Search: “deployment”

SpaceDiffusion: Over-the-Orbit Diffusion for Space Generate-and-Forward Communications

arXiv:2609.20899v1 Announce Type: cross Abstract: Satellite communications are an essential component of sixth-generation (6G) mobile networks, which provide ubiquitous connectivity for global service

safetyarxiv-cs-ai

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SpecQuant: Speculative Decoding with Multi-Parent Quantization for Adaptive LLM Inference

DGX agent

arXiv:2609.21704v1 Announce Type: new Abstract: Running large language models (LLMs) locally continues to be limited by restrictions of compute and memory on consumer hardware. The popular acceleratio

local-aiarxiv-cs-lg

21 Sept 2026

Transferable knowledge graphs with executable learned operators for algorithm design

arXiv:2603.27922v2 Announce Type: replace Abstract: Procedural knowledge in algorithm design is embedded in source code and rebuilt for each new domain. We introduce Generative Executable Algorithm Kn

local-aiarxiv-cs-ai

Uncertainty-driven training for three-dimensional calibrated lung nodule classification

arXiv:2609.20905v1 Announce Type: cross Abstract: In this work, we present an uncertainty-driven training framework for three-dimensional computed tomography (CT) lung nodule classification, where val

WM-VS: Progress-Aligned World Models for Closed-Loop Visual Servoing

arXiv:2609.20892v1 Announce Type: cross Abstract: Closed-loop visual servoing requires predictions that indicate whether an action reduces task error, not only whether the action is plausible. We call

ZYT-World: A Real-Time Controllable World Model for Closed-Loop Autonomous-Driving Simulation

arXiv:2609.21712v1 Announce Type: new Abstract: Generative world models offer controllable and repeatable closed-loop simulation for end-to-end and vision-language-action driving policies, but product

A Multi-Modal Generative Model for Tomato Disease Leaves Understanding

arXiv:2609.19555v1 Announce Type: cross Abstract: Artificial intelligence for plant disease analysis has advanced from task-specific classifiers to multi-modal models capable of jointly interpreting v

researcharxiv-cs-ai

A Policy Profile for Croissant: Refusal as a Property of the Dataset

arXiv:2609.19640v1 Announce Type: new Abstract: Croissant is the de facto machine-readable descriptor for ML datasets: JSON-LD over schema.org. Since version 1.1 it also carries data use conditions, r

A Simulation Platform for AUV Fault Recovery: Exploring LLM-Based Diagnostic Strategies

arXiv:2609.20620v1 Announce Type: cross Abstract: Autonomous underwater vehicles (AUVs) operating beyond reliable communications must recover from failures without human intervention. We investigate a

local-aiarxiv-cs-ai

A Unified Evaluation Framework for Trustworthy Large Language Models, Agentic AI, and Multimodal Systems

arXiv:2609.19524v1 Announce Type: new Abstract: Benchmark scores alone provide an incomplete basis for assessing the trustworthiness of modern artificial intelligence systems. Large language models (L

Accelerating Visual Policy Learning with Sampling-Based Model Predictive Control

arXiv:2609.20575v1 Announce Type: cross Abstract: Learning visual policies for locomotion and manipulation requires coordinating contact with the environment and can incur substantial computation and

local-aiarxiv-cs-ai

Affective Shared Autonomy: Temporal Affect Dynamics and Subjective Evaluation in Bimanual Teleoperation Tasks

model-releasesarxiv-cs-ro

arXiv:2609.19802v1 Announce Type: new Abstract: Physical teleoperation integrates human cognitive flexibility with robotic precision, yet demanding manipulation tasks frequently induce severe cognitiv

Agile-WAM: An Agile Tactile World Action Model for Contact-Rich Robot Control

arXiv:2609.20761v1 Announce Type: cross Abstract: World Action Models (WAMs) advance beyond conventional visuomotor policies by jointly predicting future world states and robot actions, enabling the p

AI Smart Glasses for Wearable Intelligence: From Egocentric Sensing to Agentic Personalization

arXiv:2609.19793v1 Announce Type: new Abstract: Recent advances in artificial intelligence (AI) are reshaping smart glasses from egocentric capture and display devices into platforms for wearable inte

agentsarxiv-cs-cv

AntiGrounding: Executable Robot Trajectories as Visual Prompts for VLM-Guided Manipulation

arXiv:2506.12374v3 Announce Type: replace-cross Abstract: Natural-language manipulation instructions specify the task goal but leave the underlying robot trajectory unspecified. We present AntiGroundi

safetyarxiv-cs-ai

AUDITPLAN: Commit, Then Answer for Auditable Safety Alignment

arXiv:2609.19325v1 Announce Type: cross Abstract: Safety tuning pipelines judge only the final answer, which makes it difficult to distinguish robust refusal from two undesirable shortcuts: blanket re

Applications

AURA: Adaptive Uncertainty-Routed Analysis for Email Threat Detection

arXiv:2609.19873v1 Announce Type: new Abstract: Email spam and phishing attacks remain a critical security threat. Adversaries increasingly exploit large language models to craft contextually convinci

applicationsarxiv-cs-lg

Automated Goldsmith's Mark Retrieval in Silverware

arXiv:2609.20509v1 Announce Type: new Abstract: For art historians, goldsmith marks play a critical role in the identification and dating of artifacts. In practice, experts must manually compare a que

local-aiarxiv-cs-cv

Compact Vision Models for Iris Presentation Attack Detection under Presentation Attack Instrument Shift and Environmental Degradation

arXiv:2609.20386v1 Announce Type: new Abstract: Iris presentation attack detection (PAD) is security-critical when a subsystem that appears reliable during development encounters presentation attack i

CovR: Coverage-Aware Hardware Verification via Reasoning-Guided Reinforcement Learning

arXiv:2609.19189v1 Announce Type: cross Abstract: Design verification remains one of the most resource-intensive stages of hardware development, often consuming up to 70% of the total design effort. W

agentsarxiv-cs-cl

Deep Noir: Autonomous Steering Discovery via Architectural Chronometry in Transformer Models

arXiv:2609.20722v1 Announce Type: new Abstract: Activation steering modifies LLM behavior at inference time, but identifying where and how strongly to steer remains manual. We introduce Deep Noir, a f

agentsarxiv-cs-ai

Delphi Scanner: efficient and interpretable static malware detection via API sequence modeling

arXiv:2609.19900v1 Announce Type: cross Abstract: Static malware detection for Windows Portable Executable files demands a careful balance between detection effectiveness, computational efficiency, an

researcharxiv-cs-lg

DexTouch-WM: Learning Action-Conditioned Tactile World Models from Human Touch for Dexterous Robot Manipulation

arXiv:2609.20649v1 Announce Type: cross Abstract: Learning predictive models of contact-rich dexterous manipulation requires dense tactile interaction, but such data are costly to scale on real robots

safetyarxiv-cs-cv

Don't Mask the Environment: Observation Supervision Changes How Agents Explore Under RL

arXiv:2609.20715v1 Announce Type: cross Abstract: Agent trajectories record what an agent does and what happens next. Yet standard supervised fine-tuning (SFT) applies loss only to agent-authored acti

safetyarxiv-cs-ai

Evaluating Out-of-Distribution Robustness in Graph-Based Android Malware Classification: A New Principled Benchmark

model-releasesarxiv-cs-lg

arXiv:2508.06734v3 Announce Type: replace-cross Abstract: While graph-based Android malware classifiers report strong benchmark accuracy of over 94%, their performance sharply decreases up to 45% when

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

Applications

Federated Learning Framework for Privacy-Preserving Kidney Stone Detection

arXiv:2609.19740v1 Announce Type: new Abstract: Recent innovations in deep learning have significantly enhanced the diagnosis of medical images, although they are based on the use of centralized data

applicationsarxiv-cs-cv

Feeling Terrain Before Crossing: World Models for Off-Road Navigation

arXiv:2609.19863v1 Announce Type: cross Abstract: Navigation world models plan by foresight, predicting the future that each candidate action sequence produces and selecting the best, rather than mapp

safetyarxiv-cs-cv

Fingerprinting Multimodal Large Language Models

arXiv:2609.20457v1 Announce Type: cross Abstract: While multimodal large language models (MLLMs) enable a wide range of image-text reasoning tasks, recent incidents indicate that they are vulnerable t

From Intent to Action: Benchmarking LLM Safety in Vehicle Voice Command Authorization

arXiv:2609.19630v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly integrated into vehicle voice assistants. But linking natural-language requests to vehicle functions creat

greCAPTCHA: Assessing Understanding as Evidence of Research Authorship Under Generative AI

arXiv:2609.20481v1 Announce Type: cross Abstract: Conferences, journals, funders, schools, and universities are struggling with a surge of potentially AI-generated submissions from ostensibly human au

researcharxiv-cs-ai

How Far Can Sub-3B Open Language Models Go in Zero-Shot Essay Scoring on an 8 GB Consumer GPU?

arXiv:2609.20250v1 Announce Type: new Abstract: Zero-shot essay scoring with large language models is usually demonstrated with proprietary API models, yet the settings where automated scoring is most

local-aiarxiv-cs-lg

Hybrid Residual Reinforcement Learning for Contact-Rich Robotic Book Insertion

arXiv:2609.19962v1 Announce Type: new Abstract: Placing a grasped book into a tight shelf is a compact but difficult contact-rich control problem: millimetre-scale pose error can turn a geometrically

safetyarxiv-cs-ro

Implementation of Tightly-Coupled SLAM Fusion of GPS, IMU, and LiDAR for Autonomous Vehicles

arXiv:2609.20321v1 Announce Type: new Abstract: Autonomous vehicles depend entirely on Simultaneous Localization and Mapping (SLAM) to navigate safely in unknown environments. However, relying on a si

agentsarxiv-cs-ro

Improving Generalization and Robustness in Offline Reinforcement Learning via Boundary-Aware Data Augmentation

arXiv:2609.20300v1 Announce Type: new Abstract: Current offline reinforcement learning (ORL) algorithms tend to overfit the training dataset and exhibit poor in-distribution generalization and robustn

Tutorials

LearnActCoder: Role-Aware Error Memory for Adaptive Clinical Coding Agents

arXiv:2609.19721v1 Announce Type: new Abstract: Clinical coding agents repeatedly encounter the same failure modes, including unsupported codes, missed documented conditions, specificity errors, and p

tutorialsarxiv-cs-ai

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

safetyarxiv-cs-ro

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

Model-based Bootstrap for Offline Policy Evaluation in Tabular Reinforcement Learning

arXiv:2609.20389v1 Announce Type: cross Abstract: Offline policy evaluation (OPE) is crucial in high-stakes reinforcement learning applications, where new policies must be assessed reliably before dep

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

researcharxiv-cs-lg

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

Perception, Layout, and Validation: Calibrated Confidence for Reliable Straight-Through Processing of Financial Documents

arXiv:2609.20110v1 Announce Type: new Abstract: Straight-through processing (STP) on extracted key-value fields from financial documents without human review requires a calibrated probability together

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

Queries Knew More Than We Thought: Uncovering Latent Knowledge in Segmentation Models

arXiv:2609.20283v1 Announce Type: new Abstract: Modern segmenters often fail after the expensive computation has already been done: a useful mask is present among the model's query-conditioned candida

researcharxiv-cs-cv

Radio-Frequency Convolutional Neural Networks

arXiv:2609.19279v1 Announce Type: new Abstract: Running artificial intelligence (AI) models directly on edge devices such as smartphones, wearables, and drones offers low latency, pervasive scalabilit

researcharxiv-cs-lg

RAFT: A Stateful Retrieval-Augmented Framework for Troubleshooting Agents

arXiv:2609.20754v1 Announce Type: new Abstract: Effective troubleshooting agents in enterprise customer support depend on retrieving actionable guidance from similar historical cases, yet existing ret

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

safetyarxiv-cs-ro

Applications

RISC-V and machine learning: a survey

arXiv:2609.20677v1 Announce Type: new Abstract: The intersection of open-source processor architectures and machine learning is driving the demand for customizable, efficient, and accessible hardware.

applicationsarxiv-cs-lg