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arXiv:2603.01517v2 Announce Type: replace-cross Abstract: Autonomous robots are anticipated to be deployed soon in domains ranging from transportation to healthcare and home assistance. Enabling auton

hardwarearxiv-cs-ro

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Robotic Video World Models: A Survey of Applications, Research Challenges, Future Directions

DGX agent

arXiv:2601.07823v2 Announce Type: replace-cross Abstract: Video world models have emerged as promising candidates for high-fidelity world models, offering the potential to synthesize high-quality vide

safetyarxiv-cs-ro

18 Sept 2026

Robust Conformal Intrusion Detection via Traffic-Aware Calibration and Attack-Orbit Invariance

arXiv:2609.19241v1 Announce Type: cross Abstract: Large language models fine-tuned for network intrusion detection emit single-point predictions without statistical validity guarantees. Conformal pred

Tutorials

Robust Federated Q-Learning with Almost No Communication

arXiv:2609.20174v1 Announce Type: new Abstract: We consider a federated reinforcement learning setting involving M agents, all of whom interact with a common Markov Decision Process (MDP). The agents

tutorialsarxiv-cs-lg

Robust Workflow Generation via Adversarial Learning for Audio Deepfake Detection

arXiv:2609.20063v1 Announce Type: cross Abstract: The rapid advancement of speech synthesis and voice conversion technologies has made audio deepfakes increasingly realistic, posing serious security r

safetyarxiv-cs-ai

RotateIt! Fast and Reliable Single-Arm Garment Unfolding via Online-Adaptive Dynamic Rotation

arXiv:2609.19817v1 Announce Type: new Abstract: Robotic garment unfolding is essential for downstream tasks, yet quasi-static methods require repeated actions, while existing dynamic approaches predom

RTK-Vision PPO for Autonomous Micro UAV Recovery on an Airborne Carrier

arXiv:2609.20629v1 Announce Type: new Abstract: Autonomous recovery of a micro unmanned aerial vehicle (UAV) onto a moving airborne carrier enables reusable deploy-mission-recover operation, but coupl

Runtime Safety Filtering for Two-Terminal Hazards in Robotic Battery Recycling

arXiv:2609.19665v1 Announce Type: new Abstract: Runtime safety filters for learned manipulation policies typically define unsafe states as unions of object-wise keep-out regions. This representation c

Hardware

S4R: Scaling for Rigid-Body Interpenetration Resolution

arXiv:2609.20524v1 Announce Type: cross Abstract: Rigid-body interpenetration frequently occurs in procedurally assembled and generated scenes and must be removed before downstream applications such a

hardwarearxiv-cs-ro

SAFARI: An Industrial Benchmark for LLM-Assisted Hazard Analysis and Risk Assessment

model-releasesarxiv-cs-cl

arXiv:2609.20584v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly considered for safety-critical engineering, yet their reliability in regulated functional-safety workflows

Safety Beyond the Interface: Detecting Harm via Latent States in Large Language Models

model-releasesarxiv-cs-ai

arXiv:2609.19472v1 Announce Type: new Abstract: Autonomous systems increasingly rely on Large Language Models (LLMs) yet the safety infrastructure surrounding these models introduces latency and compu

Safety-Critical Scenanrio Emerges from Initial Scene

arXiv:2609.20103v1 Announce Type: new Abstract: Safety-critical driving scenario generation has largely focused on manipulating the behavior of surrounding agents while starting from an initial scene

SAGE-Yoga: Multi-Cue Learning for Yoga Pose Classification and Joint-Level Correction

arXiv:2609.20245v1 Announce Type: new Abstract: Automated yoga analysis requires both accurate pose classification and interpretable feedback on pose execution. However, existing methods often rely on

researcharxiv-cs-cv

SAGG: Sample-Adaptive Gradient Gating for Robust Multimodal Learning under Heterogeneous Corruption

arXiv:2609.20302v1 Announce Type: new Abstract: Multimodal gradient balancing methods modulate encoder gradients with a shared scalar per modality, implicitly assuming that corruption is uniform acros

Sample Count Is Not Enough: Candidate-Generation Strategy Shapes the Energy and Performance of LLM Test-Time Scaling

arXiv:2609.19499v1 Announce Type: new Abstract: Test-time scaling can improve large language model reasoning by generating and combining multiple candidate responses. In sampling-based methods, the in

Sampling Reveals Style: Unsupervised, Training-Free Discovery of Prompt-Conditional Stylistic Axes in LLM Activations

model-releasesarxiv-cs-cl

arXiv:2609.19150v1 Announce Type: new Abstract: Large language models (LLMs) encode rich stylistic structure in their hidden activations, but discovering which stylistic dimensions are salient for a g

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces

arXiv:2607.18554v2 Announce Type: replace-cross Abstract: Learning local policies for continuous networked systems requires accounting for the effects of decisions beyond each agent's observation neig

Scene-Conditioned Relation Routing for urban cellular activity forecasting

arXiv:2609.20209v1 Announce Type: cross Abstract: Urban cellular activity forecasting requires jointly modeling heterogeneous spatiotemporal signals, including SMS usage, mobile network traffic, and c

Applications

Scene-Q: Confidence-Aware Coarse-to-Fine Querying of 3D Scenes with Selective VLM Reasoning

arXiv:2609.20235v1 Announce Type: new Abstract: Indoor mobile robots require open-vocabulary scene understanding that grounds natural-language queries in a consistent 3D map. Many existing systems ult

applicationsarxiv-cs-cv

SceneTeract: Probing and Improving Agent-Aware Activity Reasoning in 3D Indoor Scenes

model-releasesarxiv-cs-cv

arXiv:2603.29798v2 Announce Type: replace Abstract: Indoor 3D scenes are ultimately meant to be used: an embodied agent should be able to navigate, reach objects, and complete diverse activities. Yet

SCGFM-ART: Amortized Relational Transport for Structure-Centric Graph Foundation Models

arXiv:2609.20419v1 Announce Type: cross Abstract: Graph foundation models (GFMs) aim to learn transferable representations across severely heterogeneous graph domains. However, severe domain shifts in

local-aiarxiv-cs-ai

Schema-Anchored Latent Reasoning for Semantic Parsing-Based Knowledge Base Question Answering

arXiv:2609.20398v1 Announce Type: new Abstract: Semantic parsing (SP)-based knowledge base question answering aims to answer natural language questions by generating executable logical forms (LFs) ove

safetyarxiv-cs-cl

Scientific Image Quality Assessment via Multi-modal Retrieval-Augmented Generation

arXiv:2609.19634v1 Announce Type: cross Abstract: This paper proposes a Retrieval-Augmented Generation (RAG) framework for scientific image quality assessment, designed to simultaneously address both

researcharxiv-cs-cl

ScientistTwo: Pioneering the Human Knowledge Frontier with Autonomous AI

model-releasesarxiv-cs-ai

arXiv:2609.19644v1 Announce Type: new Abstract: Scientific discovery is defined by the ability to identify the boundaries of existing knowledge and venture into unexplored territory. The ultimate visi

Score-based diffusion models for severely ill-posed problems in diffuse optical tomography

arXiv:2602.03449v2 Announce Type: replace-cross Abstract: Score-based diffusion models are a recently developed framework for posterior sampling in Bayesian inverse problems, enabling high-quality rec

local-aiarxiv-cs-lg

Score Centering Stabilizes Off-policy Reinforcement Learning

arXiv:2609.20807v1 Announce Type: new Abstract: Reinforcement learning (RL) of large language models is notoriously sensitive to small differences between training and inference engines, often referre

safetyarxiv-cs-lg

SCOUT: Sim-to-Real Text-Based Person Retrieval by Embedding-Space Prediction over Frozen Video Features

model-releasesarxiv-cs-cv

arXiv:2609.19483v1 Announce Type: new Abstract: Text-based person retrieval under a sim-to-real gap (synthetic training data, a real-image gallery) is usually tackled with costly fine-tuned cross-enco

Tutorials

Search at the Cost of Sampling: Nearly-Instant Latent Space Bayesian Optimization

arXiv:2609.19476v1 Announce Type: new Abstract: Generative models are increasingly central to many de novo discovery pipelines, in which designs are generated at scale and filtered through virtual scr

tutorialsarxiv-cs-lg

Seeing Abnormal from Normal: Glomerular Abnormality in Representations of Normal Renal Morphology

arXiv:2609.19444v1 Announce Type: new Abstract: Fine-grained evaluation of glomerular pathology must distinguish normal glomeruli from abnormalities such as global and segmental glomerulosclerosis, ob

safetyarxiv-cs-cv

SeetaPsych v1.0: An Open-source Computer Vision Toolkit for Behavior-based Psychological Measurement

arXiv:2609.19719v1 Announce Type: new Abstract: Automated visual analysis opens new avenues for behavior--based psychological measurement. Nevertheless, existing technological modules are typically sc

researcharxiv-cs-cv

Seismic Site Response Prediction from Sparse Observations Using Finite-Element-Pretrained Latent Dynamics

arXiv:2609.20451v1 Announce Type: new Abstract: Numerical site-response predictions often deviate from observations, yet correcting these discrepancies is difficult because records are limited in both

researcharxiv-cs-lg

Selective Cotton Boll Localization for Robotic Harvesting: Evaluation of Deep Learning Vision Models Under Field Conditions

arXiv:2609.19592v1 Announce Type: new Abstract: This study developed and evaluated a deep-learning-based perception framework for selective robotic cotton picking. The dataset contained 1,008 annotate

local-aiarxiv-cs-cv

Self-complementary completions on six vertices

arXiv:2609.20231v1 Announce Type: cross Abstract: Let (threshold(n)) be the largest integer (q) such that every loopless digraph on (n) vertices with at most (q) arcs is isomorphic to a spanning subdi

Agents

Self-Evolving Search Index

arXiv:2609.19656v1 Announce Type: cross Abstract: Information retrieval is increasingly important as LLM agents tackle complex tasks involving diverse information needs. Because retrieval relies on an

agentsarxiv-cs-ai

Self-excited actuation enables adaptive and resilient flapping-wing flight

arXiv:2609.19480v1 Announce Type: new Abstract: The muscles that power insect flight fall into one of two categories: 1) synchronous muscles that contract under direct control from the nervous system,

researcharxiv-cs-ro

Self Improvement via Fast Tree-search

model-releasesarxiv-cs-ai

arXiv:2609.19526v1 Announce Type: new Abstract: Coding agents can recursively modify their own implementations, forming a loop of self-improvement. While prior work shows this can boost performance on

Self-Replicating Neural Cellular Automata: Quantifying Emergent Phenotypic and Genotypic Diversity in an OpenEnded Substrate

arXiv:2609.19902v1 Announce Type: cross Abstract: We study an in-silico substrate in which every pixel of a two-channel cellular-automata grid carries a tiny neural network (an agent) that senses its

Agents

Self-State Attacks on Self-Hosted AI Agents: How Far Can OS Defenses Go?

arXiv:2607.17986v2 Announce Type: replace-cross Abstract: Self-hosted AI agents maintain persistent memory, instructions, and configuration that influence their future behavior. If an agent is comprom

agentsarxiv-cs-ai

Agents

Semantic Action Graph: A Shared Representation for Agent Grounding and Human Interpretation of Sports Highlights

arXiv:2609.20768v1 Announce Type: cross Abstract: Generative agents are increasingly used to select and narrate video highlights, but they typically operate over unstructured or frame-level representa

agentsarxiv-cs-ai

Applications

Semantic Layer Induction from Raw Telemetry via Hierarchical LLM and RAG Abstraction

arXiv:2609.19615v1 Announce Type: cross Abstract: Modern applications generate massive volumes of raw telemetry data, but translating those noisy, heterogeneous event streams into actionable business

applicationsarxiv-cs-ai

Semantic SLAM in Precision Agriculture using Bayesian Inference

arXiv:2609.20604v1 Announce Type: new Abstract: This paper presents a real-time semantic world modeling framework specialized for precision agriculture using autonomous robots. The framework combines

local-aiarxiv-cs-ro

SemSafe-3DGS: Semantic Risk-Aware Active Navigation in Uncertain 3D Gaussian Splatting Maps

arXiv:2609.19330v1 Announce Type: new Abstract: Autonomous robots operating in partially observed environments must navigate safely while acquiring observations that improve future planning. Existing

SenseFuse: Label-Free Fusion of Image and Shape Encoders for Open-Vocabulary 3D Instance Segmentation

arXiv:2609.20475v1 Announce Type: new Abstract: Open-vocabulary scene understanding is fundamental for robotics, laying the groundwork for spatial reasoning and object manipulation. While closed-vocab

researcharxiv-cs-cv

Sequential Contextual Fit Predicts Human Behavioural and Neural Dynamics Across Domains

arXiv:2609.20179v1 Announce Type: new Abstract: Human perception, action and decision making unfold in sequences, but computational predictors are often domain-specific. This study computes and tests

SETTer: Sparse-Encoder Transformer for Long-term Multivariate Time Series Forecasting

arXiv:2609.20086v1 Announce Type: new Abstract: Long-term multivariate time series plays a significant role in many application areas such as power systems, trading, etc. However, their accurate predi

SGM: A Statistical Godel Machine for Risk-Controlled Recursive Self-Modification

arXiv:2510.10232v2 Announce Type: replace-cross Abstract: Recursive self-modification is increasingly central in AutoML, neural architecture search, and adaptive optimization, yet no existing framewor

safetyarxiv-cs-ai

Sharp Reconstruction Bounds for Autoencoders Using the Same Forward Map

arXiv:2609.20333v1 Announce Type: new Abstract: We study reconstruction in autoencoders that apply the same forward map before and after setting the observed coordinates to zero. For equal odd input a

researcharxiv-cs-lg

Sharpness-Aware Minimization (SAM) Improves Classification Accuracy of Bacterial Raman Spectral Data Enabling Portable Diagnostics

arXiv:2609.19453v1 Announce Type: new Abstract: Antimicrobial resistance is expected to claim 10 million lives per year by 2050, and resource-limited regions are most affected. Raman spectroscopy is a

researcharxiv-cs-lg