Search: “models”

Decoupling Physical Speed from Path Parameterization in Singularity-Free Guiding Vector Fields

arXiv:2609.19726v1 Announce Type: new Abstract: The existing singularity-free guiding vector field (SF-GVF) with an additional virtual coordinate can eliminate singular points (i.e., points where the

researcharxiv-cs-ro

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Safety

DeliveryGym: An RL Environment for Long-Horizon Embodied Agent Planning with Adaptive Curriculum

DGX agent

arXiv:2609.19801v1 Announce Type: new Abstract: Executable environments enable LLM agents to learn from the consequences of their actions. For embodied agents, those consequences extend beyond whether

safetyarxiv-cs-lg

18 Sept 2026

Demystifying Linear Operator Learning for Control Systems

arXiv:2609.19428v1 Announce Type: cross Abstract: This paper proposes a structured approach to learning linear operators for control systems from data. We address both structural and learning-theoreti

Detecting Deceptive Recruitment: A Signal-theoretic Machine Learning Framework for Early Identification of Labour Exploitation

arXiv:2609.20336v1 Announce Type: cross Abstract: Deceptive online job advertisements have emerged as a primary pathway into forced labour, yet systematic detection methods remain underdeveloped due t

applicationsarxiv-cs-lg

Detecting Soft Errors in Parallel Software with LLM-tuned Instruction Duplication

arXiv:2609.19531v1 Announce Type: cross Abstract: We propose PaRID (PaRallel Instruction Duplication), a software-directed soft error detection framework that requires only compile-time effort for mul

Distance to Class Prototypes: Active Learning for Object Detection

arXiv:2609.20248v1 Announce Type: new Abstract: Deploying a deep object detector in a new setting is limited less by architecture than by the cost of annotating data from that setting. Active learning

researcharxiv-cs-cv

Dual-Axis Policy Optimization for LLM Agents: Bayesian Feedback Attribution and Trajectory Mass Normalization

arXiv:2609.19830v1 Announce Type: new Abstract: Reinforcement learning for LLM agents involves two distinct optimization di- mensions: how environment feedback is exploited within a trajectory, and ho

Efficiently Linking Unstructured Data for Multi-step Reasoning

arXiv:2609.19491v1 Announce Type: cross Abstract: Modern LLMs and AI agents increasingly support data engineering workflows that integrate evidence from unstructured sources. Such pipelines typically

agentsarxiv-cs-ai

Emergent interactions lead to collective frustration in robotic matter

arXiv:2507.22148v3 Announce Type: replace-cross Abstract: Artificial intelligence and robotic systems are increasingly deployed as interacting collectives of learning agents. This raises the question

researcharxiv-cs-ro

Execution-Aware Pre-Execution Ranking for Grasp-Conditioned Robotic Placement

arXiv:2609.19946v1 Announce Type: new Abstract: A geometrically valid placement can still be difficult to execute because the selected grasp changes the required end-effector pose, collision geometry,

researcharxiv-cs-ro

From Rollout to Reset: A Graph-Based Harness for Autonomous Long-Horizon Manipulation Evaluation

arXiv:2609.19413v1 Announce Type: cross Abstract: Robot manipulation policies are improving quickly, and real-robot evaluation remains the standard evidence for that progress. It still relies on a hum

From Wizard-of-Oz Human-Robot Dialogue Collection to a Taxonomy of Robot Response Decisions: A Retrospective Analysis of Assistive Pilot Interactions

arXiv:2609.19447v1 Announce Type: new Abstract: Robots that follow natural-language instructions in everyday indoor environments must act on incomplete human utterances. Instructions often omit essent

FunArt: Decoding Functional Structure and Articulation from Generative 3D Latents

arXiv:2609.20673v1 Announce Type: new Abstract: To operate effectively in human environments, robots must identify articulated objects, segment their movable and interactive parts, and estimate their

researcharxiv-cs-cv

Generative Query Suggestion via Intent Coverage and Query-Level Credit Assignment

arXiv:2609.19209v1 Announce Type: new Abstract: Generative query suggestion aims to enhance user engagement by anticipating user intents and recommending relevant follow-up queries. A central challeng

applicationsarxiv-cs-lg

Google is testing a new version of its AI agent CC, pivoting the tool from an individual productivity assistant into a collaborative household management agent (Sarah Perez/TechCrunch)

Sarah Perez / TechCrunch: Google is testing a new version of its AI agent CC, pivoting the tool from an individual productivity assistant into a collaborative household management agent — Google is te

agentstechmeme

GPT-6-Astra in a Navigation Workflow: Behavioral Analysis in Zero-Shot Vision-and-Language Navigation in Continuous Environments

arXiv:2609.20116v1 Announce Type: new Abstract: We study GPT-6-Astra in a zero-shot Vision-and-Language Navigation in Continuous Environments (VLN-CE) system, where it interprets instructions, assesse

agentsarxiv-cs-ro

GR2PO: Group Relative Return Policy Optimization for Continuous Robot Control

arXiv:2609.19850v1 Announce Type: new Abstract: Actor-critic architecture has been widely used in continuous robot control. However, they rely on learning a value network, introducing additional compu

GS-PI: An Optimization-Decoupled Appearance Decomposition Approach for Generating PBR Gaussian Assets

arXiv:2609.19907v1 Announce Type: new Abstract: Gaussian Splatting (GS) excels at novel-view synthesis but encodes baked-in radiance, tightly entangling illumination with geometry and preventing seaml

researcharxiv-cs-cv

HEROIC: Heterogeneous Evidential Reasoning for Open-Vocabulary Identification and Cross-Robot Collaboration

arXiv:2609.19803v1 Announce Type: new Abstract: Multi-agent heterogeneous air-ground robot teams are attractive for open world search, with applications for reconnaissance, urban search and rescue mis

agentsarxiv-cs-ro

Hypernetwork-Parameterized Spatially Adaptive Neural Operators for PDE Learning

arXiv:2609.20309v1 Announce Type: new Abstract: Spatially heterogeneous partial differential equations (PDEs) exhibit location-dependent dynamics arising from variations in geometry and physical coeff

Improving Online Reinforcement Learning via Bidirectional Behavior Prior Distillation

arXiv:2609.20268v1 Announce Type: new Abstract: Online reinforcement learning (RL) algorithms frequently exhibit poor sample efficiency and unstable learning dynamics, stemming from systematic critic

safetyarxiv-cs-lg

It ain’t independent if you are partnering with them and chose the partner.

It ain’t independent if you are partnering with them and chose the partner. We’re partnering with Accenture on independent evaluation of frontier AI—part of our recent commitment to embed evaluators a

safetygary-marcus--x

JointMatch: A Unified Heterogeneous Graph Neural Solver for Large-Scale Ride-Sharing Matching

arXiv:2609.20200v1 Announce Type: new Abstract: Ride-sharing platforms must continuously decide which open requests to bundle into shared trips and which idle vehicles should serve them. The dominant

Kinematics-Grounded Agentic AI for Robotic Additive Manufacturing Process Planning

arXiv:2609.19347v1 Announce Type: cross Abstract: Robotic additive manufacturing (AM) extends material-extrusion printing beyond gantry kinematics but makes process planning robot-dependent. A slicer-

agentsarxiv-cs-ai

Learn Before You Judge: Progressive Knowledge-to-Decision Alignment for Explainable Hateful Meme Detection

arXiv:2609.19778v1 Announce Type: new Abstract: Hateful memes spread abusive content through implicit interactions between images and text, posing serious threats to the safety of online communities.

safetyarxiv-cs-cl

Learning and Transferring Closed-Loop Robot Software

arXiv:2609.19906v1 Announce Type: cross Abstract: Closed-loop robot policies require observation processing, state management, and situation-dependent branching, making them costly to design and tune

Learning Slope-Adaptive Whole-Body Locomotion for Humanoid Robots in Roofing Construction

arXiv:2609.20558v1 Announce Type: new Abstract: Roofing requires workers to coordinate locomotion, balance, and work-related body motions on pitched surfaces, creating a challenging application for hu

LIFD: Anchored Diffusion for 3D-Aware Scene Memory in Robotic Manipulation

arXiv:2609.19796v1 Announce Type: new Abstract: Robotic manipulation under partial observability requires spatial information that extends beyond the current view. Geometry-aware RGB features describe

LLM-as-an-Improver: Turning Verification into Better Candidates

arXiv:2609.19515v1 Announce Type: new Abstract: Verifier-based selection improves LLM performance by generating multiple candidate solutions and using a verifier to select the most promising one. Howe

LLM-Guided Transformation of Non-Critical Driving Scenes into Safety-Critical Scenarios Using Augmented Reality

arXiv:2609.20318v1 Announce Type: cross Abstract: Testing Autonomous Driving Systems (ADS) requires realistic safety-critical scenarios, but collecting such data from real-world driving is costly and

Industry

London-based AI infrastructure startup Nscale files for a US IPO, reports H1 2026 revenue up 1,252% YoY to 140.6M, with a net loss of 1.02B, up from $368.9M (Jordan Novet/CNBC)

Jordan Novet / CNBC: London-based AI infrastructure startup Nscale files for a US IPO, reports H1 2026 revenue up 1,252% YoY to 140.6M, with a net loss of 1.02B, up from $368.9M — Nscale, a cloud prov

industrytechmeme

Meta's personal AI agent Muse climbs to No. 1 among free apps on Apple's US App Store, ahead of ChatGPT; Muse launched on September 8 (Georgia Hennessy/Business Insider)

Georgia Hennessy / Business Insider: Meta's personal AI agent Muse climbs to No. 1 among free apps on Apple's US App Store, ahead of ChatGPT; Muse launched on September 8 — Mark Zuckerberg's ambition

agentstechmeme

MILER: Semantic Mid-Level Representation for Sim-to-Real Reinforcement Learning in Unstructured Autonomous Driving

arXiv:2609.20747v1 Announce Type: cross Abstract: Reinforcement learning constitutes a promising approach owing to its potential for superhuman performance and self-learned policies. However, its appl

safetyarxiv-cs-lg

Local Ai

Not All AI Agents Are Equal: Characterizing Resource and Performance Dynamics

arXiv:2609.19947v1 Announce Type: new Abstract: LLM-based AI agents process user requests through iterative reasoning and tool execution, often involving the invocation of remote LLM APIs with local t

local-aiarxiv-cs-ai

Online Supervised Dimension Reduction with Random Features: Diagnostics and Computational Trade-offs

arXiv:2609.20454v1 Announce Type: cross Abstract: Accurate optimization of a supervised spectral objective need not produce an accurate population subspace or a better predictive representation. We in

Open-vocabulary 3D object detection with promptable segmentation

arXiv:2609.19358v1 Announce Type: new Abstract: Three-dimensional object detection for autonomous driving is dominated by detectors trained on large corpora of human-annotated 3D boxes. Such a detecto

agentsarxiv-cs-cv

OPTED: On-Policy Fine-Tuning for End-to-End Driving using a Render-Free Teacher

arXiv:2609.20756v1 Announce Type: cross Abstract: As scaling pre-training data alone yields diminishing returns, post-training is becoming increasingly important across physical AI domains such as aut

safetyarxiv-cs-cv

Optimal Transport Metric Learning for Feature Alignment in Partially Supervised Segmentation

arXiv:2609.19176v1 Announce Type: cross Abstract: Multi-organ segmentation is often challenged by partially annotated datasets and domain shifts across different imaging sources. To address these limi

ParticleSplat: Self-supervised Object-centric Latent Particle Splatting

arXiv:2609.19463v1 Announce Type: new Abstract: We present ParticleSplat, a self-supervised object-centric learning method that decomposes scenes into a set of latent ''particles'' representing semant

applicationsarxiv-cs-cv

Perturbing the Phase: Analyzing Adversarial Robustness of Complex-Valued Neural Networks

arXiv:2602.06577v2 Announce Type: replace-cross Abstract: Complex-valued neural networks (CVNNs) are rising in popularity for all kinds of applications. To safely use CVNNs in practice, analyzing thei

PhyRestore: Physics-Structured Latent-Factor Restoration

arXiv:2609.19776v1 Announce Type: new Abstract: Estimating temporal soil-loss change is challenging when physically meaningful input factors are noisy or corrupted, particularly because substantial ch

PIVOT: Perception-aware Independent Viewpoint Online Optimization

arXiv:2609.19510v1 Announce Type: new Abstract: A fundamental assumption in robotic perception is that the sensor's field of view (FoV) is fixed relative to the robot body. Motion-decoupled sensors, s

applicationsarxiv-cs-ro

Pose-aware Legged Robot Semantic Exploration with Omnidirectional Perception in Confined Unknown Environments

arXiv:2609.19460v1 Announce Type: new Abstract: Semantic exploration in confined environments requires both environment mapping and detailed observation of target objects. For ground robots, limited s

applicationsarxiv-cs-ro

Q&A on Any Spreadsheet Requires Interpreting Its Grid Structure

arXiv:2609.20732v1 Announce Type: new Abstract: Semantic cell annotation improves chunking interpretability for spreadsheets in LLM-driven RAG systems, aiding answer generation through enriched contex

Local Ai

QoS-Aware Federated Learning for Multimodal In-Cabin Interaction in Smart Vehicles

arXiv:2609.20123v1 Announce Type: new Abstract: Modern smart vehicles leverage multimodal sensors, ranging from high-bandwidth vision systems to low-rate physiological monitors, to provide personalize

local-aiarxiv-cs-lg

Radio Frequency Detection and Classification of Microplastics in Water

arXiv:2609.20507v1 Announce Type: new Abstract: Micro- and nano-plastic particles (MPs/NPs) are ubiquitous environmental contaminants whose increasing abundance and potential health impacts have creat

Reading Emotions in the Token Space: Discriminative Adaptation of SpeechLLMs for Emotion Recognition

arXiv:2609.20081v1 Announce Type: cross Abstract: SpeechLLMs have shown strong potential for emotion recognition, yet they read the predicted emotion off a generative decoder not suited for classifica

ReShoot: Generative Visual Domain Randomization of Recorded Robot Demonstrations for Visuomotor Policy Learning

arXiv:2609.19661v1 Announce Type: new Abstract: Imitation-learned robot policies are frequently overfit to the visual conditions present in their training demonstrations. Consequently, variations in o