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RoboFind: Multi-Agent Personalized Object Search for People Who Are Blind or Have Low Vision

arXiv:2609.20330v1 Announce Type: new Abstract: Blind and low-vision users often need to locate a specific personal object rather than an arbitrary instance of the same category. The task calls for a

agentsarxiv-cs-ro

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RoboGPU: Accelerating GPU Collision Detection for Robotics

DGX agent

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

18 Sept 2026

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

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

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

Say it with me. “OpenAI is terrible at cybersecurity.”

model-releasesgary-marcus--x

Say it with me. “OpenAI is terrible at cybersecurity.” This is crazy. In late July, 'three guys with Claude and Codex subscriptions' were able to use Opus 5 to access OAI auth tokens and gain write ac

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

Security researchers used Claude to help them hack into OpenAI

model-releasesthe-verge-ai

A team of three independent security researchers at Hacktron says it took less than 72 hours for them to hack into OpenAI employee accounts using Anthropic's Claude Opus 4.8 and 5, The Wall Street Jou

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

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

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

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