Search: “deployment”

Casting the Net! Revisiting MasterFace Impersonation Attacks

arXiv:2608.06952v1 Announce Type: cross Abstract: Impersonation is a fundamental security threat in face recognition systems (FRSs). While the security of FRSs has been challenged by various attack ve

applicationsarxiv-cs-cv

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Characterizing the Quality Profile of AI-Generated C++ in Production

DGX agent

arXiv:2608.06640v1 Announce Type: cross Abstract: The widespread integration of AI coding assistants offers undeniable boosts to engineering velocity. Yet, recent studies point to a growing trade-off,

applicationsarxiv-cs-ai

10 Aug 2026

CloudDiffusion: Diffusion-Based Scene Completion in the Point Cloud Domain

arXiv:2606.16048v3 Announce Type: replace Abstract: Reconstructing dense 3D scenes from sparse LiDAR point clouds (LiDAR scene completion) is a fundamental challenge in autonomous driving, where diffu

agentsarxiv-cs-cv

CoDAT: Collaborative Dual-Attention Transformer with Low-Cost Temporal Modeling for Efficient Edge Action Recognition

model-releasesarxiv-cs-cv

arXiv:2608.06691v1 Announce Type: new Abstract: Real-time human action recognition on Internet-of-Things (IoT) edge devices requires models that capture rich spatio-temporal cues within strict latency

Local Ai

Conformal Coverage Guarantees for Any Video Temporal Grounder

arXiv:2608.07434v1 Announce Type: new Abstract: Event boundaries in continuous video are ambiguous: re-annotate the same query-video pair and independent annotators mark moments that overlap by less t

local-aiarxiv-cs-cv

Critical Acclaim Orientation in Large Language Models: Evidence from Film Preference Elicitation

arXiv:2608.06955v1 Announce Type: new Abstract: Large language models (LLMs) are trained on corpora that contain expressions of human judgment about films, books, music, and more. Yet whether LLMs sys

CrossTracer: Cross-Embodiment Navigation via VLA Model Reasoning and Trace Residuals Adapting

model-releasesarxiv-cs-ro

arXiv:2608.06688v1 Announce Type: new Abstract: Vision-language-action (VLA) models provide strong semantic priors for robot navigation, but they often ignore embodiment-specific mobility constraints.

Curriculum as Code: An AI-Assisted Architecture for Instructional Design in STEM Education

arXiv:2608.07364v1 Announce Type: new Abstract: Contribution: This paper presents a six-phase AI-assisted instructional design architecture based on the Curriculum as Code paradigm, integrating Genera

applicationsarxiv-cs-ai

Depth-Wise Probing and Pruning of the Planning Token in a Driving Vision-Language-Action Model

arXiv:2608.07361v1 Announce Type: cross Abstract: Vision-language-action (VLA) models route driving decisions through a deep language model, but it is unclear how much of that depth the action itself

Do 3D Medical Foundation Models See Through MRI Artifacts? A Controlled Study of Representation Robustness

arXiv:2608.06613v1 Announce Type: cross Abstract: Self-supervised 3D medical foundation models are increasingly used as general-purpose feature extractors, yet their sensitivity to MRI artifacts remai

safetyarxiv-cs-ai

Do Audio Language Models Use Paralinguistic Evidence? Counterfactual Audits for Response Evaluation

model-releasesarxiv-cs-cl

arXiv:2608.06718v1 Announce Type: new Abstract: Audio-language models (ALMs) are increasingly used as judges for speech-to-speech systems, but a judge that receives audio may not actually use paraling

Local Ai

Dual-Node NVIDIA DGX Spark over Tailscale: A Remote-Access Testbed for Distributed LLM Training and Cyber-Threat-Intelligence Fine-Tuning

arXiv:2608.07226v1 Announce Type: cross Abstract: Compact AI systems make local language-model experimentation increasingly accessible, yet practical evidence for multi-node training on desktop-class

local-aiarxiv-cs-lg

GeoDistill-Refine: Silhouette-First Geometry Distillation for Annotation-Free Spacecraft Segmentation

arXiv:2608.07405v1 Announce Type: cross Abstract: Foundation segmentation models can provide supervision for spacecraft imagery without manual training masks, but their predictions vary with textual p

Let's Unlearn Stereotypes Before Decision-Making: Assessing the Impact of Intrinsic Bias Mitigation on Downstream Fairness in LLMs

arXiv:2509.16462v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly used in high-stakes decision-making systems, where biased predictions can reinforce social and economi

safetyarxiv-cs-cl

Tutorials

LoRAScan: Detecting Backdoor Prompts in Low-Rank Adapters for Large Language Models via Down-Projection Activation Spikes

arXiv:2608.06795v1 Announce Type: cross Abstract: Low-rank adaptation (LoRA) enables efficient specialization and distribution of large language models through compact adapters. However, untrusted ada

tutorialsarxiv-cs-ai

Multi-Level Modeling of Large Language Model Inference Latency and Energy via Hybrid Analytical--Machine-Learning Predictors

arXiv:2608.06723v1 Announce Type: cross Abstract: The rapid scaling of Large Language Models (LLMs) has significantly increased computational cost, energy consumption, and inference latency, making ac

MultiView-Bench: A Diagnostic Benchmark for World-Centric Multi-View Integration in VLMs

arXiv:2607.08970v2 Announce Type: replace-cross Abstract: Recent benchmarks for VLMs largely assess single- or limited-view perception, leaving untested the core cognitive ability to integrate observa

Pathryoshka: Compressing Pathology Foundation Models via Multi-Teacher Knowledge Distillation with Nested Embeddings

arXiv:2511.23204v2 Announce Type: replace Abstract: Pathology foundation models (FMs) have driven significant progress in computational pathology. However, these high-performing models can easily exce

PHOENIX: Fine-Tuned SLM-Powered Autonomous Satellite Lifetime Extension via Predictive Self-Healing and Multi-Agent AI Recovery

arXiv:2608.07126v1 Announce Type: cross Abstract: Most CubeSats, small and low-cost satellites roughly the size of a shoebox, do not survive as long as they were designed to: a study of 178 missions f

Prune Once: Retraining-Free Task-Agnostic Pruning for Vision-Language Models

arXiv:2608.06901v1 Announce Type: new Abstract: Vision-language models (VLMs) have achieved remarkable generalization across diverse multimodal tasks through large-scale pre-training, yet their rapidl

Representation Handoffs for OpenArm-Based Laboratory Mobile Manipulation

arXiv:2608.07154v1 Announce Type: cross Abstract: Open-source robotics and foundation models have lowered the barrier to embodied AI, yet language-guided laboratory automation still requires reliable

safetyarxiv-cs-ai

SetEasy: A Multi-Modal Classroom Engagement Assessment and Seating Optimization Framework

arXiv:2608.07188v1 Announce Type: new Abstract: SetEasy optimizes classroom engagement in fixed seating grids. It fuses multimodal sensing (wristband physiology, 4K video, environmental data) and trai

SNI-GNN: SmartNIC-Assisted Full-Graph GNN Training with In-Network Embedding Prediction

arXiv:2608.06441v1 Announce Type: new Abstract: Full-graph GNN training delivers high accuracy but scales poorly on multi-server clusters due to heavy, irregular inter-node embedding exchanges. We pre

safetyarxiv-cs-lg

SyncSBC: Decentralized Swarm Behavior Prediction for Synchronized Autonomous Control

arXiv:2608.06587v1 Announce Type: cross Abstract: Robot swarms utilize many independent limited-sensing agents to produce complex emergent behaviors without requiring centralized control. However, lit

TOFD: Target-Oriented Feature Decoupling against Poisoning Attacks in Split Federated Learning

arXiv:2608.07274v1 Announce Type: cross Abstract: Split Federated Learning (SFL) facilitates privacy-preserving collaborative training with reduced client-side overhead. However, its split architectur

Vehicle routing problem using deep reinforcement learning - A case study about truck planning in the industry

arXiv:2608.06668v1 Announce Type: new Abstract: As an important component of the supply chain industry, transportation has experienced rapid development in the past decade with the assistance of digit

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family

model-releasesarxiv-cs-cv

arXiv:2608.07051v1 Announce Type: new Abstract: Generic parameter-efficient fine-tuning (PEFT) methods transferred from language models can fail silently on real-time detectors, whose heterogeneous op

A Survey of Adversarial Efficiency Degradation for Vision Transformer by Exploiting Input-adaptive Optimization

arXiv:2608.05217v1 Announce Type: cross Abstract: Vision Transformers (ViTs) increasingly rely on input-adaptive inference, such as token pruning and early halting, to meet energy and latency budgets.

A System for Train Condition Monitoring and Structural Health Assessment of Rail Vehicles

arXiv:2608.05221v1 Announce Type: new Abstract: The ongoing digitalization of rail systems and the increasing use of artificial intelligence (AI) are fundamentally transforming the design, operation,

safetyarxiv-cs-ro

Bayesian adaptively-weighted ensembles for few-shot abdominal segmentation

arXiv:2608.05815v1 Announce Type: new Abstract: Few-shot learning has emerged as a promising approach for anatomical segmentation when labelled data are scarce. However, different few-shot learning al

Beyond Full-Model Rollback: AuroSFT for Adapter-State Multi-Task Fine-Tuning

model-releasesarxiv-cs-lg

arXiv:2608.05250v1 Announce Type: new Abstract: Multi-task supervised fine-tuning (SFT) often casts a heterogeneous data mixture as a single optimization problem, even though different tasks may reach

Context Matters: Support Set Selection and Failure Detection for In-Context Medical Image Segmentation

arXiv:2608.05333v1 Announce Type: new Abstract: In-context learning (ICL) adapts medical image segmentation models to unseen structures and modalities without retraining by conditioning on a task-spec

Local Ai

Curia-MAE: Multi-Modal Multi-Anatomy MAE Pre-Training for 3D Medical Image Segmentation

arXiv:2608.05844v1 Announce Type: new Abstract: Radiology foundation models learn transferable representations that can be adapted to new tasks by training only small layers on top of a frozen encoder

local-aiarxiv-cs-cv

EvoHarness-RL: Learning Self-Evolving Runtime Harness for Long-Horizon LLM Agents

arXiv:2608.05446v1 Announce Type: cross Abstract: Long-horizon LLM agents increasingly rely on external execution support to maintain state, track progress, invoke tools, verify outcomes, and reuse ex

safetyarxiv-cs-cl

F^2Agent: Financial Fusion of Agentic Intelligence for Multimodal Trading

arXiv:2608.05668v1 Announce Type: cross Abstract: With increasingly diverse and heterogeneous information sources, effectively leveraging multimodal data is becoming pivotal for high-quality financial

Failing Gracefully: Mitigating Impact of Inevitable Robot Failures

arXiv:2608.05313v1 Announce Type: cross Abstract: Service robots operate in household environments shared with humans, pets, and everyday objects, where they are highly susceptible to failures such as

safetyarxiv-cs-ai

FormBharo: Designing and Evaluating a Voice Agent for Conversational Form Filling in Rural India

arXiv:2608.06027v1 Announce Type: cross Abstract: In India, almost every social benefit starts with a form, yet the people who need these benefits most are often unable to read or write. Reaching them

Hardware Keystores for AI Agent Signing Workflows: A Zero-Trust MCP Enforcement Architecture

arXiv:2608.06130v1 Announce Type: cross Abstract: AI agents performing cryptographic operations (signing Git commits, authenticating API calls, issuing certificates) currently store private keys in so

IMMENSE: Inductive Multi-perspective User Classification in Social Networks

arXiv:2608.05259v1 Announce Type: cross Abstract: Online social networks increasingly expose people to users who propagate discriminatory, hateful, and violent content. Young users, in particular, are

applicationsarxiv-cs-ai

KV-Skill: Forging Expertise in the Model's Native Language

model-releasesarxiv-cs-lg

arXiv:2608.05475v1 Announce Type: new Abstract: Task knowledge is commonly stored either as text in the prompt or as an update to model weights. Text is modular but must be interpreted on every use, w

Learning Globally Reusable Skills for Coding Agents

arXiv:2608.06153v1 Announce Type: cross Abstract: Automated skill evolution enables Large Language Model (LLM) agents to continuously improve without expensive retraining. However, existing approaches

NavTrust: Benchmarking Trustworthiness for Embodied Navigation

arXiv:2603.19229v2 Announce Type: replace-cross Abstract: There are two major categories of embodied navigation: Vision-Language Navigation (VLN), where agents navigate by following natural language i

nnMIL: A generalizable multiple instance learning framework for computational pathology

arXiv:2511.14907v2 Announce Type: replace Abstract: Computational pathology holds substantial promise for improving diagnosis and guiding treatment decisions. Recent pathology foundation models enable

applicationsarxiv-cs-cv

Online Reasoning Calibration: Test-Time Training Enables Generalizable Conformal LLM Reasoning

arXiv:2604.01170v2 Announce Type: replace-cross Abstract: While test-time scaling has enabled large language models to solve highly difficult tasks, state-of-the-art results come at exorbitant compute

PathCover: A Fast Convex Decomposition along a Path via Randomized Iterative Space Partitioning (RISP) on Point Clouds

arXiv:2608.05586v1 Announce Type: new Abstract: Autonomous robot navigation requires the rapid generation of obstacle-free regions for trajectory planning. However, existing corridor generators strugg

agentsarxiv-cs-ro

PhaseCoder: Microphone Geometry-Agnostic Spatial Audio Understanding for Multimodal LLMs

arXiv:2601.21124v2 Announce Type: replace-cross Abstract: Current multimodal LLMs process audio as a mono stream, ignoring the rich spatial information essential for embodied AI. Existing spatial audi

Plausible Patients, Impossible Populations: Auditing Epidemiological Fidelity in Large Language Model Mental Health Simulations

arXiv:2604.17359v2 Announce Type: replace-cross Abstract: Language models asked to simulate psychiatric patients produce cases that survive inspection one at a time and populations that match no real

Revisiting Black-Box Model Ownership Verification through Information Theory

arXiv:2409.06130v2 Announce Type: replace-cross Abstract: Modern machine learning models require substantial computational resources and data to train, making them valuable intellectual property. Mode

applicationsarxiv-cs-ai