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Robust Lightweight Crack Classification for Real-Time UAV Bridge Inspection

arXiv:2604.27617v1 Announce Type: cross Abstract: With the widespread application of Unmanned Aerial Vehicles (UAVs) in bridge structural health monitoring, deep learning-based automatic crack detecti

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Research

RopeDreamer: A Kinematic Recurrent State Space Model for Dynamics of Flexible Deformable Linear Objects

DGX agent

arXiv:2604.28161v1 Announce Type: new Abstract: The robotic manipulation of Deformable Linear Objects (DLOs) is a fundamental challenge due to the high-dimensional, non-linear dynamics of flexible str

researcharxiv-cs-ro

1 May 2026

RPC-Bench: A Fine-grained Benchmark for Research Paper Comprehension

arXiv:2601.14289v2 Announce Type: replace-cross Abstract: Understanding research papers remains challenging for foundation models due to specialized scientific discourse and complex figures and tables

RuC: HDL-Agnostic Rule Completion Benchmark Generation

arXiv:2604.27780v1 Announce Type: cross Abstract: Large Language Models (LLMs) have rapidly improved in performance across code-related tasks, making their integration into Register Transfer Level (RT

Safe Bilevel Delegation (SBD): A Formal Framework for Runtime Delegation Safety in Multi-Agent Systems

arXiv:2604.27358v1 Announce Type: new Abstract: As large language model (LLM) agents are deployed in high-stakes environments, the question of how safely to delegate subtasks to specialized sub-agents

safetyarxiv-cs-ai

Sample-efficient evidence estimation of score based priors for model selection

arXiv:2602.20549v2 Announce Type: replace-cross Abstract: The choice of prior is central to solving ill-posed imaging inverse problems, making it essential to select one consistent with the measuremen

safetyarxiv-cs-cv

Sampler-Robust Optimization under Generative Models

arXiv:2604.27447v1 Announce Type: cross Abstract: Modern stochastic optimization pipelines increasingly rely on learned generative models to represent uncertainty, while downstream decisions are evalu

Sampling two-dimensional spin systems with transformers

arXiv:2604.27738v1 Announce Type: cross Abstract: Autoregressive Neural Networks based on dense or convolutional layers have recently been shown to be a viable strategy for generating classical spin s

researcharxiv-cs-lg

SASI: Leveraging Sub-Action Semantics for Robust Early Action Recognition in Human-Robot Interaction

arXiv:2604.27508v1 Announce Type: new Abstract: Understanding human actions is critical for advancing behavior analysis in human-robot interaction. Particularly in tasks that demand quick and proactiv

researcharxiv-cs-ro

ScaleBox: Enabling High-Fidelity and Scalable Code Verification for Large Language Models

arXiv:2604.27467v1 Announce Type: cross Abstract: Code sandboxes have emerged as a critical infrastructure for advancing the coding capabilities of large language models, providing verifiable feedback

SCOPE-FE: Structured Control of Operator and Pairwise Exploration for Feature Engineering

model-releasesarxiv-cs-lg

arXiv:2604.27025v1 Announce Type: cross Abstract: Automatic feature engineering is an effective approach for improving predictive performance in tabular learning. However, expand-and-reduce methods, s

SECOS: Semantic Capture for Rigorous Classification in Open-World Semi-Supervised Learning

arXiv:2604.27596v1 Announce Type: new Abstract: In open-world semi-supervised learning (OWSSL), a model learns from labeled data and unlabeled data containing both known and novel classes. In practica

Local Ai

Secret Stealing Attacks on Local LLM Fine-Tuning through Supply-Chain Model Code Backdoors

arXiv:2604.27426v1 Announce Type: cross Abstract: Local fine-tuning datasets routinely contain sensitive secrets such as API keys, personal identifiers, and financial records. Although ''local offline

local-aiarxiv-cs-ai

Agents

Security Attack and Defense Strategies for Autonomous Agent Frameworks: A Layered Review with OpenClaw as a Case Study

arXiv:2604.27464v1 Announce Type: cross Abstract: Autonomous agent frameworks built upon large language models (LLMs) are evolving into complex, tool-integrated, and continuously operating systems, in

agentsarxiv-cs-ai

Selective Augmentation: Improving Universal Automatic Phonetic Transcription via G2P Bootstrapping

arXiv:2604.27204v1 Announce Type: new Abstract: In the field of universal automatic phonetic transcription (APT), clean and diverse training transcriptions are required. However, such high-quality dat

Agents

Self-Evolving Software Agents

arXiv:2604.27264v1 Announce Type: cross Abstract: Autonomous agents can adapt their behaviour to changing environments, but remain bound to requirements, goals, and capabilities fixed at design time,

agentsarxiv-cs-ai

Self-Supervised Learning of Plant Image Representations

arXiv:2604.27538v1 Announce Type: new Abstract: Automated plant recognition plays a crucial role in biodiversity monitoring and conservation, yet current approaches rely heavily on supervised learning

Semantic Structure of Feature Space in Large Language Models

arXiv:2604.27169v1 Announce Type: new Abstract: We show that the geometric relations between semantic features in large language models' hidden states closely mirror human psychological associations.

Semantic Variational Bayes Based on Semantic Information G Theory for Solving Latent Variables

arXiv:2408.13122v2 Announce Type: replace-cross Abstract: The Variational Bayesian method (VB) is used to solve the probability distributions of latent variables with the minimum free energy criterion

Applications

Sentiment Analysis of AI Adoption in Indonesian Higher Education Using Machine Learning and Transformer-Based Models

arXiv:2604.27439v1 Announce Type: new Abstract: This study analyzes Indonesian student opinions on the adoption of artificial intelligence in higher education using two approaches: TF-IDF-based machin

applicationsarxiv-cs-cl

Tutorials

Sequential Inference for Gaussian Processes: A Signal Processing Perspective

arXiv:2604.28163v1 Announce Type: cross Abstract: The proliferation of capable and efficient machine learning (ML) models marks one of the strongest methodological shifts in signal processing (SP) in

tutorialsarxiv-cs-lg

Shuffling-Aware Optimization for Private Vector Mean Estimation

arXiv:2604.28032v1 Announce Type: new Abstract: We study d-dimensional unbiased mean estimation in the single-message shuffle model, where each user sends a single privatized message and the analyzer

researcharxiv-cs-lg

Signature Kernel Scoring Rule: A Spatio-Temporal Diagnostic for Probabilistic Weather Forecasting

arXiv:2510.19110v2 Announce Type: replace-cross Abstract: Modern weather forecasting has increasingly transitioned from numerical weather prediction (NWP) to data-driven machine learning forecasting t

researcharxiv-cs-lg

Simple Self-Conditioning Adaptation for Masked Diffusion Models

arXiv:2604.26985v1 Announce Type: cross Abstract: Masked diffusion models (MDMs) generate discrete sequences by iterative denoising under an absorbing masking process. In standard masked diffusion, if

Simulating clinical interventions with a generative multimodal model of human physiology

arXiv:2604.27899v1 Announce Type: new Abstract: Understanding how human health changes over time, and why responses to interventions vary between individuals, remains a central challenge in medicine.

Simulating Infant First-Person Sensorimotor Experience via Motion Retargeting from Babies to Humanoids

arXiv:2604.27583v1 Announce Type: cross Abstract: Motion retargeting from humans to human-like artificial agents is becoming increasingly important as humanoid robots grow more capable. However, most

researcharxiv-cs-ro

Simulating Validity: Modal Decoupling in MLLM Generated Feedback on Science Drawings

arXiv:2604.26957v1 Announce Type: cross Abstract: In science education, students frequently construct hand-drawn visual models of scientific phenomena. These drawings rely on a visual structure where

Skills-Coach: A Self-Evolving Skill Optimizer via Training-Free GRPO

model-releasesarxiv-cs-cl

arXiv:2604.27488v1 Announce Type: new Abstract: We introduce Skills-Coach, a novel automated framework designed to significantly enhance the self-evolution of skills within Large Language Model (LLM)-

Softmax-GS: Generalized Gaussians Learning When to Blend or Bound

model-releasesarxiv-cs-cv

arXiv:2604.27437v1 Announce Type: new Abstract: 3D Gaussian Splatting (3D GS) is widely adopted for novel view synthesis due to its high training and rendering efficiency. However, its efficiency reli

Agents

SpaAct: Spatially-Activated Transition Learning with Curriculum Adaptation for Vision-Language Navigation

arXiv:2604.27620v1 Announce Type: new Abstract: Vision-and-Language Navigation (VLN) aims to enable an embodied agent to follow natural-language instructions and navigate to a target location in unsee

agentsarxiv-cs-cv

Applications

Sparse-View 3D Gaussian Splatting in the Wild

arXiv:2604.27422v1 Announce Type: new Abstract: We propose a 3D novel sparse-view synthesis framework for unconstrained real-world scenarios that contain distractors. Unlike existing methods that prim

applicationsarxiv-cs-cv

SpatialGrammar: A Domain-Specific Language for LLM-Based 3D Indoor Scene Generation

arXiv:2604.27555v1 Announce Type: new Abstract: Automatically generating interactive 3D indoor scenes from natural language is crucial for virtual reality, gaming, and embodied AI. However, existing L

Spectral Dynamic Attention Network for Hyperspectral Image Super-Resolution

model-releasesarxiv-cs-cv

arXiv:2604.27326v1 Announce Type: cross Abstract: Hyperspectral image super-resolution is essential for enhancing the spatial fidelity of HSI data, yet existing deep learning methods often struggle wi

SpecVQA: A Benchmark for Spectral Understanding and Visual Question Answering in Scientific Images

arXiv:2604.28039v1 Announce Type: new Abstract: Spectra are a prevalent yet highly information-dense form of scientific imagery, presenting substantial challenges to multimodal large language models (

Splitting Argumentation Frameworks with Collective Attacks and Supports

arXiv:2604.28112v1 Announce Type: new Abstract: This work proposes novel splitting techniques for argumentation formalisms that incorporate supports between defeasible elements. We base our studies on

Splitting Assumption-Based Argumentation Frameworks

arXiv:2604.27964v1 Announce Type: new Abstract: Assumption-Based Argumentation (ABA) is a well-established formalism for modelling and reasoning over debates, with a wide range of applications. Howeve

SQuadGen: Generating Simple Quad Layouts via Chart Distance Fields

arXiv:2604.27329v1 Announce Type: cross Abstract: 3D shapes from scanning, reconstruction, or AI-generated content often lack simple quad mesh layouts -- critical for efficient editing and modeling. E

Stable Behavior, Limited Variation: Persona Validity in LLM Agents for Urban Sentiment Perception

arXiv:2604.28048v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used as proxies for human perception in urban analysis, yet it remains unclear whether persona prompting p

safetyarxiv-cs-cl

Stable but Wrong: An Inference Limit in Galactic Archaeology

model-releasesarxiv-cs-lg

arXiv:2604.27368v1 Announce Type: new Abstract: Statistical inference in observational science typically relies on a fundamental assumption: as sample size increases and uncertainties decrease, the in

State-Dependent Lyapunov Method for Rank-1 Matrix Factorization

model-releasesarxiv-cs-lg

arXiv:2604.26993v1 Announce Type: cross Abstract: We study gradient descent for rank-1 matrix factorization through a certificate-based viewpoint. The central object is a parameterized quadratic certi

Static Program Slicing Using Language Models With Dataflow-Aware Pretraining and Constrained Decoding

arXiv:2604.26961v1 Announce Type: cross Abstract: Static program slicing is a fundamental software engineering technique for isolating code relevant to specific variables. While recent learning-based

Statistical Channel Fingerprint Construction for Massive MIMO: A Unified Tensor Learning Framework

arXiv:2604.27574v1 Announce Type: cross Abstract: Channel fingerprint (CF) is considered a key enabler for facilitating the acquisition of channel state information (CSI) in massive multiple-input mul

Step-level Optimization for Efficient Computer-use Agents

arXiv:2604.27151v1 Announce Type: new Abstract: Computer-use agents provide a promising path toward general software automation because they can interact directly with arbitrary graphical user interfa

Stop Holding Your Breath: CT-Informed Gaussian Splatting for Dynamic Bronchoscopy

arXiv:2604.28179v1 Announce Type: new Abstract: Bronchoscopic navigation relies on registering endoscopic video to a preoperative CT scan, but respiratory motion deforms the airway by 5-20 mm, creatin

Hardware

Strait: Perceiving Priority and Interference in ML Inference Serving

arXiv:2604.28175v1 Announce Type: new Abstract: Machine learning (ML) inference serving systems host deep neural network (DNN) models and schedule incoming inference requests across deployed GPUs. How

hardwarearxiv-cs-lg

Student Classroom Behavior Recognition Based on Improved YOLOv8s

arXiv:2604.27293v1 Announce Type: new Abstract: In classroom teaching, student behavior can reflect their learning state and classroom participation, which is of great significance for teaching qualit

Supercharging Agenda Setting Research: The ParlaCAP Dataset of 28 European Parliaments and a Scalable Multilingual LLM-Based Classification

arXiv:2602.16516v2 Announce Type: replace Abstract: This paper introduces ParlaCAP, a large-scale dataset for analyzing parliamentary agenda setting across Europe, and proposes a cost-effective method

safetyarxiv-cs-cl

Syntactically-guided Information Maintenance in Sentence Comprehension

arXiv:2604.27468v1 Announce Type: new Abstract: Maintaining information in context is essential in successful real-time language comprehension, but maintenance is cognitively costly and can slow proce