Search: “papers”

Safety-Critical Control for Smoothed Implicit Contact Dynamics

model-releasesarxiv-cs-ro

arXiv:2605.21138v1 Announce Type: new Abstract: Smoothed implicit contact dynamics enables gradient-based planning and control for contact-rich tasks without predefined mode sequences. However, safety

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Seeing Through Fog: Towards Fog-Invariant Action Recognition

DGX agent

arXiv:2605.20645v1 Announce Type: new Abstract: Foggy conditions are commonly encountered in real-world applications; however, existing action recognition approaches typically assume favorable weather

model-releasesarxiv-cs-cv

21 May 2026

Shiny Stories, Hidden Struggles: Investigating the Representation of Disability Through the Lens of LLMs

arXiv:2605.20191v1 Announce Type: new Abstract: Modern Large Language Models (LLMs) have recently attracted much attention for their ability to simulate human behavior and generate text that reflects

safetyarxiv-cs-cl

Testing Support Size More Efficiently Than Learning Histograms

arXiv:2410.18915v4 Announce Type: replace-cross Abstract: Consider two problems about an unknown probability distribution p: 1. How many samples from p are required to test if p is supported on n elem

Text Analytics Evaluation Framework: A Case Study on LLMs and Social Media

model-releasesarxiv-cs-cl

arXiv:2605.21338v1 Announce Type: new Abstract: LLMs have demonstrated exceptional proficiency in a wide range of NLP tasks. However, a notable gap remains in practical data analysis scenarios, partic

Time-To-Reach Separation and Safety Filtering for Safe, Fair, and Efficient Multi-Agent Coordination

arXiv:2605.20625v1 Announce Type: cross Abstract: Advanced Air Mobility (AAM) operations are expected to significantly increase aerial traffic in urban airspace, requiring autonomous traffic managemen

safetyarxiv-cs-ro

torchtune: PyTorch native post-training library

arXiv:2605.21442v1 Announce Type: new Abstract: Modern LLMs typically require multistage training pipelines to achieve strong downstream performance, with post-training serving as the main interface f

Towards Resilient and Autonomous Networks: A BlueSky Vision on AI-Native 6G

arXiv:2605.21395v1 Announce Type: cross Abstract: The proliferation of emerging applications, such as autonomous driving and immersive experiences, demands cellular networks that are not only faster,

agentsarxiv-cs-lg

Towards the Anonymization of the Language Modeling

arXiv:2501.02407v3 Announce Type: replace Abstract: Rapid advances in Natural Language Processing (NLP) have revolutionized many fields, including healthcare. However, these advances raise significant

applicationsarxiv-cs-cl

Tunable MAGMAX: Preference-Aware Model Merging for Continual Learning

model-releasesarxiv-cs-lg

arXiv:2605.20803v1 Announce Type: new Abstract: Continual learning (CL) aims to train models sequentially on multiple tasks while mitigating catastrophic forgetting of previously learned knowledge. Re

UniEdit-Flow: Unleashing Inversion and Editing in the Era of Flow Models

arXiv:2504.13109v2 Announce Type: replace Abstract: Flow matching models have emerged as a strong alternative to diffusion models, but existing inversion and editing methods designed for diffusion are

USV: Towards Understanding the User-generated Short-form Videos

arXiv:2605.20838v1 Announce Type: new Abstract: Several large-scale video datasets have been published these years and have advanced the area of video understanding. However, the newly emerged user-ge

Validating Navmesh using Geometry: Voxel-Based Analysis with Prioritized Exploration

arXiv:2605.21397v1 Announce Type: cross Abstract: Navigation mesh (Navmesh) inconsistencies affect the player experience by directly impacting the navigation systems used by non-playable characters (N

applicationsarxiv-cs-ro

Verifiable Error Bounds for Physics-Informed Neural Network Solutions of Lyapunov and Hamilton-Jacobi-Bellman Equations

arXiv:2603.19545v2 Announce Type: replace-cross Abstract: Many core problems in nonlinear systems analysis and control can be recast as solving partial differential equations (PDEs) such as Lyapunov a

safetyarxiv-cs-lg

Vision Transformers and Convolutional Neural Networks for Land Use Scene Classification

model-releasesarxiv-cs-cv

arXiv:2605.21268v1 Announce Type: new Abstract: Land Use Scene Classification (LUSC) from remote sensing imagery plays a critical role in environmental monitoring, urban planning, and sustainable reso

WaveGraphNet: Physics-Consistent Guided-Wave Damage Localization through Coupled Inverse-Forward Graph Learning

model-releasesarxiv-cs-lg

arXiv:2605.20311v1 Announce Type: new Abstract: Guided-wave structural health monitoring enables damage localization in composite plates using sparse networks of bonded piezoelectric transducers. Howe

Why Latent Actions Fail, and How to Prevent It

arXiv:2605.20223v1 Announce Type: new Abstract: Latent action models (LAMs) aim to learn action-like representations from unlabeled videos by compressing frame-to-frame changes. The frames of in-the-w

agentsarxiv-cs-cv

Tutorials

WiXus: A Wheeled-Legged Robot with Wire-Driven Environmental Utilizing to Integrate Mobility and Manipulation

arXiv:2605.20932v1 Announce Type: new Abstract: Wheeled-legged robots, which have wheels at their feet and achieve high mobility by coordinating wheel drive and leg drive, have been developed. These r

tutorialsarxiv-cs-ro

A Data-Driven Approach to Idiomaticity Based on Experts' Criteria in Theoretical Linguistics

arXiv:2605.19575v1 Announce Type: new Abstract: The article observes data analysis of 286 multi-word expressions (MWEs) based on 16 lexical, grammatical and other criteria described in theoretical boo

researcharxiv-cs-cl

A Derandomization Framework for Structure Discovery: Applications in Neural Networks and Beyond

arXiv:2510.19382v2 Announce Type: replace-cross Abstract: Understanding the dynamics of feature learning in neural networks (NNs) remains a significant challenge. The work of (Mousavi-Hosseini et al.,

A Grid-Based Framework for E-Scooter Demand Representation and Temporal Input Design for Deep Learning: Evidence from Austin, Texas

arXiv:2603.13609v2 Announce Type: replace Abstract: Despite progress in deep learning for shared micromobility demand prediction, the systematic design and statistical validation of temporal input str

A novel YOLO26-MoE optimized by an LLM agent for insulator fault detection considering UAV images

arXiv:2605.19595v1 Announce Type: cross Abstract: The inspection of electrical power line insulators is essential for ensuring grid reliability and preventing failures caused by damaged or degraded in

agentsarxiv-cs-ai

A Practical Framework of Key Performance Indicators for Multi-Robot Lunar and Planetary Field Tests

arXiv:2601.20529v3 Announce Type: replace Abstract: Robotic prospecting for critical resources on the Moon, such as ilmenite, rare earth elements, and water ice, requires robust exploration methods gi

researcharxiv-cs-ro

Agentic Trading: When LLM Agents Meet Financial Markets

arXiv:2605.19337v1 Announce Type: new Abstract: A growing body of work explores how Large Language Models (LLMs) can be embedded in trading systems as agents that perceive market information, retrieve

agentsarxiv-cs-ai

An Empirical Investigation of Reconstruction-Based Models for Seizure Prediction from ECG Signals

arXiv:2504.08381v2 Announce Type: replace-cross Abstract: Epileptic seizures are transient neurological events characterized by abnormal and excessive neuron activity in the brain, which are often ass

applicationsarxiv-cs-lg

An Objective Performance Evaluation of the LSTM Networks in Time Series Classification

arXiv:2605.19311v1 Announce Type: new Abstract: The rapid adoption of deep learning has increasingly led to data-driven models replacing classical model-based algorithms, even in domains governed by w

AQuaUI: Visual Token Reduction for GUI Agents with Adaptive Quadtrees

arXiv:2605.19260v1 Announce Type: new Abstract: Large Multimodal Models (LMMs) have recently emerged as promising backbones for GUI-agent models, where high-resolution GUI screenshots are introduced t

agentsarxiv-cs-ai

AR1-ZO: Topology-Aware Rank-1 Zeroth-Order Queries for High-Rank LoRA Fine-Tuning

arXiv:2605.19767v1 Announce Type: cross Abstract: Zeroth-order (ZO) optimization enables large-language-model fine-tuning without storing backpropagation activations, while LoRA supplies compact train

Artificial Intelligence, conceptual metaphors and conceptual engineering: Are AI-based framings of human behaviour and cognition successful?

arXiv:2504.07756v2 Announce Type: replace Abstract: Understanding human behaviour, neuroscience and psychology using concepts from the domain of AI is increasing in popularity. Given the massive integ

Atoms of Thought: Universal EEG Representation Learning with Microstates

arXiv:2605.20182v1 Announce Type: cross Abstract: Learning universal representations from electroencephalogram (EEG) signals is a cutting-edge approach in the field of neuroinformatics and brain-compu

Attention-Guided Reward for Reinforcement Learning-based Jailbreak against Large Reasoning Models

arXiv:2605.19485v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) have demonstrated remarkable capabilities in solving complex problems by generating structured, step-by-step reasoning con

safetyarxiv-cs-ai

Automated Big Data Quality Assessment using Knowledge Graph Embeddings

arXiv:2605.18833v1 Announce Type: cross Abstract: Automated data quality assessment is crucial for managing big data, but existing solutions face challenges in achieving accurate context-aware assessm

applicationsarxiv-cs-ai

Local Ai

BabyMamba-HAR: Lightweight Selective State Space Models for Efficient Human Activity Recognition on Resource Constrained Devices

arXiv:2602.09872v2 Announce Type: replace Abstract: Human activity recognition (HAR) on resource constrained devices requires high accuracy across diverse sensor setups. Selective state space models (

local-aiarxiv-cs-cv

Bayesian Joint Model of Multi-Sensor and Failure Event Data for Multi-Mode Failure Prediction

arXiv:2506.17036v2 Announce Type: replace-cross Abstract: Modern industrial systems are often subject to multiple failure modes, and their conditions are monitored by multiple sensors, generating mult

BLINKG: A Benchmark for LLM-Integrated Knowledge Graph Generation

model-releasesarxiv-cs-ai

arXiv:2605.19518v1 Announce Type: new Abstract: Generating Knowledge Graphs (KGs) remains one of the most time-consuming and labor-intensive tasks for knowledge engineers, as they need to identify sem

Block-Sphere Vector Quantization

arXiv:2605.19972v1 Announce Type: cross Abstract: Vector quantization is a fundamental primitive for scalable machine learning systems, enabling memory-efficient storage, fast retrieval, and compresse

CAD-Free Learning of Spacecraft Pose Estimators via NeRF-Based Augmentations

arXiv:2605.19649v1 Announce Type: new Abstract: Spacecraft pose estimation networks require tens of thousands of CAD-rendered images to be trained. This reliance on synthetic CAD data (i) limits appli

CADENet: Condition-Adaptive Asynchronous Dual-Stream Enhancement Network for Adverse Weather Perception in Autonomous Driving

arXiv:2605.19837v1 Announce Type: cross Abstract: Adverse weather (rain, fog, sand, and snow) degrades camera-based object detection in autonomous vehicles. Existing enhancement-then-detect approaches

safetyarxiv-cs-ai

CLIC: Contextual Language-Informed Cardiac Pathology Classification

arXiv:2605.19132v1 Announce Type: new Abstract: The electrocardiogram (ECG) is the gold standard for non-invasive diagnosis of cardiac pathologies and is a fundamental pillar of cardiovascular medicin

ClinSeekAgent: Automating Multimodal Evidence Seeking for Agentic Clinical Reasoning

model-releasesarxiv-cs-cl

arXiv:2605.20176v1 Announce Type: new Abstract: Large language models (LLMs) and agentic systems have shown promise for clinical decision support, but existing works largely assume that evidence has a

Closed-Loop Hybrid Digital Twin Platform for Connected and Automated Vehicle Validation

arXiv:2605.19490v1 Announce Type: cross Abstract: Comprehensive and efficient validation of connected and automated vehicles (CAVs) is critical prior to real-world deployment. While simulation-based t

applicationsarxiv-cs-cv

CogScale: Scalable Benchmark for Sequence Processing

model-releasesarxiv-cs-ai

arXiv:2605.19758v1 Announce Type: new Abstract: The ability to maintain and manipulate information over time is a fundamental aspect of living beings and Artificial Intelligence. While modern models h

COMPASS: Confined-space Manipulation Planning with Active Sensing Strategy

model-releasesarxiv-cs-ro

arXiv:2509.14787v2 Announce Type: replace Abstract: Manipulation in confined and cluttered environments remains a significant challenge due to partial observability and complex configuration spaces. E

Component-Aware Structure-Preserving Style Transfer for Satellite Sim2Real 6D Pose Estimation

arXiv:2605.19624v1 Announce Type: cross Abstract: Monocular 6D pose estimation for non-cooperative satellites depends heavily on annotated training data, yet real satellite images with reliable pose l

Compositional Literary Primitives in Instruction-Tuned LLMs: Cross-Architectural SAE Features for Self, Style, and Affect

model-releasesarxiv-cs-ai

arXiv:2605.18808v1 Announce Type: cross Abstract: We characterize a compositional architecture of literary primitives in two instruction-tuned large language models (Llama 3.1 8B-Instruct and Gemma 2

Context-dependent manifold learning: A neuromodulated constrained autoencoder approach

arXiv:2603.11673v2 Announce Type: replace Abstract: Many physical systems exhibit a low-dimensional structure that varies with external parameters: link lengths in a robot, forcing constants in a flui

safetyarxiv-cs-lg

CopT: Contrastive On-Policy Thinking with Continuous Spaces for General and Agentic Reasoning

arXiv:2605.20075v1 Announce Type: cross Abstract: Chain-of-thought (CoT) is a standard approach for eliciting reasoning capabilities from large language models (LLMs). However, the common CoT paradigm

safetyarxiv-cs-ai

Counterfactual Likelihood Tests for Indirect Influence in Private Reasoning Channels

arXiv:2605.19092v1 Announce Type: cross Abstract: Reasoning systems increasingly separate intermediate computation into private and public channels, creating evaluation cases that look similar in tran