Search: “deployment”

Skill Profiling with Attributable Reasoning (SPAR): A Wearable Analysis System for Boxing

arXiv:2609.30753v1 Announce Type: cross Abstract: A punch is a ballistic, full-body action driven by a kinetic chain running from the legs through the trunk to the arm, where a small sequencing error

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Staged Depth Training: A Representation Curriculum for PINNs

DGX agent

arXiv:2609.30299v1 Announce Type: new Abstract: Representation quality is a central determinant of PINNs' performance, yet standard training leaves representations to emerge implicitly while fitting t

local-aiarxiv-cs-lg

28 Sept 2026

Structured-Diffuser: Diffusion with Task-Conditioned Structured Priors for Motion Planning

arXiv:2509.25685v3 Announce Type: replace Abstract: We propose Structured-Diffuser, a diffusion planner that embeds task and motion structure directly into the noise model. Unlike standard diffusion-b

researcharxiv-cs-ro

The Price of Thought: Does Test-Time Reasoning Pay in LLM Trading?

arXiv:2609.30705v1 Announce Type: new Abstract: While inference-time reasoning in large language models (LLMs) promises better decision making, its higher computational cost may not yield better econo

The Uncontrolled Variable: Vision-Language Refusal Is Conditioned on the Image-Attachment Interface, and Not Robust to Irrelevant Image Properties

arXiv:2609.26174v2 Announce Type: replace-cross Abstract: We show that aligned vision-language models also condition refusal on a property of a request's form: whether an image is attached, holding ev

safetyarxiv-cs-ai

Towards Understanding LLM-Based Log Anomaly Detection: An Empirical Study of Performance, Efficiency, and Robustness

arXiv:2609.31371v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated promising performance in log anomaly detection, yet how their adaptation strategies, architectures, and d

Towards Whole-Study Screening for Congenital Heart Disease in Fetal Ultrasound Using Multiple Instance Learning

arXiv:2609.31376v1 Announce Type: cross Abstract: Congenital heart disease (CHD) is the most common birth defect, yet a large fraction of cases remain undetected on prenatal ultrasound, in part becaus

Hardware

TRACKGRAPH: Online Open-Vocabulary 3D Scene Graphs via Image-Space Tracking

arXiv:2609.31005v1 Announce Type: new Abstract: Open-vocabulary 3D maps enable robots to reason about previously unknown environments using natural language. However, existing systems typically segmen

hardwarearxiv-cs-cv

Training-Free Bottleneck Width Planning for Convolutional Autoencoders

model-releasesarxiv-cs-cv

arXiv:2609.30755v1 Announce Type: new Abstract: Multiscale Spectral Rate-Distortion (MS-SRD) estimates the bottleneck channels required at user-supplied spatial cuts from training images and a normali

VLaRL: Augmenting Vision-Language-Action Models with Simulation-Trained Latent-Conditioned Residual RL

arXiv:2609.30868v1 Announce Type: new Abstract: Vision-language-action (VLA) models provide broad, instruction-conditioned manipulation behaviors, but their physical execution can remain imprecise dur

safetyarxiv-cs-ro

Where a Model Sends Its Own Repeated Token

arXiv:2609.31181v1 Announce Type: new Abstract: Black-box model identification works by scoring a model's response to natural-language prompts. One line of work feeds models a degenerate input -- thei

researcharxiv-cs-cl

A Living Benchmark for Information Retrieval from Electronic Health Records

arXiv:2609.30205v1 Announce Type: new Abstract: Large language model (LLM)-based clinical assistants are increasingly being integrated into electronic health record (EHR) systems, transforming how cli

A Procedure for Classifying Attachments and Affective Social Bonds in Human-Robot Dyads

arXiv:2609.29063v1 Announce Type: cross Abstract: Human-robot interaction (HRI) claims that people form attachments and social bonds with artificial agents, yet the terms are often applied without the

applicationsarxiv-cs-ro

A Support-Enhanced Granular-Jamming Gripper for RL-based Grasping with Continuum Manipulators

arXiv:2609.29093v1 Announce Type: new Abstract: Continuum manipulators provide dexterous motion in confined spaces, but structural compliance, hysteresis, and load-dependent deformation leave residual

applicationsarxiv-cs-ro

AdaHVLA: Adaptive Harnesses for Long-Horizon Vision-Language-Action Execution

arXiv:2609.29204v1 Announce Type: new Abstract: Vision-language-action (VLA) models offer strong local control and instruction following but often struggle with long-horizon tasks requiring persistent

agentsarxiv-cs-ro

ALOE: Semantically Addressed Low-Rank Operators for Knowledge Editing

arXiv:2609.29269v1 Announce Type: new Abstract: Knowledge editing changes what a model knows by modifying parameters so that a requested fact updates while unrelated behavior is preserved. This is usu

researcharxiv-cs-ai

An Empirical Study of VLM Pipelines for Long-Document QA

arXiv:2609.29933v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are increasingly used for long-document processing, where the inputs combine text with charts, tables, figures, and comp

agentsarxiv-cs-ai

Auditability Is Not One Property: Rule Overlap, Behavioural Agreement, and Composition in Reinforcement Learning

arXiv:2609.28581v1 Announce Type: cross Abstract: Reinforcement-learning (RL) policies are often distributed as opaque neural checkpoints, while training logs show that a run occurred without explaini

safetyarxiv-cs-ai

Automated Regulatory Compliance Question Answering in Financial Services with Domain-Adapted Retrieval-Augmented Generation

arXiv:2609.30009v1 Announce Type: cross Abstract: Financial institutions operate under dense, frequently amended rulebooks, and answering a compliance question correctly requires not only fluency but

Baszta: Data-Centric Fine-Tuning of a Polish Multi-Label Safety Classifier

arXiv:2609.29266v1 Announce Type: new Abstract: We develop a multi-label Polish content-safety classifier by fine-tuning allegro/herbert-base-cased (124M) across five categories (hate, vulgarity, sexu

Benchmarking and Domain Adaptation of Automatic Speech Recognition (ASR) for Adolescent Health Communication in Ghanaian Languages

arXiv:2609.29798v1 Announce Type: cross Abstract: This paper presents an end-to-end study of automatic speech recognition (ASR) for adolescent health communication in three Ghanaian languages (Twi, Da

Claim-Gated Source-Risk Auditing for Generative Search

arXiv:2609.29145v1 Announce Type: new Abstract: A generative search answer can cite a supported passage yet omit a source relationship that changes its interpretation. We specify a claim-gated audit o

researcharxiv-cs-ai

ComplexSync: High-Fidelity and Real-Time Lip Sync in Complex Scenarios

model-releasesarxiv-cs-cv

arXiv:2609.29225v1 Announce Type: new Abstract: Lip synchronization aims to generate visual lip dynamics that align precisely with speech audio. Despite the high generation quality of diffusion models

Continuous Online Fault Detection for Mobile Robots via Adaptive Edge Models

arXiv:2609.29194v1 Announce Type: cross Abstract: Mobile robots require robust, real-time fault detection capable of continuous adaptation on constrained edge hardware. While deep time-series models e

Dense Coverage, Sparse Refinement: Byte-Constrained Cooperative Perception

arXiv:2609.29456v1 Announce Type: new Abstract: Collaborative perception improves autonomous perception by sharing intermediate Bird's-Eye-View (BEV) features across connected agents, but dense featur

agentsarxiv-cs-cv

Design and Evaluation of LLM Chaining-Based Task Planning for General Purpose Service Robots

arXiv:2609.29043v1 Announce Type: cross Abstract: General Purpose Service Robot (GPSR) tasks, as defined in the RoboCup@Home benchmark, require robots to interpret diverse natural language commands an

ENDOPROMPT: Victim-Side Pseudo-References for Utility Degradation

arXiv:2609.29948v1 Announce Type: new Abstract: Prompt injection can degrade benign task performance without eliciting harmful content. Yet many attack objectives depend on task labels or predefined t

From Target Selection to Digging: A Learning-Based Framework for Continuous Autonomous Excavation

arXiv:2609.29750v1 Announce Type: new Abstract: Repeated excavation continuously reshapes pile geometry, requiring an autonomous excavator to adapt its digging targets and coordinate motion across suc

safetyarxiv-cs-ro

Functional Architecture of European Electricity Trading Markets: Requirements for AI Supported Trading Systems under Regulatory Constraints

arXiv:2609.29108v1 Announce Type: new Abstract: European electricity trading in the EU operates as a constrained multi-layer system in which legal design, exchange microstructure, and network physics

applicationsarxiv-cs-ai

GCUL: Ambiguity Identification in Text Emotion Classification via Cluster-Guided Learning

arXiv:2609.29327v1 Announce Type: cross Abstract: Selective classification enables a model to abstain from predictions on uncertain instances, but existing approaches typically reject them through con

Hardware

GHOST-Q: Towards Studying Grounding Hallucinations Overlooked Under Same-score TradeOffs in Quantized VLMS

arXiv:2609.29999v1 Announce Type: cross Abstract: Post-training quantization of vision--language models (VLMs) is typically assessed through aggregate task accuracy and memory savings, but preserving

hardwarearxiv-cs-ai

Graph-Based Inference and Topology-Aware Multi-Agent Reinforcement Learning for Large-Scale Railway Network Management

arXiv:2609.30150v1 Announce Type: new Abstract: Modern infrastructure asset management constitutes a complex sequential decision-making problem, characterized by long planning horizons and system-leve

agentsarxiv-cs-lg

GridSFM: A Foundation Model for Solving AC Optimal Power Flow

arXiv:2609.30173v1 Announce Type: cross Abstract: We introduce GridSFM, a framework that combines a pretrained foundation model across grid topologies with physics-informed fine-tuning for solving AC

HelloWorld: Towards Practical Applications of Generative Driving World Models

arXiv:2609.28931v1 Announce Type: new Abstract: Driving world models provide a promising route toward scalable counterfactual data generation and interactive simulation beyond recorded driving logs. R

Image Fidelity is Not Field Fidelity: Joint Thermodynamic Reconstruction and Error Localization in Neural Tomography

arXiv:2609.28868v1 Announce Type: new Abstract: Neural fields for scientific tomography are optimized from 2D images, but the actual quantity of interest is often a latent 3D physical field. Because t

local-aiarxiv-cs-lg

M3GD: Multi-Modal Multi-View Geometric Diffusion for Camera--LiDAR Novel View Synthesis

arXiv:2609.30056v1 Announce Type: cross Abstract: Robotic novel view synthesis (NVS) must recover both visual appearance and metric 3D structure, yet most generative NVS methods rely only on images, o

applicationsarxiv-cs-cv

MDE-VIO: Enhancing Visual-Inertial Odometry Using Learned Depth Priors

arXiv:2602.11323v2 Announce Type: replace Abstract: Traditional monocular Visual-Inertial Odometry (VIO) systems struggle in low-texture environments where sparse visual features are insufficient for

MILO: Efficient Many-shot In-Context Learning with Block-wise Low-rank Compression

arXiv:2609.29913v1 Announce Type: new Abstract: Many-shot in-context learning (ICL) enables large language models (LLMs) to adapt to complex tasks by conditioning on thousands of demonstration example

local-aiarxiv-cs-cl

Monitoring Urban Traffic Dynamics at Fine Spatiotemporal Resolution Using Distributed Acoustic Sensing and Deep Learning

arXiv:2609.28793v1 Announce Type: new Abstract: Mapping the distribution of traffic dynamics at high spatiotemporal resolution is a fundamental question in transportation research. Distributed acousti

Morphometric Imitation: From Morphology and Contact Aware Hand Retargeting to Sim-to-Real Visuomotor Policy

arXiv:2609.28660v1 Announce Type: new Abstract: Human hand-object interactions (HOIs) provide a rich source of demonstrations for dexterous manipulation, but learning directly from them presents chall

safetyarxiv-cs-ro

MoSign: Challenge-Response Motion-Watermark Authentication for Anonymous Virtual-Reality Users

arXiv:2609.29603v1 Announce Type: cross Abstract: Social virtual reality (VR) creates a paradox. A user's body motion is a high-entropy biometric: head and hand trajectories alone re-identify users am

Hardware

Multi-Agent Orchestration of 3GPP Channel Estimators

arXiv:2609.29044v1 Announce Type: cross Abstract: Pilot-aided channel estimation is a decisive block in orthogonal frequency-division multiplexing (OFDM) receivers for both 5G New Radio (5G-NR) and Lo

hardwarearxiv-cs-ai

Tutorials

Neuro-symbolic AI for Industrial Configuration

arXiv:2609.29947v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown impressive performance on a wide range of generative tasks. Yet their probabilistic nature makes them, in isolat

tutorialsarxiv-cs-ai

Nuclear Norm-Regularized Bayesian Matrix Completion

arXiv:2609.30078v1 Announce Type: cross Abstract: Matrix completion, the problem of estimating missing entries in a matrix from noisily observed ones, underlies a diverse array of problems such as rec

OncoVision: Integrating Mammography and Clinical Data through Attention-Driven Multimodal AI for Enhanced Breast Cancer Diagnosis

arXiv:2511.19667v2 Announce Type: replace Abstract: OncoVision is a privileged-information training framework that uses mammography images and clinical features during training and performs inference

Optimal Recovery Meets Bayesian Learning: Where Worst-Case Bounds Pay Off

arXiv:2609.29622v1 Announce Type: cross Abstract: Worst-case Optimal Recovery (OR) and Bayesian learning describe the same Gaussian-quadratic-Hilbert problems in two vocabularies. We sharpen the corre

Outcome-Sensitive Motion Search for Impact-Aware Dexterous Catching

arXiv:2609.29020v1 Announce Type: new Abstract: Skilled humans can catch fast-moving objects softly by coordinating interception, velocity matching, and follow-through to mitigate impact. Learning suc

local-aiarxiv-cs-ro

Paging the Experts: A Reproducible Characterization of Flash-Backed MoE Inference on iPhone

arXiv:2609.29032v1 Announce Type: cross Abstract: Sparse activation reduces mixture-of-experts computation without eliminating the need to store all experts. We present Routide, a Swift/MLX runtime th

local-aiarxiv-cs-lg