Search: “deployment”

Lightweight Cross-Spectral Face Recognition via Contrastive Alignment and Distillation

arXiv:2605.04769v1 Announce Type: new Abstract: Heterogeneous Face Recognition (HFR) aims at matching face images captured across different sensing modalities, such as thermal-to-visible or near-infra

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Safety

Mechanical Conscience: A Mathematical Framework for Dependability of Machine Intelligenc

DGX agent

arXiv:2605.03847v1 Announce Type: new Abstract: Distributed collaborative intelligence (DCI), encompassing edge-to-edge architectures, federated learning, transfer learning, and swarm systems, creates

safetyarxiv-cs-ai

7 May 2026

MIRAGE: Retrieval and Generation of Multimodal Images and Texts for Medical Education

arXiv:2605.04772v1 Announce Type: new Abstract: Access to diverse, well-annotated medical images with interactive learning tools is fundamental for training practitioners in medicine and related field

applicationsarxiv-cs-cv

Model Quantization: Post-Training Quantization Using NVIDIA Model Optimizer

Post-training quantization is a technique that reduces model size and improves inference performance by converting weights and activations to lower precision formats after training is complete. NVIDIA

local-ainvidia-developer

Tutorials

Multi Language Models for On-the-Fly Syntax Highlighting

arXiv:2510.04166v2 Announce Type: replace-cross Abstract: Syntax highlighting is a critical feature in modern software development environments, enhancing code readability and developer productivity.

tutorialsarxiv-cs-ai

Physics-Grounded Multi-Agent Architecture for Traceable, Risk-Aware Human-AI Decision Support in Manufacturing

arXiv:2605.04003v1 Announce Type: cross Abstract: High-precision CNC machining of free-form aerospace components requires bounded compensations informed by inspection, simulation, and process knowledg

Privacy-Preserving Empathy Detection in Video Interactions

model-releasesarxiv-cs-cv

arXiv:2504.10808v3 Announce Type: replace Abstract: Detecting empathy from video interactions has emerging applications, yet raw videos that could be used for training AI models are rarely available d

Quantifying Trust: Financial Risk Management for Trustworthy AI Agents

arXiv:2604.03976v2 Announce Type: replace Abstract: Prior work on trustworthy AI emphasizes model-internal properties such as bias mitigation, adversarial robustness, and interpretability. As AI syste

safetyarxiv-cs-ai

Replacing Parameters with Preferences: Federated Alignment of Heterogeneous Vision-Language Models

arXiv:2605.03426v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have broad potential in privacy-sensitive domains such as healthcare and finance, yet strict data-sharing constraints rend

SafeRedir: Prompt Embedding Redirection for Robust Unlearning in Image Generation Models

arXiv:2601.08623v2 Announce Type: replace Abstract: Image generation models (IGMs), while capable of producing impressive and creative content, often memorize a wide range of undesirable concepts from

Scalable Object Detection in the Car Interior With Vision Foundation Models

model-releasesarxiv-cs-cv

arXiv:2508.19651v2 Announce Type: replace Abstract: AI tasks in the car interior like identifying and localizing externally introduced objects is crucial for response quality of personal assistants. H

Software Engineering for Self-Adaptive Robotics: A Research Agenda

arXiv:2505.19629v3 Announce Type: replace-cross Abstract: Self-adaptive robotic systems operate autonomously in dynamic and uncertain environments, requiring robust real-time monitoring and adaptive b

safetyarxiv-cs-ro

Stop Automating Peer Review Without Rigorous Evaluation

arXiv:2605.03202v1 Announce Type: new Abstract: Large language models offer a tempting solution to address the peer review crisis. This position paper argues that today's AI systems should not be used

researcharxiv-cs-ai

SymptomAI: Towards a Conversational AI Agent for Everyday Symptom Assessment

arXiv:2605.04012v1 Announce Type: new Abstract: Language models excel at diagnostic assessments on currated medical case-studies and vignettes, performing on par with, or better than, clinical profess

Temporal Structure Matters for Efficient Test-Time Adaptation in Wearable Human Activity Recognition

arXiv:2605.04617v1 Announce Type: new Abstract: Wearable human activity recognition (WHAR) models often suffer from performance degradation under real-world cross-user distribution shifts. Test-time a

Top skill to learn today: AI Agent Evaluation. Anyone can build AI agents now but the difference is in the quality that's only possible via …

Top skill to learn today: AI Agent Evaluation. Anyone can build AI agents now but the difference is in the quality that's only possible via proper evals. Wrote some thoughts on evaluating production A

agentsdair-ai--x

Topology-Constrained Quantized nnUNet for Efficient and Anatomically Accurate 3D Tooth Segmentation

arXiv:2605.04201v1 Announce Type: new Abstract: We propose a topology-constrained quantized nnUNet framework for efficient and anatomically accurate 3D tooth segmentation, addressing the challenges of

applicationsarxiv-cs-cv

Tutorials

Towards Adaptive Humanoid Control via Multi-Behavior Distillation and Reinforced Fine-Tuning

arXiv:2511.06371v3 Announce Type: replace Abstract: Humanoid robots are promising to learn a diverse set of human-like locomotion behaviors, including standing up, walking, running, and jumping. Howev

tutorialsarxiv-cs-ro

Towards Self-Referential Analytic Assessment: A Profile-Based Approach to L2 Writing Evaluation with LLMs

arXiv:2605.04298v1 Announce Type: new Abstract: Automated essay scoring (AES) research often relies on rank-based correlation metrics to validate analytic assessment. However, such metrics obscure bot

researcharxiv-cs-cl

UAV-VL-R1: Generalizing Vision-Language Models via Supervised Fine-Tuning and Multi-Stage GRPO for UAV Visual Reasoning

arXiv:2508.11196v2 Announce Type: replace Abstract: Recent advances in vision-language models (VLMs) have demonstrated strong generalization in natural image tasks. However, their performance often de

What Happens Inside Agent Memory? Circuit Analysis from Emergence to Diagnosis

arXiv:2605.03354v1 Announce Type: new Abstract: Agent memory failures are silent: an LLM-based agent can produce a fluent response even when it fails to extract, retain, or retrieve the information ne

Why Talent Transformation Is the Missing Focus of Enterprise AI

Enterprise AI implementations often fail due to insufficient focus on talent transformation and workforce upskilling, despite heavy investment in technology infrastructure. Organizations need to syste

applicationsdatabricks

Worth remembering when @janleike quit over OpenAI safety concerns.

Jan Leike, OpenAI's safety and alignment lead, resigned in May 2024, citing concerns about the company's commitment to safety practices and the deprioritization of safety work relative to product deve

safetygary-marcus--x

YOTOnet: Zero-Shot Cross-Domain Fault Diagnosis via Domain-Conditioned Mixture of Experts

arXiv:2605.04528v1 Announce Type: new Abstract: Mechanical equipment forms the critical backbone of modern industrial production, yet domain shift severely limits the generalization of deep learning b

applicationsarxiv-cs-lg

A Scoping Review of Deep Learning Methods for Photoplethysmography Data

arXiv:2401.12783v3 Announce Type: replace-cross Abstract: Background: Photoplethysmography (PPG) is a non-invasive optical sensing technique widely used to capture hemodynamic information, with broad

applicationsarxiv-cs-lg

Accelerating Inference of Discrete Autoregressive Normalizing Flows by Selective Jacobi Decoding

arXiv:2505.24791v2 Announce Type: replace Abstract: Discrete normalizing flows are promising generative models with advantages such as analytical log-likelihood computation and end-to-end training. Ho

researcharxiv-cs-lg

AfriVox-v2: A Domain-Verticalized Benchmark for In-the-Wild African Speech Recognition

model-releasesarxiv-cs-cl

arXiv:2605.03590v1 Announce Type: new Abstract: Recent large language models (LLMs) show strong speech recognition and translation capabilities for high-resource languages. However, African languages

Agentic Multi-Source Grounding for Enhanced Query Intent Understanding: A DoorDash Case Study

arXiv:2603.01486v2 Announce Type: replace Abstract: Accurately mapping user queries to business categories is a fundamental Information Retrieval challenge for multi-category marketplaces, where conte

AhaRobot: A Low-Cost Open-Source Bimanual Mobile Manipulator for Embodied AI

arXiv:2503.10070v2 Announce Type: replace-cross Abstract: Scaling Vision-Language-Action models for embodied manipulation demands large volumes of diverse manipulation data, yet the high cost of comme

applicationsarxiv-cs-lg

AI in Agriculture: A Survey of Deep Learning Techniques for Crops, Fisheries and Livestock

arXiv:2507.22101v2 Announce Type: replace Abstract: Crops, fisheries and livestock form the backbone of global food production, essential to feed the ever-growing global population. However, these sec

applicationsarxiv-cs-cv

Hardware

[AINews] Silicon Valley gets Serious about Services

Silicon Valley companies are increasingly shifting focus toward AI service offerings and applications rather than solely developing foundational models, reflecting a maturing market where practical de

hardwarelatent-space

An Empirical Study of Agent Skills for Healthcare: Practice, Gaps, and Governance

arXiv:2605.02709v1 Announce Type: new Abstract: Healthcare automation is shaped by local procedures and organizational constraints, so agent capabilities rarely transfer unchanged across settings. Age

local-aiarxiv-cs-ai

APIOT: Autonomous Vulnerability Management Across Bare-Metal Industrial OT Networks

arXiv:2605.02346v1 Announce Type: cross Abstract: Bare-metal operational technology (OT) devices -- especially the microcontrollers running Modbus/TCP and CoAP at the base of industrial control system

AsymK-Talker: Real-Time and Long-Horizon Talking Head Generation via Asymmetric Kernel Distillation

arXiv:2605.02948v1 Announce Type: new Abstract: Recent advances in diffusion models have markedly enhanced the visual fidelity of audio-driven talking head generation. Nevertheless, existing methods a

researcharxiv-cs-lg

Benchmarking Local Language Models for Social Robots using Edge Devices

arXiv:2605.03111v1 Announce Type: cross Abstract: Social-educational robots designed for socially interactive pedagogical support, such as the Robot Study Companion (RSC), rely on responsive, privacy-

local-aiarxiv-cs-cl

Benchmarking Logistic Regression, SVM, Naive Bayes, and IndoBERT Fine-Tuning for Sentiment Analysis on Indonesian Product Reviews

arXiv:2605.03439v1 Announce Type: new Abstract: The exponential growth of e-commerce platforms in Indonesia has generated a massive volume of user-generated product reviews. Analyzing the sentiment of

researcharxiv-cs-cl

BIT.UA-AAUBS at ArchEHR-QA 2026: Evaluating Open-Source and Proprietary LLMs via Prompting in Low-Resource QA

arXiv:2605.03618v1 Announce Type: new Abstract: This paper presents the joint participation of the BIT.UA and AAUBS groups in the ArchEHR-QA 2026 shared task, which focuses on clinical question answer

local-aiarxiv-cs-cl

Caliper-in-the-Loop: Black-Box Optimization for Hyperledger Fabric Performance Tuning

arXiv:2605.02690v1 Announce Type: cross Abstract: Hyperledger Fabric performance depends on many interacting configuration parameters, making manual tuning difficult. We study automated throughput tun

researcharxiv-cs-ai

Compress Then Adapt? No, Do It Together via Task-aware Union of Subspaces

arXiv:2605.02829v1 Announce Type: new Abstract: Adapting large pretrained models to diverse tasks is now routine, yet the two dominant strategies of parameter-efficient fine-tuning (PEFT) and low-rank

Coordination as an Architectural Layer for LLM-Based Multi-Agent Systems

model-releasesarxiv-cs-lg

arXiv:2605.03310v1 Announce Type: cross Abstract: Multi-agent LLM systems fail in production at rates between 41% and 87%, mostly due to coordination defects rather than base-model capability. Existin

Data driven approach for Outdoor Channel Prediction in 5G and Beyond

arXiv:2605.01777v1 Announce Type: cross Abstract: An evolution of Wireless Communications towards 5G and beyond provides improved user experience in terms of quality of services. Understanding and est

researcharxiv-cs-ai

EQUITRIAGE: A Fairness Audit of Gender Bias in LLM-Based Emergency Department Triage

model-releasesarxiv-cs-cl

arXiv:2605.03998v1 Announce Type: new Abstract: Emergency department triage assigns patients an acuity score that determines treatment priority, and clinical evidence documents persistent gender dispa

Erase Persona, Forget Lore: Benchmarking Multimodal Copyright Unlearning in Large Vision Language Models

model-releasesarxiv-cs-cv

arXiv:2605.03547v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs), trained on web-scale data, risk memorizing and regenerating copyrighted visual content such as characters and logo

Evaluating Reasoning Models for Queries with Presuppositions

arXiv:2605.03050v1 Announce Type: new Abstract: Millions of users turn to AI models for their information needs. It is conceivable that a large number of user queries contain assumptions that may be f

researcharxiv-cs-cl

FINER-SQL: Boosting Small Language Models for Text-to-SQL

arXiv:2605.03465v1 Announce Type: cross Abstract: Large language models have driven major advances in Text-to-SQL generation. However, they suffer from high computational cost, long latency, and data

safetyarxiv-cs-cl

Foundation-Model-Based Agents in Industrial Automation: Purposes, Capabilities, and Open Challenges

arXiv:2605.02592v1 Announce Type: new Abstract: Foundation models, particularly large language models, are increasingly integrated into agent architectures for industrial tasks such as decision suppor

Graph Reconstruction from Differentially Private GNN Explanations

model-releasesarxiv-cs-lg

arXiv:2605.03388v1 Announce Type: new Abstract: Regulatory frameworks such as GDPR increasingly require that ML predictions be accompanied by post-hoc explanations, even when raw data and trained mode

HAAS: A Policy-Aware Framework for Adaptive Task Allocation Between Humans and Artificial Intelligence Systems

arXiv:2605.02832v1 Announce Type: new Abstract: Deciding how to distribute work between humans and AI systems is a central challenge in organisational design. Most approaches treat this as a binary ch