prior for Online Vectorized HD Map Prediction

arXiv:2606.20725v1 Announce Type: new Abstract: Accurate, up-to-date representations of road structures are critical for the safe operation of autonomous vehicles. Existing systems rely either on cost

Dead-Direction Signatures: A Cheap Spectral Reading of Singular Complexity

arXiv:2606.21158v1 Announce Type: new Abstract: Singular learning theory characterises the complexity of a deep network through the geometry of its loss singularities. The local learning coefficient (

local-aiarxiv-cs-lg

Decentralized Autonomous Traffic Management through Corridor Networks

arXiv:2606.23585v1 Announce Type: cross Abstract: As autonomous aircraft are introduced at scale and traffic density increases, centralized management becomes insufficient to coordinate the large numb

agentsarxiv-cs-ro

Dense Reward for Multi-View 3D Reasoning with Global Maps and Local Views

arXiv:2606.23557v1 Announce Type: new Abstract: Multi-view 3D Visual Question Answering (MV3D-VQA) requires integrating partial observations into a coherent 3D scene representation and selecting infor

Detecting Satellites in Radio-Frequency Data via Semi-Supervised Learning

arXiv:2606.20976v1 Announce Type: new Abstract: Radio-frequency (RF) monitoring is essential for space domain awareness, but it often generates large, variable, and sparsely populated datasets with fe

Direct Raw Audio Signal Processing via Reservoir Computing: An Investigation into 'Feature-Free' Architectures

arXiv:2606.21335v1 Announce Type: cross Abstract: This paper evaluates Reservoir Computing (RC) as an autonomous, 'feature-free' framework for audio processing, designed to eliminate traditional, hand

agentsarxiv-cs-lg

Domain-incremental audio classification using domain-specific experts and prototype classifier

arXiv:2606.22952v1 Announce Type: cross Abstract: This technical report presents submission systems for Task 7(domain-incremental audio classification) of the DCASE 2026 Challenge. The main obstacle i

DPLAN: Minimal Connectivity to Floorplan Generation

arXiv:2606.21159v1 Announce Type: cross Abstract: Automated floor plan generation is an important problem in computational architectural design. The goal is to construct a floor plan from user-defined

researcharxiv-cs-ro

Applications

DreamUV: Unwrap Artist-like UV by End-to-End Flow Matching

arXiv:2606.22445v1 Announce Type: new Abstract: UV parameterization is a fundamental step in 3D content creation, yet producing production-ready UV layouts remains challenging due to the gap between g

applicationsarxiv-cs-cv

DT-GOL: Dual-Track Geometric Online Learning in Nonstationary Environment with Label Delay

arXiv:2606.22950v1 Announce Type: new Abstract: Online learning is crucial for handling complex data streams in big data applications. Recent research has begun to focus on dynamic scenarios, i.e., no

Dual-Attention Convolution Experts for Sparse Tensor Completion

arXiv:2606.21427v1 Announce Type: new Abstract: Tensor factorization (TF) has been widely adopted for high-dimensional sparse data completion tasks. Despite significant progress, neural TF methods oft

EasyUUV: An LLM-Enhanced Universal and Lightweight Sim-to-Real Reinforcement Learning Framework for UUV Attitude Control

arXiv:2510.22126v3 Announce Type: replace Abstract: Despite recent advances in Unmanned Underwater Vehicle (UUV) attitude control, existing methods still struggle with generalizability, robustness to

safetyarxiv-cs-ro

Efficient Document Tampering Localization with Multi-Level Discrepancy Features and Unified DCT-Quantization Embedding

arXiv:2606.22285v1 Announce Type: new Abstract: Localizing document tampering is extremely challenging, as manipulations are crafted to appear visually consistent and often leave only subtle traces th

local-aiarxiv-cs-cv

Enhancing IMU-Based Online Handwriting Recognition via Contrastive Learning with Zero Inference Overhead

arXiv:2602.07049v2 Announce Type: replace Abstract: Online handwriting recognition using inertial measurement units opens up handwriting on paper as input for digital devices. Doing it on edge hardwar

Equilibrium with Internal Transfers

arXiv:2606.20960v1 Announce Type: cross Abstract: Nash equilibrium (NE) arises from selfish utility maximization, yet its social welfare can be arbitrarily far from optimal. Moreover, computing an NE

agentsarxiv-cs-lg

Escaping the Variance Trap: Jacobian-Free Dynamics for Root-Finding Bilevel Optimization

arXiv:2606.22433v1 Announce Type: new Abstract: Many central machine learning tasks, from entropy tuning in reinforcement learning to equilibrating generative adversarial networks, are fundamentally s

Evals are the new PRDs, @hwchase17 It might be my takeaway of the @LangChain Chicago meetup tonight.

Harrison Chase suggests that evaluations (evals) are becoming as critical to AI/LLM development as Product Requirements Documents (PRDs) traditionally were, implying a shift in how teams validate and

agentsharrison-chase--x

Evaluating self-supervised echocardiographic representations across downstream extraction strategies for left-ventricular segmentation and ejection fraction estimation

arXiv:2606.22943v1 Announce Type: new Abstract: Self-supervised learning (SSL) is increasingly used in medical imaging to reduce annotation requirements, but representation quality is often judged usi

researcharxiv-cs-cv