Search: “applications”

Test-Time Scaling in Multimodal Foundation Models: A Comprehensive Survey of Generation and Reasoning

arXiv:2606.08231v1 Announce Type: new Abstract: Test-time Scaling (TTS) has emerged as a pivotal research direction for enhancing model performance by dynamically allocating computational resources du

researcharxiv-cs-cv

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The Cross-Architecture Substrate: A Domain-Transcendent, Calibration-Surviving Geometric Invariant of Modern Vision Encoders

DGX agent

arXiv:2606.07882v1 Announce Type: cross Abstract: Different vision neural networks -- trained to classify, contrast, reconstruct, or match images to text -- should have correspondingly different inter

safetyarxiv-cs-ai

9 Jun 2026

TQA-Bench: Evaluating LLMs for Multi-Table Question Answering

arXiv:2411.19504v2 Announce Type: replace Abstract: The advance of large language models (LLMs) has unlocked great opportunities in complex multi-modal data management tasks, particularly in question

VGP-Nav: Metric-Aware Visual Geometric Perception for Robot Navigation

arXiv:2606.09268v1 Announce Type: new Abstract: Reliable robotic navigation necessitates the seamless integration of accurate global localization and dense, metric-consistent obstacle perception. A co

agentsarxiv-cs-ro

Weighted universal approximation of differentiable maps on infinite-dimensional manifolds

arXiv:2606.09820v1 Announce Type: cross Abstract: We generalize the universal approximation theorem for functional input neural networks (FNN) to differentiable maps by including the approximation of

Local Ai

When Vision Misleads, Let Location Speak: A Worldwide Image Geo-Localization Method via Location Attention Mechanism and Large Multimodal Models

arXiv:2606.08918v1 Announce Type: new Abstract: Worldwide image geo-localization aims to determine the capture location of an image on a global scale. Existing methods often mislocalize images by matc

local-aiarxiv-cs-cv

Where Instruction Hierarchy Breaks: Diagnosing and Repairing Failures in Reasoning Language Models

arXiv:2606.07808v1 Announce Type: new Abstract: Reasoning language models deployed in agentic workflows must follow an instruction hierarchy: when instructions from different sources conflict, the mod

X-OP: Cross-Morphology Whole-Body Teleoperation via MPC Retargeting

arXiv:2606.07934v1 Announce Type: new Abstract: Whole-body teleoperation is essential for scalable robot data collection in loco-manipulation tasks, yet existing approaches relying on exoskeleton suit

safetyarxiv-cs-ro

Zero-Shot Learning in Industrial Scenarios: New Large-Scale Benchmark, Challenges and Baseline

arXiv:2606.07965v1 Announce Type: new Abstract: Large Visual Language Models (LVLMs) have achieved remarkable success in vision tasks. However, the significant differences between industrial and natur

A Causal Probabilistic Framework for Perception-Informed Closed-Loop Simulation of Autonomous Driving

arXiv:2606.07186v1 Announce Type: new Abstract: Software-in-the-loop (SIL) simulation is a cornerstone for the validation of modern automotive safety functions. However, many current frameworks utiliz

safetyarxiv-cs-ro

A Cross-view Fusion Framework for Robust 6-DoF Grasp Pose Estimation

model-releasesarxiv-cs-cv

arXiv:2606.06878v1 Announce Type: cross Abstract: In this paper, we propose a cross-view fusion framework that enhances the robustness of 6-DoF grasp pose estimation in corner views. Our framework all

A Geometric Gaussian Mixture Representation of Plane Curves

arXiv:2606.06505v1 Announce Type: cross Abstract: We introduce a user defined probabilistic polygonal representation for plane curves. Given a curve, we select vertices on the curve and connect consec

AI-Driven Test Case Generation from Natural Language Requirements: A Survey of Techniques and Research Gaps

arXiv:2606.06563v1 Announce Type: cross Abstract: Software testing is critical for verifying that systems meet specified requirements, yet remains among the most time-consuming and expensive activitie

AMD-FCG: An Enhanced Function Call Graph Dataset with Integrated Topological Features for Malware Detection and Classification

arXiv:2606.06815v1 Announce Type: cross Abstract: As malware illustrates a complex structure and behavior, detection of these has been a significant challenge in the domain of cybersecurity along with

agentsarxiv-cs-lg

ARAPDiffusion: ARAP Regularization for Diffusion-Based Deformable Shape Space Learning

arXiv:2606.06887v1 Announce Type: new Abstract: This paper introduces ARAPDiffusion, a latent diffusion model to learn the underlying continuous shape space of a deformation shape collection. The key

Auditing Training Data in Domain-adapted LLMs: LoRA-MINT

arXiv:2606.06946v1 Announce Type: cross Abstract: We present LoRA-MINT, a new methodology for Membership Inference Test (MINT) applied to recent Large Language Models (LLMs) fine-tuned for specific Na

Beyond Backscatter: InSAR coherence from detected SAR images

arXiv:2606.07374v1 Announce Type: cross Abstract: In this work, we propose a deep learning framework for coherence regression directly from detected SAR images, without the need for accurate coregistr

Bootstrap Theory of Representational Emergence: Explanatory Insufficiency as a Driver of Representation Learning and World Models

arXiv:2606.07303v1 Announce Type: new Abstract: Representation learning is central to modern machine learning, enabling transitions from handcrafted features to learned embeddings, latent spaces, foun

Bounded-Abstention Pairwise Learning to Rank

arXiv:2505.23437v2 Announce Type: replace-cross Abstract: Ranking systems influence decision-making in high-stakes domains like health, education, and employment, where they can have substantial econo

safetyarxiv-cs-ai

Certified Robustness to Data Poisoning in Gradient-Based Training

model-releasesarxiv-cs-cv

arXiv:2406.05670v3 Announce Type: replace-cross Abstract: Modern machine learning pipelines leverage large amounts of public data, making it infeasible to guarantee data quality and leaving models ope

Creation of the Estonian Subjectivity Dataset: Assessing the Degree of Subjectivity on a Scale

model-releasesarxiv-cs-cl

arXiv:2512.09634v2 Announce Type: replace Abstract: This article presents the creation of an Estonian-language dataset for document-level subjectivity, analyzes the resulting annotations, and reports

Deep Single-Index Frechet Regression

arXiv:2606.06957v1 Announce Type: cross Abstract: Predicting outputs that are located in non-Euclidean spaces, such as probability distributions, networks, and symmetric positive-definite matrices, is

Deployed trusted-node quantum key distribution over 300 km with a multi-core fiber access link

arXiv:2606.06107v1 Announce Type: cross Abstract: Quantum key distribution (QKD) is increasingly considered for deployment in realistic communication networks, where long distances, heterogeneous fibe

Differences in Detection: Explainability Where it Matters

arXiv:2606.07503v1 Announce Type: new Abstract: We propose Differences in Detection (DnD), an intuitive method to compare two object detection models. Based on the same matching algorithm, it compleme

Direct 3D-Aware Object Insertion via Decomposed Visual Proxies

arXiv:2606.06601v1 Announce Type: cross Abstract: Object insertion aims to seamlessly composite a reference object into a specified region of a background image. Recent diffusion-based methods achieve

Directed evolution algorithm drives neural prediction

arXiv:2512.01362v2 Announce Type: replace Abstract: Neural prediction offers a promising approach to forecasting the individual variability of neurocognitive functions and disorders and providing prog

Efficient Coordination and Synchronization of Multi-Robot Systems Under Recurring Linear Temporal Logic

arXiv:2502.16531v2 Announce Type: replace Abstract: We consider multi-robot systems under recurring tasks formalized as linear temporal logic (LTL) specifications. To solve the planning problem effici

agentsarxiv-cs-ro

Error-State LQR Formulation for Quadrotor UAV Trajectory Tracking

arXiv:2501.15768v2 Announce Type: replace Abstract: This article presents an error-state Linear Quadratic Regulator (LQR) formulation for robust trajectory tracking in quadrotor Unmanned Aerial Vehicl

researcharxiv-cs-ro

Explainable Runtime Dependency Tracking for AI-RAN Conflict Monitoring

model-releasesarxiv-cs-lg

arXiv:2606.06663v1 Announce Type: new Abstract: Future AI-integrated Radio Access Networks (AI-RAN) will combine open programmability with learning-enabled xApps, rApps, and control functions that act

Extending Responsibility-Sensitive Safety for the Assessment of Offloaded Autonomous Driving Services

arXiv:2606.07067v1 Announce Type: new Abstract: Safety is a fundamental requirement in the development of autonomous driving (AD) systems. While function offloading has demonstrated significant benefi

safetyarxiv-cs-ro

Feasible Action Space Reduction for Quantifying Causal Responsibility in Continuous Spatial Interactions

arXiv:2505.17739v2 Announce Type: replace-cross Abstract: Understanding the causal influence of one agent on another agent is crucial for safely deploying artificially intelligent systems such as auto

agentsarxiv-cs-ro

Finding Most Influential Sets

model-releasesarxiv-cs-lg

arXiv:2606.05919v2 Announce Type: replace-cross Abstract: Identifying most influential sets (MIS) - size-k subsets whose removal maximally changes a target estimand - is typically infeasible because i

Inside the Visual Mind: Neuroscience-Motivated Concept Circuits for Interpreting and Steering Vision Transformers

arXiv:2606.06664v1 Announce Type: cross Abstract: Despite high accuracy, Vision Transformer (ViT) predictions can be driven by spurious cues, raising the need to understand their inner workings before

Lighting-Aware Representation Learning under Controllable Lighting Variation

arXiv:2606.06899v1 Announce Type: new Abstract: Variations in illumination remain a major challenge for visual representation learning, as they induce substantial appearance changes both across and wi

LLM-Guided Search for Deletion-Correcting Codes

arXiv:2504.00613v2 Announce Type: replace Abstract: Finding deletion-correcting codes of maximum size has been an open problem for over 70 years, even for a single deletion. We adapt FunSearch, a larg

Model Recycling Framework for Multi-Source Data-Free Supervised Transfer Learning

model-releasesarxiv-cs-lg

arXiv:2508.02039v2 Announce Type: replace Abstract: Increasing concerns for data privacy and other difficulties associated with retrieving source data for model training have created the need for sour

Local Ai

Off-Policy Evaluation with Strategic Agents via Local Disclosure

arXiv:2606.07308v1 Announce Type: new Abstract: We study off-policy evaluation (OPE) under strategic behavior where decision subjects (or agents) respond to a decision maker's policy by strategically

local-aiarxiv-cs-ai

On orbital stabilization of a circular motion primitive for a dynamic extension of the Dubins car model

arXiv:2606.07449v1 Announce Type: cross Abstract: This paper addresses orbital stabilization of a circular motion primitive for a dynamic extension of the Dubins car model within a transverse-lineariz

researcharxiv-cs-ro

OpenHalDet: A Unified Benchmark for Hallucination Detection across Diverse Generation Scenarios

arXiv:2606.06959v1 Announce Type: cross Abstract: Hallucination detection is essential for the reliable deployment of large language models (LLMs). However, existing evaluations face two core challeng

Principles and Practice of Deep Representation Learning: or a Mathematical Theory of Memory

arXiv:2606.06624v1 Announce Type: new Abstract: In the current era of deep learning and especially generative models, there is significant investment in training very large generative models. Thus far

Re-imagining ISO 26262 in the Age of Autonomous Vehicles: Enhancing Controllability through Transferability and Predictability

arXiv:2606.07437v1 Announce Type: cross Abstract: The ISO 26262 standard defines functional safety for road vehicles through risk assessments based on Severity, Exposure, and Controllability, grounded

safetyarxiv-cs-ai

ReclAIm: A Multi-Agent Framework for Monitoring and Correcting Performance Decline in Medical Imaging AI

arXiv:2510.17004v2 Announce Type: replace-cross Abstract: Purpose: To develop and evaluate a multi-agent framework (ReclAIm) for automated monitoring, detection, and correction of performance decline

REMEDI: A Benchmark for Retention and Unlearning Evaluation in Multi-label Clinical Disease Inference

arXiv:2606.07141v1 Announce Type: cross Abstract: Language models trained for clinical disease inference are trained on patient data, which may include sensitive and private information, and data owne

SegMoTE: Token-Level Mixture of Experts for Medical Image Segmentation

arXiv:2602.19213v2 Announce Type: replace Abstract: Medical image segmentation is vital for clinical diagnosis and quantitative analysis, yet remains challenging due to the heterogeneity of imaging mo

researcharxiv-cs-cv

SigmaScale: LLM Compression with SVD-based Low-Rank Decomposition and Learned Scaling Matrices

model-releasesarxiv-cs-cl

arXiv:2606.07098v1 Announce Type: new Abstract: We present SigmaScale, a method for learning auxiliary scaling matrices S to aid truncated Singular Value Decomposition (SVD) based Large Language Model

STRIPS-WM: Learning Grounded Propositional STRIPS-style World Models from Images

arXiv:2606.06832v1 Announce Type: new Abstract: Robots performing long-horizon visual manipulation observe high-dimensional images, but successful plans depend on action-relevant facts: what can be do

researcharxiv-cs-ro

Local Ai

Task Editing for Generalizable 3D Visuomotor Policy Learning

arXiv:2606.07012v1 Announce Type: new Abstract: 3D visuomotor policies offer a promising direction for complex robotic manipulation, as depth maps and point clouds provide rich geometric information f

local-aiarxiv-cs-ro

The Sim-to-Real Gap of Foundation Model Agents: A Unified MDP Perspective

arXiv:2606.07017v1 Announce Type: new Abstract: Foundation model agents are increasingly deployed for real-world decision-making, but suffer from the sim-to-real gap. While robotics and classical cont

agentsarxiv-cs-ai